From 18341e3d3f523a01876b2c2ffa6d14fc56c79029 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Tom=C3=A1=C5=A1=20Fr=C3=BDda?= <tomas.fryda@h2o.ai>
Date: Fri, 7 Jun 2024 11:27:52 +0200
Subject: [PATCH] GH-16177: Validate h2o 3 package on r 4 4 and add test image
 to jenkins (#16291)

* Add update dependencies for R 4.4.0

* Enable R 4.4.0 image

* Fix runit_GBM_weight_gamma.R

* Deal with .checkFieldsInMethod warning

* Add html tidy to the R image for CRAN check

* Fix runit_coxph_concordance.R test

* Fix runit_coxph_concordance_heart.R test

* Fix runit_coxph_predict.R

* Fix runit_pubdev_8945_coxph_all_interactions_mojo.R

* Fix runit_GBM_ecology.R

* Install uplift package even if it was archived

* Fix runit_GLM_libR_airlines.R

* Fix runit_GLM_offset.R

* Fix runit_PUBDEV_6037_fractionalbinomial_mojo.R

* Fix runit_PUBDEV_8638_bodyfat_RID_Binomial_compareR_test.R

* Fix runit_glrm_PUBDEV_3788_loss_by_col_err.R

* Fix runit_isofor_accuracy.R

* Fix runit_PUBDEV_8235_modelselection_gaussian_validation.R

* Fix runit_OLD_1079_airlines.R

* Fix runit_pubdev_6817_noK_PCA.R

* Fix runit_pca_5_golden.R

* Fix javapredict

* Fix runit_head_tail.R

* Fix runit_relevel.R

* Fix runit_import_upload_singlequoted.R

* Fix runit_ifelse.R

* Fix runit_h2oconfig.R and .parse.h2oconfig in config.R

* Fix runit_as.h2o_sparse.R

* Fix runit_pubdev_8218.R

* Fix runit_PUBDEV_7362_merge_duplicate_others.R

* Fix runit_pubdev_1654.R

* Fix runit_pubdev_1398.R

* Fix runit_pubdev_1383.R

* Fix runit_hexdev_29_categorical_continuous.R

* Fix runit_GLM_offset.R for R 3.5

* Add DT to R 4.4 image

* Do not set options(stringsAsFactors=TRUE) in the tests

* Fix runit_as.h2o_sparse.R

* Add new cran messages to validate_r_cmf_check_output.py

* More changes to the validate_r_cmd_check_output.py
---
 docker/Jenkinsfile-build-docker               |   2 +-
 docker/Makefile                               |  16 +
 docker/jenkins-images/Dockerfile-r            |   3 +-
 docker/scripts/install_R_version              | 655 ++++++++++++------
 h2o-r/h2o-package/R/config.R                  |   4 +-
 h2o-r/h2o-package/R/explain.R                 |   6 +-
 h2o-r/scripts/h2o-r-test-setup.R              |   1 -
 h2o-r/tests/runitUtils/shared_javapredict.R   |   2 +-
 .../coxph/runit_coxph_concordance.R           |   5 +-
 .../coxph/runit_coxph_concordance_heart.R     |   2 +-
 .../testdir_algos/coxph/runit_coxph_predict.R |   5 +-
 ..._pubdev_8945_coxph_all_interactions_mojo.R |   2 -
 .../testdir_algos/gbm/runit_GBM_ecology.R     |   2 +-
 .../gbm/runit_GBM_weight_gamma.R              |  15 +-
 .../glm/runit_GLM_libR_airlines.R             |   2 +
 .../testdir_algos/glm/runit_GLM_offset.R      |   6 +-
 ...unit_PUBDEV_6037_fractionalbinomial_mojo.R |   3 +-
 ..._8638_bodyfat_RID_Binomial_compareR_test.R |   1 -
 .../runit_glrm_PUBDEV_3788_loss_by_col_err.R  |   5 +-
 .../isofor/runit_isofor_accuracy.R            |   6 +-
 ..._8235_modelselection_gaussian_validation.R |   2 +-
 .../pca/runit_OLD_1079_airlines.R             |   1 -
 ...runit_pubdev_3502_pca_hangs_large_NOPASS.R |   1 -
 .../pca/runit_pubdev_6817_noK_PCA.R           |   1 -
 .../tests/testdir_golden/runit_pca_5_golden.R |   2 +-
 ...runit_PUBDEV_5008_ordinal_glm_mojo_large.R |   2 +-
 ...t_PUBDEV_5303_multinomial_glm_mojo_large.R |   2 +-
 ...unit_PUBDEV_5355_binomial_glm_mojo_large.R |   2 +-
 ...it_PUBDEV_5529_leaf_node_assign_gbm_mojo.R |   1 -
 ...unit_PUBDEV_7185_binomial_gam_mojo_large.R |   2 +-
 ...runit_PUBDEV_7185_quasibinomial_gam_MOJO.R |   2 +-
 ...unit_PUBDEV_7860_binomial_gam_TP_CS_MOJO.R |   2 +-
 ..._8330_fractionalbinomial_glm_MOJO_offset.R |   2 +-
 ...UBDEV_8330_quasibinomial_glm_MOJO_offset.R |   2 +-
 ...unit_PUBDEV_8330_tweedie_glm_MOJO_offset.R |   2 +-
 .../runit_pubdev_4531_large.R                 |   3 +-
 .../runit_pubdev_5351_pca_mojo_large.R        |   2 +-
 .../runit_pubdev_6617_setInvNumNA.R           |   1 -
 ...runit_PUBDEV_7362_merge_duplicate_others.R |  82 ++-
 .../runit_hexdev_29_categorical_continuous.R  |   3 +-
 .../runit_hexdev_29_import_types.R            |   1 -
 h2o-r/tests/testdir_jira/runit_pubdev_1383.R  |   2 +-
 h2o-r/tests/testdir_jira/runit_pubdev_1398.R  |   2 +-
 h2o-r/tests/testdir_jira/runit_pubdev_1654.R  |   2 +-
 .../runit_pubdev_5518_autoencoder_grid.R      |   1 -
 h2o-r/tests/testdir_jira/runit_pubdev_8218.R  |   6 +-
 .../testdir_misc/runit_PUBDEV-6775-2D-pdp.R   |   1 -
 .../tests/testdir_misc/runit_as.h2o_sparse.R  |   3 +-
 h2o-r/tests/testdir_misc/runit_h2oconfig.R    |   8 +-
 h2o-r/tests/testdir_misc/runit_ifelse.R       |   2 +-
 .../runit_import_upload_singlequoted.R        |   4 +-
 .../runit_pubdev_5921_na_prints_large.R       |   1 -
 h2o-r/tests/testdir_misc/runit_relevel.R      |   2 +-
 .../testdir_munging/unop/runit_head_tail.R    |   2 +-
 .../runit_GH_15741_force_col_types.R          |   1 -
 .../runit_GH_15741_parquet_force_col_types.R  |   1 -
 scripts/jenkins/groovy/buildConfig.groovy     |   2 +-
 .../jenkins/groovy/defineTestStages.groovy    |  16 +
 scripts/validate_r_cmd_check_output.py        |   7 +
 59 files changed, 600 insertions(+), 324 deletions(-)

diff --git a/docker/Jenkinsfile-build-docker b/docker/Jenkinsfile-build-docker
index c6ae3654059f..61f541ee9575 100644
--- a/docker/Jenkinsfile-build-docker
+++ b/docker/Jenkinsfile-build-docker
@@ -22,7 +22,7 @@ IMAGE_NAME_PREFIX = 'harbor.h2o.ai/opsh2oai/h2o-3'
 JDK_VERSIONS = ['8', '10', '11', '12', '13', '14', '15', '16', '17']
 JDK_VERSIONS_PY_R = ['8', '11', '17'] // stable, last-supported, latest
 PYTHON_VERSIONS = ['3.6', '3.7', '3.8', '3.9', '3.10', '3.11']
-R_VERSION = ['3.3.3', '3.4.1', '3.5.3', '3.6.2', '4.0.2']
+R_VERSION = ['3.3.3', '3.4.1', '3.5.3', '3.6.2', '4.0.2', '4.4.0']
 
 def pipelineContext
 
diff --git a/docker/Makefile b/docker/Makefile
index 1680a8c1f93b..9847d489c01c 100644
--- a/docker/Makefile
+++ b/docker/Makefile
@@ -276,6 +276,22 @@ ifeq ($(shell echo $(PUSH) | tr [:upper:] [:lower:] ),true)
 	docker push harbor.h2o.ai/opsh2oai/h2o-3/dev-r-4.0.2-jdk-$*:$(VERSION)
 endif
 
+ifneq ($(CI), 1)
+dev-r-4.4.0-jdk-%: dev-r-4.4.0
+endif
+dev-r-4.4.0-jdk-%:
+	docker build -t harbor.h2o.ai/opsh2oai/h2o-3/dev-r-4.4.0-jdk-$*:$(VERSION) \
+		$(NO_CACHE) \
+		-f jenkins-images/Dockerfile-jdk-others \
+		--build-arg FROM_VERSION=$(VERSION) \
+		--build-arg FROM_IMAGE=harbor.h2o.ai/opsh2oai/h2o-3/dev-r-4.4.0 \
+		--build-arg INSTALL_JAVA_VERSION=$* \
+		--build-arg H2O_BRANCH=$(H2O_BRANCH) \
+		.
+ifeq ($(shell echo $(PUSH) | tr [:upper:] [:lower:] ),true)
+	docker push harbor.h2o.ai/opsh2oai/h2o-3/dev-r-4.4.0-jdk-$*:$(VERSION)
+endif
+
 ifneq ($(CI), 1)
 dev-r-%: dev-r-base
 endif
diff --git a/docker/jenkins-images/Dockerfile-r b/docker/jenkins-images/Dockerfile-r
index e9b592580a9f..4acda2697da8 100644
--- a/docker/jenkins-images/Dockerfile-r
+++ b/docker/jenkins-images/Dockerfile-r
@@ -9,7 +9,8 @@ ENV R_VERSION=${R_VERSION}
 # In C, global variables with multiple tentative definitions now result in linker errors. With -fcommon such definitions
 # are silently merged during linking.). I tried using -fcommon but without much luck so due to the time constrain I
 # decided to use gcc-9 instead.
-RUN apt-get update && apt-get install -y gcc-9 gfortran-9 g++-9 tcl-dev tk-dev && apt-get clean && apt-get autoremove -y && \
+RUN apt-get update && apt-get install -y gcc-9 gfortran-9 g++-9 tcl-dev tk-dev tidy && \
+    apt-get clean && apt-get autoremove -y && \
     rm -rf /var/cache/apt/*  &&\
     update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-9 99 --slave /usr/bin/g++ g++ /usr/bin/g++-9 \
     --slave /usr/bin/gcov gcov /usr/bin/gcov-9 && update-alternatives --install /usr/bin/gfortran f95 /usr/bin/gfortran-9 99
diff --git a/docker/scripts/install_R_version b/docker/scripts/install_R_version
index bdc9d89e5a13..193e226e7ddc 100755
--- a/docker/scripts/install_R_version
+++ b/docker/scripts/install_R_version
@@ -111,7 +111,8 @@ function getAndInstallFromCRAN(){
   NAME="$1"
   VERSION="$2"
   getAndInstall "https://cran.r-project.org/src/contrib/Archive/${NAME}/${NAME}_${VERSION}.tar.gz" "$NAME" "$VERSION" || \
-  getAndInstall "https://cran.r-project.org/src/contrib/${NAME}_${VERSION}.tar.gz" "$NAME" "$VERSION" || exit 1
+  getAndInstall "https://cran.r-project.org/src/contrib/${NAME}_${VERSION}.tar.gz" "$NAME" "$VERSION" || \
+  getAndInstall "https://cloud.r-project.org/src/contrib/Archive/${NAME}/${NAME}_${VERSION}.tar.gz" "$NAME" "$VERSION" || exit 1
   set -x
 }
 
@@ -175,214 +176,452 @@ function getAndInstallFromCRAN(){
 
 # Install dependencies
 echo "Installing dependencies for R ${R_VERSION}"
-getAndInstallFromCRAN abind 1.4-5
-getAndInstallFromCRAN acepack 1.4.1
-getAndInstallFromCRAN AUC 0.3.0
-getAndInstallFromCRAN backports 1.3.0
-getAndInstallFromCRAN base64enc 0.1-3
-getAndInstallFromCRAN bit 4.0.4
-getAndInstallFromCRAN bitops 1.0-7
-getAndInstallFromCRAN boot 1.3-18
-getAndInstallFromCRAN brew 1.0-6
-getAndInstallFromCRAN brio 1.1.2
-getAndInstallFromCRAN clipr 0.7.1
-getAndInstallFromCRAN cluster 2.0.5
-getAndInstallFromCRAN codetools 0.2-15
-getAndInstallFromCRAN colorspace 2.0-2
-getAndInstallFromCRAN commonmark 1.7
-getAndInstallFromCRAN cpp11 0.4.1
-getAndInstallFromCRAN crayon 1.4.2
-getAndInstallFromCRAN curl 4.3.2
-getAndInstallFromCRAN data.table 1.14.2
-getAndInstallFromCRAN DEoptimR 1.0-9
-getAndInstallFromCRAN digest 0.6.28
-getAndInstallFromCRAN diptest 0.76-0
-getAndInstallFromCRAN evaluate 0.14
-getAndInstallFromCRAN fansi 0.5.0
-getAndInstallFromCRAN farver 2.1.0
-getAndInstallFromCRAN fastmap 1.1.0
-getAndInstallFromCRAN foreign 0.8-67
-getAndInstallFromCRAN formatR 1.11
-getAndInstallFromCRAN Formula 1.2-4
-getAndInstallFromCRAN fs 1.5.0
-getAndInstallFromCRAN futile.options 1.0.1
-getAndInstallFromCRAN generics 0.1.1
-getAndInstallFromCRAN getopt 1.20.3
-getAndInstallFromCRAN gitcreds 0.1.1
-getAndInstallFromCRAN glue 1.5.0
-getAndInstallFromCRAN gtable 0.3.0
-getAndInstallFromCRAN gtools 3.9.2
-getAndInstallFromCRAN HDtweedie 1.1
-getAndInstallFromCRAN highlight 0.5.0
-getAndInstallFromCRAN ini 0.3.1
-getAndInstallFromCRAN isoband 0.2.5
-getAndInstallFromCRAN iterators 1.0.13
-getAndInstallFromCRAN jsonlite 1.7.2
-getAndInstallFromCRAN kernlab 0.9-29
-getAndInstallFromCRAN KernSmooth 2.23-15
-getAndInstallFromCRAN labeling 0.4.2
-getAndInstallFromCRAN lattice 0.20-34
-getAndInstallFromCRAN lazyeval 0.2.2
-getAndInstallFromCRAN LiblineaR 1.94-2
-getAndInstallFromCRAN magrittr 2.0.1
-getAndInstallFromCRAN MASS 7.3-45
-getAndInstallFromCRAN mclust 5.4.8
-getAndInstallFromCRAN mime 0.12
-getAndInstallFromCRAN misc3d 0.9-1
-getAndInstallFromCRAN mlbench 2.1-3
-getAndInstallFromCRAN MLmetrics 1.0.0
-getAndInstallFromCRAN modeltools 0.2-23
-getAndInstallFromCRAN mvtnorm 1.0-0
-getAndInstallFromCRAN nnet 7.3-12
-getAndInstallFromCRAN packrat 0.7.0
-getAndInstallFromCRAN pixmap 0.4-12
-getAndInstallFromCRAN pkgconfig 2.0.3
-getAndInstallFromCRAN praise 1.0.0
-getAndInstallFromCRAN prettyunits 1.1.1
-getAndInstallFromCRAN proxy 0.4-20
-getAndInstallFromCRAN ps 1.6.0
-getAndInstallFromCRAN R.methodsS3 1.8.1
-getAndInstallFromCRAN R6 2.5.1
-getAndInstallFromCRAN randomForest 4.6-14
-getAndInstallFromCRAN rappdirs 0.3.3
-getAndInstallFromCRAN RColorBrewer 1.1-2
-getAndInstallFromCRAN Rcpp 1.0.12
-getAndInstallFromCRAN RcppParallel 5.1.4
-getAndInstallFromCRAN remotes 2.4.1
-getAndInstallFromCRAN rlang 1.0.0
-getAndInstallFromCRAN rpart 4.1-10
-getAndInstallFromCRAN rprojroot 2.0.2
-getAndInstallFromCRAN rstudioapi 0.13
-getAndInstallFromCRAN RUnit 0.4.32
-getAndInstallFromCRAN slam 0.1-40
-getAndInstallFromCRAN sourcetools 0.1.7
-getAndInstallFromCRAN SparseM 1.81
-getAndInstallFromCRAN sparsepp 1.22
-getAndInstallFromCRAN spatial 7.3-11
-getAndInstallFromCRAN statmod 1.4.36
-getAndInstallFromCRAN stringi 1.7.5
-getAndInstallFromCRAN svd 0.5
-getAndInstallFromCRAN sys 3.4
-getAndInstallFromCRAN systemfonts 0.2.3
-getAndInstallFromCRAN tweedie 2.3.5
-getAndInstallFromCRAN utf8 1.2.2
-getAndInstallFromCRAN uuid 1.0-3
-getAndInstallFromCRAN versions 0.3
-getAndInstallFromCRAN viridisLite 0.4.0
-getAndInstallFromCRAN whisker 0.4
-getAndInstallFromCRAN withr 2.4.2
-getAndInstallFromCRAN xfun 0.28
-getAndInstallFromCRAN xml2 1.3.2
-getAndInstallFromCRAN xtable 1.8-4
-getAndInstallFromCRAN yaml 2.2.1
-getAndInstallFromCRAN zip 2.2.0
-getAndInstallFromCRAN checkmate 2.0.0
-getAndInstallFromCRAN bit64 4.0.5
-getAndInstallFromCRAN caTools 1.17.1.4
-getAndInstallFromCRAN RCurl 1.95-4.12
-getAndInstallFromCRAN munsell 0.5.0
-getAndInstallFromCRAN diffobj 0.3.5
-getAndInstallFromCRAN robustbase 0.93-7
-getAndInstallFromCRAN lambda.r 1.2.4
-getAndInstallFromCRAN optparse 1.7.1
-getAndInstallFromCRAN cli 3.1.0
-getAndInstallFromCRAN gridExtra 2.3
-getAndInstallFromCRAN foreach 1.5.1
-getAndInstallFromCRAN Matrix 1.2-8
-getAndInstallFromCRAN nlme 3.1-131
-getAndInstallFromCRAN sp 1.4-5
-getAndInstallFromCRAN class 7.3-14
-getAndInstallFromCRAN prabclus 2.3-2
-getAndInstallFromCRAN plot3D 1.4
-getAndInstallFromCRAN flexmix 2.3-17
-getAndInstallFromCRAN R.oo 1.24.0
-getAndInstallFromCRAN processx 3.5.2
-getAndInstallFromCRAN latticeExtra 0.6-28
-getAndInstallFromCRAN RcppArmadillo 0.10.7.3.0
-getAndInstallFromCRAN cachem 1.0.6
-getAndInstallFromCRAN ellipsis 0.3.2
-getAndInstallFromCRAN htmltools 0.5.2
-getAndInstallFromCRAN later 1.3.0
-getAndInstallFromCRAN lifecycle 1.0.1
-getAndInstallFromCRAN purrr 0.3.4
-getAndInstallFromCRAN desc 1.4.0
-getAndInstallFromCRAN stringr 1.4.0
-getAndInstallFromCRAN askpass 1.1
-getAndInstallFromCRAN highr 0.9
-getAndInstallFromCRAN tinytex 0.35
-getAndInstallFromCRAN rversions 2.1.1
-getAndInstallFromCRAN gplots 3.1.1
-getAndInstallFromCRAN futile.logger 1.4.3
-getAndInstallFromCRAN sessioninfo 1.2.1
-getAndInstallFromCRAN glmnet 2.0-2
-getAndInstallFromCRAN irlba 2.3.3
-getAndInstallFromCRAN survival 2.44-1.1
-getAndInstallFromCRAN xgboost 1.0.0.2
-getAndInstallFromCRAN mgcv 1.8-17
-getAndInstallFromCRAN ade4 1.7-18
-getAndInstallFromCRAN e1071 1.7-9
-getAndInstallFromCRAN flexclust 1.4-0
-getAndInstallFromCRAN fpc 2.2-9
-getAndInstallFromCRAN R.utils 2.11.0
-getAndInstallFromCRAN callr 3.7.0
-getAndInstallFromCRAN xopen 1.0.0
-getAndInstallFromCRAN memoise 2.0.0
-getAndInstallFromCRAN vctrs 0.3.8
-getAndInstallFromCRAN crosstalk 1.2.0
-getAndInstallFromCRAN fontawesome 0.2.2
-getAndInstallFromCRAN htmlwidgets 1.5.4
-getAndInstallFromCRAN jquerylib 0.1.4
-getAndInstallFromCRAN sass 0.4.0
-getAndInstallFromCRAN promises 1.2.0.1
-getAndInstallFromCRAN scales 1.1.1
-getAndInstallFromCRAN pkgload 1.2.3
-getAndInstallFromCRAN openssl 1.4.5
-getAndInstallFromCRAN knitr 1.36
-getAndInstallFromCRAN ROCR 1.0-7
-getAndInstallFromCRAN text2vec 0.5.0
-getAndInstallFromCRAN coin 1.0-0
-getAndInstallFromCRAN gbm 2.1.3
-getAndInstallFromCRAN penalized 0.9-51
-getAndInstallFromCRAN RItools 0.1-17
-getAndInstallFromCRAN pkgbuild 1.2.0
-getAndInstallFromCRAN webshot 0.5.2
-getAndInstallFromCRAN pillar 1.6.4
-getAndInstallFromCRAN tidyselect 1.1.1
-getAndInstallFromCRAN bslib 0.3.1
-getAndInstallFromCRAN httpuv 1.6.3
-getAndInstallFromCRAN credentials 1.3.0
-getAndInstallFromCRAN httr 1.4.2
-getAndInstallFromCRAN rsconnect 0.8.24
-getAndInstallFromCRAN htmlTable 2.3.0
-getAndInstallFromCRAN rmarkdown 2.11
-getAndInstallFromCRAN roxygen2 7.2.2
-getAndInstallFromCRAN tables 0.9.6
-getAndInstallFromCRAN rcmdcheck 1.4.0
-getAndInstallFromCRAN repr 1.1.3
-getAndInstallFromCRAN tibble 3.1.6
-getAndInstallFromCRAN shiny 1.7.1
-getAndInstallFromCRAN gert 1.3.0
-getAndInstallFromCRAN gh 1.3.0
-getAndInstallFromCRAN uplift 0.3.5
-getAndInstallFromCRAN IRdisplay 1.0
-getAndInstallFromCRAN dplyr 1.0.7
-getAndInstallFromCRAN ggplot2 3.3.5
-getAndInstallFromCRAN rematch2 2.1.2
-getAndInstallFromCRAN miniUI 0.1.1.1
-getAndInstallFromCRAN shinyjs 2.0.0
-getAndInstallFromCRAN usethis 2.0.1
-getAndInstallFromCRAN tidyr 1.1.4
-getAndInstallFromCRAN viridis 0.6.2
-getAndInstallFromCRAN pkgdown 1.5.1
-getAndInstallFromCRAN waldo 0.3.1
-getAndInstallFromCRAN manipulateWidget 0.11.1
-getAndInstallFromCRAN plotly 4.10.0
-getAndInstallFromCRAN Hmisc 4.3-0
-getAndInstallFromCRAN testthat 3.1.0
-getAndInstallFromCRAN rgl 0.100.54
-getAndInstallFromCRAN devtools 2.4.2
-getAndInstallFromCRAN plot3Drgl 1.0.2
 
+if [ "$R_VERSION" = "4.4.0" ]; then
+  getAndInstallFromCRAN abind 1.4-5
+  getAndInstallFromCRAN acepack 1.4.2
+  getAndInstallFromCRAN AUC 0.3.2
+  getAndInstallFromCRAN backports 1.5.0
+  getAndInstallFromCRAN base64enc 0.1-3
+  getAndInstallFromCRAN bit 4.0.5
+  getAndInstallFromCRAN bitops 1.0-7
+  getAndInstallFromCRAN boot 1.3-30
+  getAndInstallFromCRAN brew 1.0-10
+  getAndInstallFromCRAN brio 1.1.5
+  getAndInstallFromCRAN cli 3.6.2
+  getAndInstallFromCRAN clipr 0.8.0
+  getAndInstallFromCRAN cluster 2.1.6
+  getAndInstallFromCRAN codetools 0.2-20
+  getAndInstallFromCRAN colorspace 2.1-0
+  getAndInstallFromCRAN commonmark 1.9.1
+  getAndInstallFromCRAN cpp11 0.4.7
+  getAndInstallFromCRAN crayon 1.5.2
+  getAndInstallFromCRAN curl 5.2.1
+  getAndInstallFromCRAN data.table 1.15.4
+  getAndInstallFromCRAN deldir 2.0-4
+  getAndInstallFromCRAN DEoptimR 1.1-3
+  getAndInstallFromCRAN digest 0.6.35
+  getAndInstallFromCRAN diptest 0.77-1
+  getAndInstallFromCRAN evaluate 0.23
+  getAndInstallFromCRAN fansi 1.0.6
+  getAndInstallFromCRAN farver 2.1.2
+  getAndInstallFromCRAN fastmap 1.2.0
+  getAndInstallFromCRAN float 0.3-2
+  getAndInstallFromCRAN foreign 0.8-86
+  getAndInstallFromCRAN formatR 1.14
+  getAndInstallFromCRAN Formula 1.2-5
+  getAndInstallFromCRAN fs 1.6.4
+  getAndInstallFromCRAN futile.options 1.0.1
+  getAndInstallFromCRAN generics 0.1.3
+  getAndInstallFromCRAN getopt 1.20.4
+  getAndInstallFromCRAN gitcreds 0.1.2
+  getAndInstallFromCRAN glue 1.7.0
+  getAndInstallFromCRAN gtools 3.9.5
+  getAndInstallFromCRAN HDtweedie 1.2
+  getAndInstallFromCRAN highlight 0.5.1
+  getAndInstallFromCRAN ini 0.3.1
+  getAndInstallFromCRAN isoband 0.2.7
+  getAndInstallFromCRAN iterators 1.0.14
+  getAndInstallFromCRAN jpeg 0.1-10
+  getAndInstallFromCRAN jsonlite 1.8.8
+  getAndInstallFromCRAN kernlab 0.9-32
+  getAndInstallFromCRAN KernSmooth 2.23-24
+  getAndInstallFromCRAN labeling 0.4.3
+  getAndInstallFromCRAN lattice 0.22-6
+  getAndInstallFromCRAN lazyeval 0.2.2
+  getAndInstallFromCRAN LiblineaR 2.10-23
+  getAndInstallFromCRAN magrittr 2.0.3
+  getAndInstallFromCRAN MASS 7.3-60.2
+  getAndInstallFromCRAN matrixStats 1.3.0
+  getAndInstallFromCRAN mclust 6.1.1
+  getAndInstallFromCRAN mime 0.12
+  getAndInstallFromCRAN misc3d 0.9-1
+  getAndInstallFromCRAN mlbench 2.1-5
+  getAndInstallFromCRAN modeltools 0.2-23
+  getAndInstallFromCRAN mvtnorm 1.2-5
+  getAndInstallFromCRAN nnet 7.3-19
+  getAndInstallFromCRAN packrat 0.9.2
+  getAndInstallFromCRAN pixmap 0.4-13
+  getAndInstallFromCRAN pkgconfig 2.0.3
+  getAndInstallFromCRAN png 0.1-8
+  getAndInstallFromCRAN praise 1.0.0
+  getAndInstallFromCRAN prettyunits 1.2.0
+  getAndInstallFromCRAN proxy 0.4-27
+  getAndInstallFromCRAN ps 1.7.6
+  getAndInstallFromCRAN R.methodsS3 1.8.2
+  getAndInstallFromCRAN R6 2.5.1
+  getAndInstallFromCRAN randomForest 4.7-1.1
+  getAndInstallFromCRAN rappdirs 0.3.3
+  getAndInstallFromCRAN RColorBrewer 1.1-3
+  getAndInstallFromCRAN Rcpp 1.0.12
+  getAndInstallFromCRAN RcppParallel 5.1.7
+  getAndInstallFromCRAN remotes 2.5.0
+  getAndInstallFromCRAN renv 1.0.7
+  getAndInstallFromCRAN RhpcBLASctl 0.23-42
+  getAndInstallFromCRAN rlang 1.1.3
+  getAndInstallFromCRAN rpart 4.1.23
+  getAndInstallFromCRAN rprojroot 2.0.4
+  getAndInstallFromCRAN rstudioapi 0.16.0
+  getAndInstallFromCRAN RUnit 0.4.33
+  getAndInstallFromCRAN shape 1.4.6.1
+  getAndInstallFromCRAN slam 0.1-50
+  getAndInstallFromCRAN sourcetools 0.1.7-1
+  getAndInstallFromCRAN SparseM 1.83
+  getAndInstallFromCRAN sparsepp 1.22
+  getAndInstallFromCRAN spatial 7.3-17
+  getAndInstallFromCRAN statmod 1.5.0
+  getAndInstallFromCRAN stringi 1.8.4
+  getAndInstallFromCRAN svd 0.5.5
+  getAndInstallFromCRAN sys 3.4.2
+  getAndInstallFromCRAN tweedie 2.3.5
+  getAndInstallFromCRAN utf8 1.2.4
+  getAndInstallFromCRAN uuid 1.2-0
+  getAndInstallFromCRAN versions 0.3
+  getAndInstallFromCRAN viridisLite 0.4.2
+  getAndInstallFromCRAN whisker 0.4.1
+  getAndInstallFromCRAN withr 3.0.0
+  getAndInstallFromCRAN xfun 0.44
+  getAndInstallFromCRAN xtable 1.8-4
+  getAndInstallFromCRAN yaml 2.3.8
+  getAndInstallFromCRAN zip 2.3.1
+  getAndInstallFromCRAN checkmate 2.3.1
+  getAndInstallFromCRAN PKI 0.1-12
+  getAndInstallFromCRAN bit64 4.0.5
+  getAndInstallFromCRAN caTools 1.18.2
+  getAndInstallFromCRAN RCurl 1.98-1.14
+  getAndInstallFromCRAN sessioninfo 1.2.2
+  getAndInstallFromCRAN munsell 0.5.1
+  getAndInstallFromCRAN diffobj 0.3.5
+  getAndInstallFromCRAN robustbase 0.99-2
+  getAndInstallFromCRAN lambda.r 1.2.4
+  getAndInstallFromCRAN optparse 1.7.5
+  getAndInstallFromCRAN foreach 1.5.2
+  getAndInstallFromCRAN Matrix 1.7-0
+  getAndInstallFromCRAN nlme 3.1-164
+  getAndInstallFromCRAN sp 2.1-4
+  getAndInstallFromCRAN zoo 1.8-12
+  getAndInstallFromCRAN class 7.3-22
+  getAndInstallFromCRAN prabclus 2.3-3
+  getAndInstallFromCRAN plot3D 1.4.1
+  getAndInstallFromCRAN libcoin 1.0-10
+  getAndInstallFromCRAN flexmix 2.3-19
+  getAndInstallFromCRAN R.oo 1.26.0
+  getAndInstallFromCRAN desc 1.4.3
+  getAndInstallFromCRAN lgr 0.4.4
+  getAndInstallFromCRAN processx 3.8.4
+  getAndInstallFromCRAN RcppArmadillo 0.12.8.3.0
+  getAndInstallFromCRAN RcppEigen 0.3.4.0.0
+  getAndInstallFromCRAN interp 1.1-6
+  getAndInstallFromCRAN cachem 1.1.0
+  getAndInstallFromCRAN ellipsis 0.3.2
+  getAndInstallFromCRAN htmltools 0.5.8.1
+  getAndInstallFromCRAN later 1.3.2
+  getAndInstallFromCRAN lifecycle 1.0.4
+  getAndInstallFromCRAN xml2 1.3.6
+  getAndInstallFromCRAN askpass 1.2.0
+  getAndInstallFromCRAN highr 0.11
+  getAndInstallFromCRAN tinytex 0.51
+  getAndInstallFromCRAN gplots 3.1.3.1
+  getAndInstallFromCRAN futile.logger 1.4.3
+  getAndInstallFromCRAN irlba 2.3.5.1
+  getAndInstallFromCRAN MatrixExtra 0.1.15
+  getAndInstallFromCRAN mlapi 0.1.1
+  getAndInstallFromCRAN survival 3.6-4
+  getAndInstallFromCRAN xgboost 1.7.7.1
+  getAndInstallFromCRAN mgcv 1.9-1
+  getAndInstallFromCRAN ade4 1.7-22
+  getAndInstallFromCRAN sandwich 3.1-0
+  getAndInstallFromCRAN e1071 1.7-14
+  getAndInstallFromCRAN flexclust 1.4-2
+  getAndInstallFromCRAN fpc 2.2-12
+  getAndInstallFromCRAN R.utils 2.12.3
+  getAndInstallFromCRAN callr 3.7.6
+  getAndInstallFromCRAN xopen 1.0.1
+  getAndInstallFromCRAN latticeExtra 0.6-30
+  getAndInstallFromCRAN memoise 2.0.1
+  getAndInstallFromCRAN crosstalk 1.2.1
+  getAndInstallFromCRAN fontawesome 0.5.2
+  getAndInstallFromCRAN jquerylib 0.1.4
+  getAndInstallFromCRAN sass 0.4.9
+  getAndInstallFromCRAN promises 1.3.0
+  getAndInstallFromCRAN gtable 0.3.5
+  getAndInstallFromCRAN scales 1.3.0
+  getAndInstallFromCRAN systemfonts 1.1.0
+  getAndInstallFromCRAN vctrs 0.6.5
+  getAndInstallFromCRAN rversions 2.1.2
+  getAndInstallFromCRAN urlchecker 1.0.1
+  getAndInstallFromCRAN openssl 2.2.0
+  getAndInstallFromCRAN knitr 1.47
+  getAndInstallFromCRAN ROCR 1.0-11
+  getAndInstallFromCRAN rsparse 0.5.1
+  getAndInstallFromCRAN gbm 2.1.9
+  getAndInstallFromCRAN glmnet 4.1-8
+  getAndInstallFromCRAN penalized 0.9-52
+  getAndInstallFromCRAN TH.data 1.1-2
+  getAndInstallFromCRAN pkgbuild 1.4.4
+  getAndInstallFromCRAN webshot 0.5.5
+  getAndInstallFromCRAN bslib 0.7.0
+  getAndInstallFromCRAN httpuv 1.6.15
+  getAndInstallFromCRAN gridExtra 2.3
+  getAndInstallFromCRAN textshaping 0.4.0
+  getAndInstallFromCRAN downlit 0.4.3
+  getAndInstallFromCRAN pillar 1.9.0
+  getAndInstallFromCRAN purrr 1.0.2
+  getAndInstallFromCRAN stringr 1.5.1
+  getAndInstallFromCRAN tidyselect 1.2.1
+  getAndInstallFromCRAN credentials 2.0.1
+  getAndInstallFromCRAN httr 1.4.7
+  getAndInstallFromCRAN httr2 1.0.1
+  getAndInstallFromCRAN rsconnect 1.3.0
+  getAndInstallFromCRAN tables 0.9.25
+  getAndInstallFromCRAN MLmetrics 1.1.3
+  getAndInstallFromCRAN text2vec 0.6.4
+  getAndInstallFromCRAN multcomp 1.4-25
+  getAndInstallFromCRAN pkgload 1.3.4
+  getAndInstallFromCRAN rcmdcheck 1.4.0
+  getAndInstallFromCRAN rmarkdown 2.27
+  getAndInstallFromCRAN shiny 1.8.1.1
+  getAndInstallFromCRAN ragg 1.3.2
+  getAndInstallFromCRAN repr 1.1.7
+  getAndInstallFromCRAN tibble 3.2.1
+  getAndInstallFromCRAN gert 2.0.1
+  getAndInstallFromCRAN gh 1.4.1
+  getAndInstallFromCRAN coin 1.4-3
+  getAndInstallFromCRAN roxygen2 7.3.1
+  getAndInstallFromCRAN htmlwidgets 1.6.4
+  getAndInstallFromCRAN miniUI 0.1.1.1
+  getAndInstallFromCRAN shinyjs 2.1.0
+  getAndInstallFromCRAN IRdisplay 1.1
+  getAndInstallFromCRAN dplyr 1.1.4
+  getAndInstallFromCRAN ggplot2 3.5.1
+  getAndInstallFromCRAN pkgdown 2.0.9
+  getAndInstallFromCRAN rematch2 2.1.2
+  getAndInstallFromCRAN usethis 2.2.3
+  getAndInstallFromCRAN htmlTable 2.4.2
+  getAndInstallFromCRAN profvis 0.3.8
+  getAndInstallFromCRAN rgl 1.3.1
+  getAndInstallFromCRAN tidyr 1.3.1
+  getAndInstallFromCRAN viridis 0.6.5
+  getAndInstallFromCRAN waldo 0.5.2
+  getAndInstallFromCRAN plot3Drgl 1.0.4
+  getAndInstallFromCRAN plotly 4.10.4
+  getAndInstallFromCRAN RItools 0.3-3
+  getAndInstallFromCRAN Hmisc 5.1-3
+  getAndInstallFromCRAN testthat 3.2.1.1
+  getAndInstallFromCRAN devtools 2.4.5
+  getAndInstallFromCRAN uplift 0.3.5
+  getAndInstallFromCRAN DT 0.33
+  
+else
+  
+  getAndInstallFromCRAN abind 1.4-5
+  getAndInstallFromCRAN acepack 1.4.1
+  getAndInstallFromCRAN AUC 0.3.0
+  getAndInstallFromCRAN backports 1.3.0
+  getAndInstallFromCRAN base64enc 0.1-3
+  getAndInstallFromCRAN bit 4.0.4
+  getAndInstallFromCRAN bitops 1.0-7
+  getAndInstallFromCRAN boot 1.3-18
+  getAndInstallFromCRAN brew 1.0-6
+  getAndInstallFromCRAN brio 1.1.2
+  getAndInstallFromCRAN clipr 0.7.1
+  getAndInstallFromCRAN cluster 2.0.5
+  getAndInstallFromCRAN codetools 0.2-15
+  getAndInstallFromCRAN colorspace 2.0-2
+  getAndInstallFromCRAN commonmark 1.7
+  getAndInstallFromCRAN cpp11 0.4.1
+  getAndInstallFromCRAN crayon 1.4.2
+  getAndInstallFromCRAN curl 4.3.2
+  getAndInstallFromCRAN data.table 1.14.2
+  getAndInstallFromCRAN DEoptimR 1.0-9
+  getAndInstallFromCRAN digest 0.6.28
+  getAndInstallFromCRAN diptest 0.76-0
+  getAndInstallFromCRAN evaluate 0.14
+  getAndInstallFromCRAN fansi 0.5.0
+  getAndInstallFromCRAN farver 2.1.0
+  getAndInstallFromCRAN fastmap 1.1.0
+  getAndInstallFromCRAN foreign 0.8-67
+  getAndInstallFromCRAN formatR 1.11
+  getAndInstallFromCRAN Formula 1.2-4
+  getAndInstallFromCRAN fs 1.5.0
+  getAndInstallFromCRAN futile.options 1.0.1
+  getAndInstallFromCRAN generics 0.1.1
+  getAndInstallFromCRAN getopt 1.20.3
+  getAndInstallFromCRAN gitcreds 0.1.1
+  getAndInstallFromCRAN glue 1.5.0
+  getAndInstallFromCRAN gtable 0.3.0
+  getAndInstallFromCRAN gtools 3.9.2
+  getAndInstallFromCRAN HDtweedie 1.1
+  getAndInstallFromCRAN highlight 0.5.0
+  getAndInstallFromCRAN ini 0.3.1
+  getAndInstallFromCRAN isoband 0.2.5
+  getAndInstallFromCRAN iterators 1.0.13
+  getAndInstallFromCRAN jsonlite 1.7.2
+  getAndInstallFromCRAN kernlab 0.9-29
+  getAndInstallFromCRAN KernSmooth 2.23-15
+  getAndInstallFromCRAN labeling 0.4.2
+  getAndInstallFromCRAN lattice 0.20-34
+  getAndInstallFromCRAN lazyeval 0.2.2
+  getAndInstallFromCRAN LiblineaR 1.94-2
+  getAndInstallFromCRAN magrittr 2.0.1
+  getAndInstallFromCRAN MASS 7.3-45
+  getAndInstallFromCRAN mclust 5.4.8
+  getAndInstallFromCRAN mime 0.12
+  getAndInstallFromCRAN misc3d 0.9-1
+  getAndInstallFromCRAN mlbench 2.1-3
+  getAndInstallFromCRAN MLmetrics 1.0.0
+  getAndInstallFromCRAN modeltools 0.2-23
+  getAndInstallFromCRAN mvtnorm 1.0-0
+  getAndInstallFromCRAN nnet 7.3-12
+  getAndInstallFromCRAN packrat 0.7.0
+  getAndInstallFromCRAN pixmap 0.4-12
+  getAndInstallFromCRAN pkgconfig 2.0.3
+  getAndInstallFromCRAN praise 1.0.0
+  getAndInstallFromCRAN prettyunits 1.1.1
+  getAndInstallFromCRAN proxy 0.4-20
+  getAndInstallFromCRAN ps 1.6.0
+  getAndInstallFromCRAN R.methodsS3 1.8.1
+  getAndInstallFromCRAN R6 2.5.1
+  getAndInstallFromCRAN randomForest 4.6-14
+  getAndInstallFromCRAN rappdirs 0.3.3
+  getAndInstallFromCRAN RColorBrewer 1.1-2
+  getAndInstallFromCRAN Rcpp 1.0.12
+  getAndInstallFromCRAN RcppParallel 5.1.4
+  getAndInstallFromCRAN remotes 2.4.1
+  getAndInstallFromCRAN rlang 1.0.0
+  getAndInstallFromCRAN rpart 4.1-10
+  getAndInstallFromCRAN rprojroot 2.0.2
+  getAndInstallFromCRAN rstudioapi 0.13
+  getAndInstallFromCRAN RUnit 0.4.32
+  getAndInstallFromCRAN slam 0.1-40
+  getAndInstallFromCRAN sourcetools 0.1.7
+  getAndInstallFromCRAN SparseM 1.81
+  getAndInstallFromCRAN sparsepp 1.22
+  getAndInstallFromCRAN spatial 7.3-11
+  getAndInstallFromCRAN statmod 1.4.36
+  getAndInstallFromCRAN stringi 1.7.5
+  getAndInstallFromCRAN svd 0.5
+  getAndInstallFromCRAN sys 3.4
+  getAndInstallFromCRAN systemfonts 0.2.3
+  getAndInstallFromCRAN tweedie 2.3.5
+  getAndInstallFromCRAN utf8 1.2.2
+  getAndInstallFromCRAN uuid 1.0-3
+  getAndInstallFromCRAN versions 0.3
+  getAndInstallFromCRAN viridisLite 0.4.0
+  getAndInstallFromCRAN whisker 0.4
+  getAndInstallFromCRAN withr 2.4.2
+  getAndInstallFromCRAN xfun 0.28
+  getAndInstallFromCRAN xml2 1.3.2
+  getAndInstallFromCRAN xtable 1.8-4
+  getAndInstallFromCRAN yaml 2.2.1
+  getAndInstallFromCRAN zip 2.2.0
+  getAndInstallFromCRAN checkmate 2.0.0
+  getAndInstallFromCRAN bit64 4.0.5
+  getAndInstallFromCRAN caTools 1.17.1.4
+  getAndInstallFromCRAN RCurl 1.95-4.12
+  getAndInstallFromCRAN munsell 0.5.0
+  getAndInstallFromCRAN diffobj 0.3.5
+  getAndInstallFromCRAN robustbase 0.93-7
+  getAndInstallFromCRAN lambda.r 1.2.4
+  getAndInstallFromCRAN optparse 1.7.1
+  getAndInstallFromCRAN cli 3.1.0
+  getAndInstallFromCRAN gridExtra 2.3
+  getAndInstallFromCRAN foreach 1.5.1
+  getAndInstallFromCRAN Matrix 1.2-8
+  getAndInstallFromCRAN nlme 3.1-131
+  getAndInstallFromCRAN sp 1.4-5
+  getAndInstallFromCRAN class 7.3-14
+  getAndInstallFromCRAN prabclus 2.3-2
+  getAndInstallFromCRAN plot3D 1.4
+  getAndInstallFromCRAN flexmix 2.3-17
+  getAndInstallFromCRAN R.oo 1.24.0
+  getAndInstallFromCRAN processx 3.5.2
+  getAndInstallFromCRAN latticeExtra 0.6-28
+  getAndInstallFromCRAN RcppArmadillo 0.10.7.3.0
+  getAndInstallFromCRAN cachem 1.0.6
+  getAndInstallFromCRAN ellipsis 0.3.2
+  getAndInstallFromCRAN htmltools 0.5.2
+  getAndInstallFromCRAN later 1.3.0
+  getAndInstallFromCRAN lifecycle 1.0.1
+  getAndInstallFromCRAN purrr 0.3.4
+  getAndInstallFromCRAN desc 1.4.0
+  getAndInstallFromCRAN stringr 1.4.0
+  getAndInstallFromCRAN askpass 1.1
+  getAndInstallFromCRAN highr 0.9
+  getAndInstallFromCRAN tinytex 0.35
+  getAndInstallFromCRAN rversions 2.1.1
+  getAndInstallFromCRAN gplots 3.1.1
+  getAndInstallFromCRAN futile.logger 1.4.3
+  getAndInstallFromCRAN sessioninfo 1.2.1
+  getAndInstallFromCRAN glmnet 2.0-2
+  getAndInstallFromCRAN irlba 2.3.3
+  getAndInstallFromCRAN survival 2.44-1.1
+  getAndInstallFromCRAN xgboost 1.0.0.2
+  getAndInstallFromCRAN mgcv 1.8-17
+  getAndInstallFromCRAN ade4 1.7-18
+  getAndInstallFromCRAN e1071 1.7-9
+  getAndInstallFromCRAN flexclust 1.4-0
+  getAndInstallFromCRAN fpc 2.2-9
+  getAndInstallFromCRAN R.utils 2.11.0
+  getAndInstallFromCRAN callr 3.7.0
+  getAndInstallFromCRAN xopen 1.0.0
+  getAndInstallFromCRAN memoise 2.0.0
+  getAndInstallFromCRAN vctrs 0.3.8
+  getAndInstallFromCRAN crosstalk 1.2.0
+  getAndInstallFromCRAN fontawesome 0.2.2
+  getAndInstallFromCRAN htmlwidgets 1.5.4
+  getAndInstallFromCRAN jquerylib 0.1.4
+  getAndInstallFromCRAN sass 0.4.0
+  getAndInstallFromCRAN promises 1.2.0.1
+  getAndInstallFromCRAN scales 1.1.1
+  getAndInstallFromCRAN pkgload 1.2.3
+  getAndInstallFromCRAN openssl 1.4.5
+  getAndInstallFromCRAN knitr 1.36
+  getAndInstallFromCRAN ROCR 1.0-7
+  getAndInstallFromCRAN text2vec 0.5.0
+  getAndInstallFromCRAN coin 1.0-0
+  getAndInstallFromCRAN gbm 2.1.3
+  getAndInstallFromCRAN penalized 0.9-51
+  getAndInstallFromCRAN RItools 0.1-17
+  getAndInstallFromCRAN pkgbuild 1.2.0
+  getAndInstallFromCRAN webshot 0.5.2
+  getAndInstallFromCRAN pillar 1.6.4
+  getAndInstallFromCRAN tidyselect 1.1.1
+  getAndInstallFromCRAN bslib 0.3.1
+  getAndInstallFromCRAN httpuv 1.6.3
+  getAndInstallFromCRAN credentials 1.3.0
+  getAndInstallFromCRAN httr 1.4.2
+  getAndInstallFromCRAN rsconnect 0.8.24
+  getAndInstallFromCRAN htmlTable 2.3.0
+  getAndInstallFromCRAN rmarkdown 2.11
+  getAndInstallFromCRAN roxygen2 7.2.2
+  getAndInstallFromCRAN tables 0.9.6
+  getAndInstallFromCRAN rcmdcheck 1.4.0
+  getAndInstallFromCRAN repr 1.1.3
+  getAndInstallFromCRAN tibble 3.1.6
+  getAndInstallFromCRAN shiny 1.7.1
+  getAndInstallFromCRAN gert 1.3.0
+  getAndInstallFromCRAN gh 1.3.0
+  getAndInstallFromCRAN uplift 0.3.5
+  getAndInstallFromCRAN IRdisplay 1.0
+  getAndInstallFromCRAN dplyr 1.0.7
+  getAndInstallFromCRAN ggplot2 3.3.5
+  getAndInstallFromCRAN rematch2 2.1.2
+  getAndInstallFromCRAN miniUI 0.1.1.1
+  getAndInstallFromCRAN shinyjs 2.0.0
+  getAndInstallFromCRAN usethis 2.0.1
+  getAndInstallFromCRAN tidyr 1.1.4
+  getAndInstallFromCRAN viridis 0.6.2
+  getAndInstallFromCRAN pkgdown 1.5.1
+  getAndInstallFromCRAN waldo 0.3.1
+  getAndInstallFromCRAN manipulateWidget 0.11.1
+  getAndInstallFromCRAN plotly 4.10.0
+  getAndInstallFromCRAN Hmisc 4.3-0
+  getAndInstallFromCRAN testthat 3.1.0
+  getAndInstallFromCRAN rgl 0.100.54
+  getAndInstallFromCRAN devtools 2.4.2
+  getAndInstallFromCRAN plot3Drgl 1.0.2
+fi
 # dependecies from GitHub
 R_REMOTES_UPGRADE=never
 /usr/local/R/current/bin/R -e "chooseCRANmirror(graphics=FALSE, ind=1); library(devtools); \
diff --git a/h2o-r/h2o-package/R/config.R b/h2o-r/h2o-package/R/config.R
index e1ab833742a6..1fa754fc0cae 100644
--- a/h2o-r/h2o-package/R/config.R
+++ b/h2o-r/h2o-package/R/config.R
@@ -88,7 +88,7 @@
       ini_to_df = ini_to_df[,names]
       ini_to_df = data.frame(ini_to_df)
       colnames(ini_to_df) <- names
-      ini_to_df <- data.frame(lapply(ini_to_df, trimws))
+      ini_to_df <- data.frame(lapply(ini_to_df, trimws), stringsAsFactors = TRUE)
       return(ini_to_df)
     }
 
@@ -110,7 +110,7 @@
     }
     ini_to_df = subset(ini_to_df,select = names)
     colnames(ini_to_df) <- names
-    ini_to_df <- data.frame(lapply(ini_to_df, trimws))
+    ini_to_df <- data.frame(lapply(ini_to_df, trimws), stringsAsFactors = TRUE)
     return(ini_to_df)
 }
 
diff --git a/h2o-r/h2o-package/R/explain.R b/h2o-r/h2o-package/R/explain.R
index 2243388bbdb7..67220f3a323e 100644
--- a/h2o-r/h2o-package/R/explain.R
+++ b/h2o-r/h2o-package/R/explain.R
@@ -242,10 +242,10 @@ case_insensitive_match_arg <- function(arg, choices) {
       .self
     },
     get_model = function(model_id) {
-      model <- memoised_models$get_model(model_id)
-      if (!is.null(model@allparameters$treatment_column))
+      m <- memoised_models$get_model(model_id)
+      if (!is.null(m@allparameters$treatment_column))
         stop("Uplift models have not supported in explain yet.")
-      return(model)
+      return(m)
     }
   )
 )
diff --git a/h2o-r/scripts/h2o-r-test-setup.R b/h2o-r/scripts/h2o-r-test-setup.R
index 6bd0e25d851f..9fbcecca52a9 100755
--- a/h2o-r/scripts/h2o-r-test-setup.R
+++ b/h2o-r/scripts/h2o-r-test-setup.R
@@ -2,7 +2,6 @@
 .origEchoValue <- getOption("echo")
 options(echo=FALSE)
 options(scipen=999)
-options(stringsAsFactors=T)
 
 #'
 #'
diff --git a/h2o-r/tests/runitUtils/shared_javapredict.R b/h2o-r/tests/runitUtils/shared_javapredict.R
index 661cbbef6bc8..54ba6a17cc72 100644
--- a/h2o-r/tests/runitUtils/shared_javapredict.R
+++ b/h2o-r/tests/runitUtils/shared_javapredict.R
@@ -68,7 +68,7 @@ doJavapredictTest <- function(model,test_file,test_frame,params, separator=",",
   safeSystem(cmd)
 
   print("Comparing predictions between H2O and Java POJO")
-  prediction2 <- read.csv(sprintf("%s/out_pojo.csv", tmpdir_name), header=T)
+  prediction2 <- read.csv(sprintf("%s/out_pojo.csv", tmpdir_name), header=T, stringsAsFactors=TRUE)
   if (nrow(prediction1) != nrow(prediction2)) {
     warning("Prediction mismatch")
     print(paste("Rows from H2O", nrow(prediction1)))
diff --git a/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance.R b/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance.R
index 5ce5f56ebada..dfc606f794d3 100644
--- a/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance.R
+++ b/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance.R
@@ -15,11 +15,12 @@ test.CoxPH.concordance <- function() {
     
     rModel <- coxph(Surv(time, status) ~ age + sex + meal.cal + age:meal.cal, data = tstdata, ties = "efron")
     rPredictor <- rModel$linear.predictors
+    
     hexModel <- h2o.coxph(x = c("age", "sex", "meal.cal"), interaction_pairs = list(c("age", "meal.cal")),
                           event_column = "status", stop_column = "time", ties = "efron", training_frame = tstdataHex)
     hexPredictor <- pred(hexModel, tstdataHex)
-    
-    expect_equal(rPredictor, hexPredictor, scale = 1, tolerance = 1e-3)
+
+    expect_equal(rPredictor - mean(rPredictor), hexPredictor, scale = 1, tolerance = 1e-3)
     
     rConcordance <- unname(summary(rModel)$concordance)[1]
     hexConcordance <- h2o.performance(hexModel, data=tstdataHex)@metrics$concordance
diff --git a/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance_heart.R b/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance_heart.R
index ce2f0fcb5918..cce60312a173 100644
--- a/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance_heart.R
+++ b/h2o-r/tests/testdir_algos/coxph/runit_coxph_concordance_heart.R
@@ -26,7 +26,7 @@ test.CoxPH.predict <- function() {
     check.pred <- function(r.model, hex.model, r.tstdata, hex.tstdata) {
         fit.pred <- pred.r(r.model, r.tstdata)
         hex.lp <- pred.h2o(hex.model, hex.tstdata)
-        expect_equal(fit.pred, hex.lp, tolerance = 1e-5, scale = 1)
+        expect_equal(fit.pred - mean(fit.pred), hex.lp, tolerance = 1e-5, scale = 1)
     }
     
     check.concordance <- function (rModel, hexModel, data, tolerance = 1e-3) {
diff --git a/h2o-r/tests/testdir_algos/coxph/runit_coxph_predict.R b/h2o-r/tests/testdir_algos/coxph/runit_coxph_predict.R
index ced349a5ef72..64edb3092f6d 100644
--- a/h2o-r/tests/testdir_algos/coxph/runit_coxph_predict.R
+++ b/h2o-r/tests/testdir_algos/coxph/runit_coxph_predict.R
@@ -16,7 +16,10 @@ pred.h2o <- function(model, data) {
 compare.results <- function(fit, hex.fit, tstdata, tstdata.hex) {
     fit.pred <- pred.r(fit, tstdata)
     hex.lp <- pred.h2o(hex.fit, tstdata.hex)
-    expect_equal(fit.pred, hex.lp, tolerance = 1e-7, scale = 1)
+    w <- tstdata$weights
+    if (is.null(w))
+        w <- rep_len(1, length(fit.pred))
+    expect_equal(fit.pred - weighted.mean(fit.pred, w, na.rm=TRUE), hex.lp, tolerance = 1e-7, scale = 1)
 }
 
 cancer.with.sex <- function () {
diff --git a/h2o-r/tests/testdir_algos/coxph/runit_pubdev_8945_coxph_all_interactions_mojo.R b/h2o-r/tests/testdir_algos/coxph/runit_pubdev_8945_coxph_all_interactions_mojo.R
index cbd36d6f3259..0982925868c3 100644
--- a/h2o-r/tests/testdir_algos/coxph/runit_pubdev_8945_coxph_all_interactions_mojo.R
+++ b/h2o-r/tests/testdir_algos/coxph/runit_pubdev_8945_coxph_all_interactions_mojo.R
@@ -10,7 +10,6 @@ test.CoxPH.mojo_interactions_impl <- function(stratify_by = NULL) {
                            interaction_pairs = list(c("C1", "C3"), c("C1", "C2"), c("C3", "C4"), c("C4", "C2"),  c("C1", "age"), c("surgery", "C3")),
                            training_frame = training_frame)
 
-    browser()
     predict_h2o <- h2o.predict(coxph_h2o, training_frame)
     print(predict_h2o)
 
@@ -21,7 +20,6 @@ test.CoxPH.mojo_interactions_impl <- function(stratify_by = NULL) {
 
     predict_mojo <- h2o.predict(coxph_mojo, training_frame)
     print(predict_mojo)
-    browser()
 
     expect_equal(as.data.frame(predict_h2o), as.data.frame(predict_mojo))
 }
diff --git a/h2o-r/tests/testdir_algos/gbm/runit_GBM_ecology.R b/h2o-r/tests/testdir_algos/gbm/runit_GBM_ecology.R
index b34586373496..accf63f09824 100644
--- a/h2o-r/tests/testdir_algos/gbm/runit_GBM_ecology.R
+++ b/h2o-r/tests/testdir_algos/gbm/runit_GBM_ecology.R
@@ -40,7 +40,7 @@ test.GBM.ecology <- function() {
   print(ecology.sum)
   
   #import csv data for R to use
-  ecology.data <- read.csv(locate("smalldata/gbm_test/ecology_model.csv"), header = TRUE)
+  ecology.data <- read.csv(locate("smalldata/gbm_test/ecology_model.csv"), header = TRUE, stringsAsFactors=TRUE)
   ecology.data <- na.omit(ecology.data) #this omits NAs... does GBM do this? Perhaps better to model w/o doing this?
   
   Log.info("H2O GBM with parameters:\nntrees = 100, max_depth = 5, min_rows = 10, learn_rate = 0.1\n")
diff --git a/h2o-r/tests/testdir_algos/gbm/runit_GBM_weight_gamma.R b/h2o-r/tests/testdir_algos/gbm/runit_GBM_weight_gamma.R
index 29077cae8f5a..14101d3b5c3a 100644
--- a/h2o-r/tests/testdir_algos/gbm/runit_GBM_weight_gamma.R
+++ b/h2o-r/tests/testdir_algos/gbm/runit_GBM_weight_gamma.R
@@ -16,16 +16,15 @@ test <- function() {
 	#htable= as.h2o(table.1.2,destination_frame = "htable")
 	hh = h2o.gbm(x = 1:3,y = "medskad",training_frame = htable,distribution = "gamma",weights_column = "antskad",
              ntrees = 20,max_depth = 1,min_rows = 1,learn_rate = 1)
-	ph = as.vector(as.data.frame(h2o.predict(hh,newdata = htable)))
-	
+	ph = as.data.frame(h2o.predict(hh,newdata = htable))$predict
 	#expect_equal(gg$initF,hh@model$init_f,tolerance = 1e-6)
-	#expect_equal(min(pr),min(ph[,1]),tolerance = 1e-6)
-	#expect_equal(max(pr),max(ph[,1]),tolerance = 1e-6)
-	#expect_equal(mean(pr),mean(ph[,1]),tolerance = 1e-6)
+	#expect_equal(min(pr),min(ph),tolerance = 1e-6)
+	#expect_equal(max(pr),max(ph),tolerance = 1e-6)
+	#expect_equal(mean(pr),mean(ph),tolerance = 1e-6)
 	expect_equal(8.804447,hh@model$init_f,tolerance = 1e-6)
-	expect_equal(3751.01,min(ph[,1]),tolerance = 1e-4)
-	expect_equal(15291,max(ph[,1]),tolerance = 1e-4)
-	expect_equal(8119,mean(ph[,1]),tolerance = 1e-4)
+	expect_equal(3751.01,min(ph),tolerance = 1e-4)
+	expect_equal(15291,max(ph),tolerance = 1e-4)
+	expect_equal(8119,mean(ph),tolerance = 1e-4)
 	
 	
 }
diff --git a/h2o-r/tests/testdir_algos/glm/runit_GLM_libR_airlines.R b/h2o-r/tests/testdir_algos/glm/runit_GLM_libR_airlines.R
index ecfe7314453e..ad4ec4b0cf32 100644
--- a/h2o-r/tests/testdir_algos/glm/runit_GLM_libR_airlines.R
+++ b/h2o-r/tests/testdir_algos/glm/runit_GLM_libR_airlines.R
@@ -13,6 +13,8 @@ test.LiblineaR.airlines <- function() {
     Log.info("epsilon = 1E-4: Tolerance of termination criterion\n")
     Log.info("  cross =    0: No kfold cross-validation\n")
     
+    dimnames(test) <- dimnames(train)
+    
     LibR.m        <- LiblineaR(train, trainLabels,type=0, epsilon=1E-4, cost=100)
     LibRpreds     <- predict(LibR.m, test, proba=1, decisionValues=TRUE)
     LibRCM        <- table(testLabels, LibRpreds$predictions)
diff --git a/h2o-r/tests/testdir_algos/glm/runit_GLM_offset.R b/h2o-r/tests/testdir_algos/glm/runit_GLM_offset.R
index a40c585049ac..32d877981868 100644
--- a/h2o-r/tests/testdir_algos/glm/runit_GLM_offset.R
+++ b/h2o-r/tests/testdir_algos/glm/runit_GLM_offset.R
@@ -26,7 +26,7 @@ test <- function() {
 	hh = h2o.glm(x = 2:31,y = 1,training_frame = frm,family = "binomial",offset_column =  "off",lambda = 0)
 	gr = glm(formula = y~X1+X2 + X3 +X4 +X5+X6+X7+X8+X9+X10+ X11+X12+X13+X14+X15+X16+X17+X18+X19+ X20+X21+X22+X23+X24+X25+X26+X27+X28+X29+X30,
          family = "binomial",data = rfm,offset= rfm[,32]) 
-	gg = glmnet(x = as.matrix(rfm[,-c(1,32)]),y = as.factor(rfm[,1]),family = "binomial",lambda =0,offse = rfm[,32])        
+	gg = glmnet(x = as.matrix(rfm[,-c(1,32)]),y = as.factor(rfm[,1]),family = "binomial",lambda =0, offset = rfm[,32])        
 	print("compare results")
 	expect_equal(gr$null.deviance, hh@model$training_metrics@metrics$null_deviance)
 	expect_equal(gr$aic, hh@model$training_metrics@metrics$AIC,tolerance = 0.00001)
@@ -34,7 +34,7 @@ test <- function() {
 	expect_equal(gr$df.residual,hh@model$training_metrics@metrics$residual_degrees_of_freedom)
 	#predictions
 	ph = h2o.predict(object = hh,newdata = val)
-	pr = predict(object = gg,newx = as.matrix(valid[,-c(1,32)]),offset = as.matrix(valid[,32]),type = "response")
+	pr = predict(object = gg,newx = as.matrix(valid[,-c(1,32)]), newoffset = as.matrix(valid[,32]), offset = as.matrix(valid[,32]),type = "response")
 	print("compare predictions")
 	expect_equal(min(pr),min(ph$p1),tolerance = 0.0001)
 	expect_equal(max(pr),max(ph$p1),tolerance = 0.0001)
@@ -49,7 +49,7 @@ test <- function() {
 	expect_equal(deviance(gg),hh@model$training_metrics@metrics$residual_deviance,tolerance = 0.00001)
 	#predictions
 	ph = h2o.predict(object = hh,newdata = val)
-	pr = predict(object = gg,newx = as.matrix(valid[,-c(1,32)]),offset = as.matrix(valid[,32]),type = "response")
+	pr = predict(object = gg,newx = as.matrix(valid[,-c(1,32)]), newoffset = as.matrix(valid[,32]), offset = as.matrix(valid[,32]),type = "response")
 	print("compare predictions")
 	expect_equal(min(pr),min(ph$p1),tolerance = 0.0001)
 	expect_equal(max(pr),max(ph$p1),tolerance = 0.0001)
diff --git a/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_6037_fractionalbinomial_mojo.R b/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_6037_fractionalbinomial_mojo.R
index 7c5d9517f050..a01cad170895 100644
--- a/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_6037_fractionalbinomial_mojo.R
+++ b/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_6037_fractionalbinomial_mojo.R
@@ -9,14 +9,13 @@ test.fractionalbinomial <-
     # Run the test
     #----------------------------------------------------------------------
 
-      browser()
       params_prob_data <- setParmsData() # generate model parameters, random dataset
       modelAndDir<-buildModelSaveMojoGLM(params_prob_data$params) # build the model and save mojo
       filename = sprintf("%s/in.csv", modelAndDir$dirName) # save the test dataset into a in.csv file.
       h2o.downloadCSV(params_prob_data$tDataset[,params_prob_data$params$x], filename)
       twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename) # perform H2O and mojo prediction and return frames
       h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
       compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-4)
   }
 
diff --git a/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_8638_bodyfat_RID_Binomial_compareR_test.R b/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_8638_bodyfat_RID_Binomial_compareR_test.R
index b851c081610c..24cdef51e822 100644
--- a/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_8638_bodyfat_RID_Binomial_compareR_test.R
+++ b/h2o-r/tests/testdir_algos/glm/runit_PUBDEV_8638_bodyfat_RID_Binomial_compareR_test.R
@@ -9,7 +9,6 @@ source("../../../scripts/h2o-r-test-setup.R")
 test_RID_binomial_compareR <- function() {
   fat <- h2o.importFile(locate("smalldata/glm_test/bodyfat.csv"))
   bodyfat <- as.data.frame(fat)
-  browser()
   rGlmBinomial <- glm(bmi ~ neck+density+hip, data=bodyfat, family=binomial())
   dfbetasGlmB <- dfbetas(rGlmBinomial)
   hGlmBinomial <- h2o.glm(x=c("neck", "density", "hip"), y="bmi", lambda=0, family="binomial", standardize=FALSE, influence="dfbetas", training_frame=fat)
diff --git a/h2o-r/tests/testdir_algos/glrm/runit_glrm_PUBDEV_3788_loss_by_col_err.R b/h2o-r/tests/testdir_algos/glrm/runit_glrm_PUBDEV_3788_loss_by_col_err.R
index 158d91fb0d2c..f6aba8b57eec 100644
--- a/h2o-r/tests/testdir_algos/glrm/runit_glrm_PUBDEV_3788_loss_by_col_err.R
+++ b/h2o-r/tests/testdir_algos/glrm/runit_glrm_PUBDEV_3788_loss_by_col_err.R
@@ -7,12 +7,11 @@ test.glrm.pubdev.3788 <- function() {
     # Create data frame with a constant column
     data <- data.frame('NumericCol' = runif(50),
     'ConstantCol' = rep(1, 50),
-    'CategoricalCol' = sample(c("A", "B", "C", "D"), size = 50, replace = T))
+    'CategoricalCol' = sample(c("A", "B", "C", "D"), size = 50, replace = T),
+    stringsAsFactors = TRUE)
 
     data <- as.h2o(data)
 
-    browser()
-    
     # Specify loss by column and set ignore_const_cols to TRUE
     glrm_model <- h2o.glrm(data, k = 2, model_id = "glrm_test.hex",
     loss_by_col = c("Quadratic", "Categorical", "Categorical"),
diff --git a/h2o-r/tests/testdir_algos/isofor/runit_isofor_accuracy.R b/h2o-r/tests/testdir_algos/isofor/runit_isofor_accuracy.R
index de11ada0ccea..dceff0de9ca1 100644
--- a/h2o-r/tests/testdir_algos/isofor/runit_isofor_accuracy.R
+++ b/h2o-r/tests/testdir_algos/isofor/runit_isofor_accuracy.R
@@ -4,15 +4,15 @@ source("../../../scripts/h2o-r-test-setup.R")
 
 
 test.IsolationForest.accuracy <- function() {
-    set.seed(1234)
+    set.seed(12345)
     N = 1e6
     random_data <- data.frame(
         x = c(rnorm(N, 0, 0.5), rnorm(N*0.05, -2, 1)),
         y = c(rnorm(N, 0, 0.5), rnorm(N*0.05,  2, 1)),
-        outlier = c(rep("NO", N), rep("YES", (0.05*N)))
+        outlier = c(rep("NO", N), rep("YES", (0.05*N))),
+        stringsAsFactors = TRUE
     )
     random_data.hex <- as.h2o(random_data)
-
     # different approach than in the paper - build a smaller number of deeper trees trained on a much larger sample
     h2o_isolation_forest <- h2o.isolationForest(x = c("x", "y"), training_frame = random_data.hex[, c("x", "y")],
                                                 ntrees = 25, seed = 1234, sample_rate = 0.7, min_rows = 1000, max_depth = 16)
diff --git a/h2o-r/tests/testdir_algos/modelselection/runit_PUBDEV_8235_modelselection_gaussian_validation.R b/h2o-r/tests/testdir_algos/modelselection/runit_PUBDEV_8235_modelselection_gaussian_validation.R
index b480a1d3551f..ae25a0f41b9e 100644
--- a/h2o-r/tests/testdir_algos/modelselection/runit_PUBDEV_8235_modelselection_gaussian_validation.R
+++ b/h2o-r/tests/testdir_algos/modelselection/runit_PUBDEV_8235_modelselection_gaussian_validation.R
@@ -6,7 +6,7 @@ testModelSelectionV <- function() {
   bhexFV2 <- h2o.uploadFile(locate("smalldata/logreg/prostate.csv"))
   Y <- "GLEASON"
   X   <- c("AGE","RACE","CAPSULE","DCAPS","PSA","VOL","DPROS")
-  browser()
+  
   Log.info("Build the MaxRGLM model")
   allsubsetsModel <- h2o.modelSelection(y=Y, x=X, seed=12345, training_frame = bhexFV, max_predictor_number=2, 
   mode="allsubsets")
diff --git a/h2o-r/tests/testdir_algos/pca/runit_OLD_1079_airlines.R b/h2o-r/tests/testdir_algos/pca/runit_OLD_1079_airlines.R
index 893f1ccc31a5..856cb38eeb63 100644
--- a/h2o-r/tests/testdir_algos/pca/runit_OLD_1079_airlines.R
+++ b/h2o-r/tests/testdir_algos/pca/runit_OLD_1079_airlines.R
@@ -3,7 +3,6 @@ source("../../../scripts/h2o-r-test-setup.R")
 
 # Make sure we can run with airline data
 test.pca.airline<- function() {
-  browser()
   dimD = 234
   pp = h2o.uploadFile(locate("smalldata/airlines/AirlinesTest.csv.zip"))
   aa = h2o.prcomp(pp, k=dimD, transform="STANDARDIZE")
diff --git a/h2o-r/tests/testdir_algos/pca/runit_pubdev_3502_pca_hangs_large_NOPASS.R b/h2o-r/tests/testdir_algos/pca/runit_pubdev_3502_pca_hangs_large_NOPASS.R
index 41f6e6ca6cca..b151260dba8a 100644
--- a/h2o-r/tests/testdir_algos/pca/runit_pubdev_3502_pca_hangs_large_NOPASS.R
+++ b/h2o-r/tests/testdir_algos/pca/runit_pubdev_3502_pca_hangs_large_NOPASS.R
@@ -9,7 +9,6 @@ test.pca.la1s <- function() {
   run_time_c <- c()
   num_run <- 1
 
-  browser()
   dataR <- h2o.importFile(locate("bigdata/laptop/jira/la1s.wc.arff.txt.zip"), sep = ',', destination_frame = "data", header = T, parse = FALSE)
   data <- h2o.parseRaw(dataR, destination_frame = "bigParse",
                               parse_type = "CSV", header = T) # chunk_size = 124022500 size will make one chunk.
diff --git a/h2o-r/tests/testdir_algos/pca/runit_pubdev_6817_noK_PCA.R b/h2o-r/tests/testdir_algos/pca/runit_pubdev_6817_noK_PCA.R
index e4774d4048d8..fac014a57764 100644
--- a/h2o-r/tests/testdir_algos/pca/runit_pubdev_6817_noK_PCA.R
+++ b/h2o-r/tests/testdir_algos/pca/runit_pubdev_6817_noK_PCA.R
@@ -6,7 +6,6 @@ test.pca.arrests <- function() {
   Log.info("Importing USArrests.csv data...\n")
   arrests.hex <- h2o.uploadFile(locate("smalldata/pca_test/USArrests.csv"))
   arrests.pca.h2o <- h2o.prcomp(training_frame = arrests.hex, k = 1, seed=12345)
-  browser()
   pca_noK <- h2o.prcomp(training_frame = arrests.hex, seed=12345)
   
   pred1 <- h2o.predict(arrests.pca.h2o, arrests.hex)
diff --git a/h2o-r/tests/testdir_golden/runit_pca_5_golden.R b/h2o-r/tests/testdir_golden/runit_pca_5_golden.R
index b312391c63b1..d0fa3e841aa3 100644
--- a/h2o-r/tests/testdir_golden/runit_pca_5_golden.R
+++ b/h2o-r/tests/testdir_golden/runit_pca_5_golden.R
@@ -5,7 +5,7 @@ source("../../scripts/h2o-r-test-setup.R")
 
 test.poison.golden <- function() {
   Log.info("Importing poison.csv data...") 
-  poisonR <- read.csv(locate("smalldata/pca_test/poison.csv"), header = TRUE)
+  poisonR <- read.csv(locate("smalldata/pca_test/poison.csv"), header = TRUE, stringsAsFactors = TRUE)
   poisonH2O <- h2o.uploadFile(locate("smalldata/pca_test/poison.csv"), destination_frame = "poisonH2O")
   
   k_test <- sort(sample(1:8,3))
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5008_ordinal_glm_mojo_large.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5008_ordinal_glm_mojo_large.R
index e6088d867185..92ced338b1d2 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5008_ordinal_glm_mojo_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5008_ordinal_glm_mojo_large.R
@@ -15,7 +15,7 @@ test.ordinalGlm.mojo <-
     h2o.downloadCSV(params_prob_data$tDataset[,params_prob_data$params$x], filename)
     twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename) # perform H2O and mojo prediction and return frames
     h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-    h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+    h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
     compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-4)
   }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5303_multinomial_glm_mojo_large.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5303_multinomial_glm_mojo_large.R
index 548675cbf166..affa516fb7f8 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5303_multinomial_glm_mojo_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5303_multinomial_glm_mojo_large.R
@@ -15,7 +15,7 @@ test.multinomialGlm.mojo <-
       h2o.downloadCSV(params_prob_data$tDataset[,params_prob_data$params$x], filename)
       twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename) # perform H2O and mojo prediction and return frames
       h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
       compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-4)
   }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5355_binomial_glm_mojo_large.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5355_binomial_glm_mojo_large.R
index 15f58343b0f4..f6695a8c9fad 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5355_binomial_glm_mojo_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5355_binomial_glm_mojo_large.R
@@ -15,7 +15,7 @@ test.ordinalGlm.mojo <-
       h2o.downloadCSV(params_prob_data$tDataset[,params_prob_data$params$x], filename)
       twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename) # perform H2O and mojo prediction and return frames
       h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
       compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-4)
   }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5529_leaf_node_assign_gbm_mojo.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5529_leaf_node_assign_gbm_mojo.R
index 64fb8ed18062..d899777e056e 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5529_leaf_node_assign_gbm_mojo.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_5529_leaf_node_assign_gbm_mojo.R
@@ -16,7 +16,6 @@ test.gbm.leaf.assignment.mojo <-
       h2o.downloadCSV(params_prob_data$tDataset[,params_prob_data$params$x], filename)
       twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, get_leaf_node_assignment=TRUE) # perform H2O and mojo prediction and return frames
       print("Finished mojo.  Going to compare two frames")
-      browser()
       print(twoFrames)
       compareStringFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1)
     }, error = function(x) x)
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_binomial_gam_mojo_large.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_binomial_gam_mojo_large.R
index 3f950ad67e2f..aee634d0ac2a 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_binomial_gam_mojo_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_binomial_gam_mojo_large.R
@@ -20,7 +20,7 @@ test.binomial.gam.mojo <-
     h2o.downloadCSV(twoFrames$h2oPredict,
                     sprintf("%s/h2oPred.csv", modelAndDir$dirName))
     h2o.downloadCSV(twoFrames$mojoPredict,
-                    sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+                    sprintf("%s/mojoOut.csv", modelAndDir$dirName))
     compareFrames(
       twoFrames$h2oPredict,
       twoFrames$mojoPredict,
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_quasibinomial_gam_MOJO.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_quasibinomial_gam_MOJO.R
index 8a6fd74918c1..93b1b0e02748 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_quasibinomial_gam_MOJO.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7185_quasibinomial_gam_MOJO.R
@@ -41,7 +41,7 @@ test.GAM.quasibinomial <- function() {
   h2o.downloadCSV(htest[1:100, x], filename)
   twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, col.types=c("enum", "numeric", "numeric")) # perform H2O and mojo prediction and return frames
   h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
   twoFrames$h2oPredict[,1] <- h2o.asfactor(twoFrames$h2oPredict[,1])
   compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-6)
 }
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7860_binomial_gam_TP_CS_MOJO.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7860_binomial_gam_TP_CS_MOJO.R
index 8d2045e9a0cd..4de31d3874c4 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7860_binomial_gam_TP_CS_MOJO.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_7860_binomial_gam_TP_CS_MOJO.R
@@ -26,7 +26,7 @@ test.GAM.binomial <- function() {
   h2o.downloadCSV(test, filename)
   twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, col.types=c("enum", "numeric", "numeric")) # perform H2O and mojo prediction and return frames
   h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
   twoFrames$h2oPredict[,1] <- h2o.asfactor(twoFrames$h2oPredict[,1])
   compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-6)
 }
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_fractionalbinomial_glm_MOJO_offset.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_fractionalbinomial_glm_MOJO_offset.R
index 1e5d5b7151e4..507b769fe917 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_fractionalbinomial_glm_MOJO_offset.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_fractionalbinomial_glm_MOJO_offset.R
@@ -23,7 +23,7 @@ test.GLM.offset.fractionalbinomial <- function() {
   h2o.downloadCSV(hf[1:100, xOffset], filename)
   twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, col.types=c("numeric", "numeric", "numeric")) # perform H2O and mojo prediction and return frames
   h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
   compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-6)
 }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_quasibinomial_glm_MOJO_offset.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_quasibinomial_glm_MOJO_offset.R
index 065aa7f83af5..65bced0aca32 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_quasibinomial_glm_MOJO_offset.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_quasibinomial_glm_MOJO_offset.R
@@ -37,7 +37,7 @@ test.GLM.offset.quasibinomial <- function() {
   h2o.downloadCSV(hf[1:100, xOffset], filename)
   twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, col.types=c("numeric", "numeric", "numeric")) # perform H2O and mojo prediction and return frames
   h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
   predictFrame <- twoFrames$h2oPredict[, 2:3]
   mojoFrame <- twoFrames$mojoPredict[, 2:3]
   compareFrames(predictFrame, mojoFrame, prob=1, tolerance = 1e-6)
diff --git a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_tweedie_glm_MOJO_offset.R b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_tweedie_glm_MOJO_offset.R
index 7d3483d199be..3c1699f448f7 100644
--- a/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_tweedie_glm_MOJO_offset.R
+++ b/h2o-r/tests/testdir_javapredict/runit_PUBDEV_8330_tweedie_glm_MOJO_offset.R
@@ -24,7 +24,7 @@ test.GLM.offset.tweedie <- function() {
   h2o.downloadCSV(hf[1:100, xOffset], filename)
   twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename, col.types=c("numeric", "numeric", "numeric")) # perform H2O and mojo prediction and return frames
   h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+  h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
   compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-6)
 }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_pubdev_4531_large.R b/h2o-r/tests/testdir_javapredict/runit_pubdev_4531_large.R
index b0d9f584e784..08d4040d16a9 100644
--- a/h2o-r/tests/testdir_javapredict/runit_pubdev_4531_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_pubdev_4531_large.R
@@ -19,7 +19,6 @@ test <-
     test_file <- locate("smalldata/logreg/prostate_train_null_column_name.csv")
     test_frame <- h2o.importFile(test_file)
     params = prepTest()
-    browser()
     doJavapredictTest("gbm",test_file,test_frame,params)  # make sure original code run
 
     # check a separator that is not a special character
@@ -53,4 +52,4 @@ prepTest <- function() {
   return(params)
 }
 
-doTest("pubdev-4531: PredictCsv test", test)
\ No newline at end of file
+doTest("pubdev-4531: PredictCsv test", test)
diff --git a/h2o-r/tests/testdir_javapredict/runit_pubdev_5351_pca_mojo_large.R b/h2o-r/tests/testdir_javapredict/runit_pubdev_5351_pca_mojo_large.R
index 0cfe66c57166..2d13ea3eeb89 100644
--- a/h2o-r/tests/testdir_javapredict/runit_pubdev_5351_pca_mojo_large.R
+++ b/h2o-r/tests/testdir_javapredict/runit_pubdev_5351_pca_mojo_large.R
@@ -16,7 +16,7 @@ test.PCA.mojo <-
       h2o.downloadCSV(params_prob_data$tDataset, filename)
       twoFrames<-mojoH2Opredict(modelAndDir$model, modelAndDir$dirName, filename) # perform H2O and mojo prediction and return frames
       h2o.downloadCSV(twoFrames$h2oPredict, sprintf("%s/h2oPred.csv", modelAndDir$dirName))
-      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirname))
+      h2o.downloadCSV(twoFrames$mojoPredict, sprintf("%s/mojoOut.csv", modelAndDir$dirName))
       compareFrames(twoFrames$h2oPredict,twoFrames$mojoPredict, prob=1, tolerance = 1e-4)
   }
 
diff --git a/h2o-r/tests/testdir_javapredict/runit_pubdev_6617_setInvNumNA.R b/h2o-r/tests/testdir_javapredict/runit_pubdev_6617_setInvNumNA.R
index 7121f7694eae..df83640a3f4d 100644
--- a/h2o-r/tests/testdir_javapredict/runit_pubdev_6617_setInvNumNA.R
+++ b/h2o-r/tests/testdir_javapredict/runit_pubdev_6617_setInvNumNA.R
@@ -18,7 +18,6 @@ test.mojo.setInvNumNA <-
     params$y <- "C2"
     params$family <- "gaussian"
     modelAndDir<-buildModelSaveMojoGLM(params) # build the model and save mojo
-    browser()
     modelPred <- h2o.predict(modelAndDir$model, testModel) # predict with invalid row value replaced with mean value
     # get genmodel.jar pathname
     a = strsplit(modelAndDir$dirName, '/')
diff --git a/h2o-r/tests/testdir_jira/runit_PUBDEV_7362_merge_duplicate_others.R b/h2o-r/tests/testdir_jira/runit_PUBDEV_7362_merge_duplicate_others.R
index 3a5c19945d4c..49005fb01a1f 100644
--- a/h2o-r/tests/testdir_jira/runit_PUBDEV_7362_merge_duplicate_others.R
+++ b/h2o-r/tests/testdir_jira/runit_PUBDEV_7362_merge_duplicate_others.R
@@ -4,38 +4,40 @@ source("../../scripts/h2o-r-test-setup.R")
 # problem with merge.
 test <- function() {
     # code from Kuba
-    left <- as.h2o(data.frame(topic=c("A","B","C","D"), value=c(12,13,14,15))) # [A, 12][B, 13][C, 14][D, 15]
-    right <- as.h2o(data.frame(topic=c("Y","B","X","D"), bigValue=c(10000, 20000, 30000, 40000))) #[Y, 10000][B, 20000][X, 30000][D, 40000]
+    left <- as.h2o(data.frame(topic=c("A","B","C","D"), value=c(12,13,14,15), stringsAsFactors = TRUE)) # [A, 12][B, 13][C, 14][D, 15]
+    right <- as.h2o(data.frame(topic=c("Y","B","X","D"), bigValue=c(10000, 20000, 30000, 40000), stringsAsFactors = TRUE)) #[Y, 10000][B, 20000][X, 30000][D, 40000]
 
     merged <- h2o.merge(right, left, all.x = TRUE, method="radix")
-    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), bigvalue=c(20000, 40000, 30000, 10000), value = c(13, 15, NA, NA)))
+    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), bigvalue=c(20000, 40000, 30000, 10000), value = c(13, 15, NA, NA), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"topic"), h2o.arrange(resultF,"topic"))
     
     merged <- h2o.merge(left, right, all.y = TRUE, method="radix")
-    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), value = c(13, 15, NA, NA), bigvalue=c(20000, 40000, 30000, 10000)))
+    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), value = c(13, 15, NA, NA), bigvalue=c(20000, 40000, 30000, 10000), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"topic"), h2o.arrange(resultF,"topic"))
  
     merged <- h2o.merge(left, right, all.x = FALSE, all.y = FALSE, method="radix")
-    resultF <- as.h2o(data.frame(topic=c("B","D"), value = c(13, 15), bigvalue=c(20000, 40000)))
+    resultF <- as.h2o(data.frame(topic=c("B","D"), value = c(13, 15), bigvalue=c(20000, 40000), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"topic"), h2o.arrange(resultF,"topic"))
     
     merged <- h2o.merge(right, left, all.x = FALSE, all.y = FALSE, method="radix")
-    resultF <- as.h2o(data.frame(topic=c("B","D"), bigvalue=c(20000, 40000), value = c(13, 15)))
+    resultF <- as.h2o(data.frame(topic=c("B","D"), bigvalue=c(20000, 40000), value = c(13, 15), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"topic"), h2o.arrange(resultF,"topic"))
     
     # customer code
     left_hf <- as.h2o(data.frame(fruit = c(-177000000, -4000000, 100000000000, 200000000000, 1000000000000),
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue')))
-    right_hf <- as.h2o(data.frame(fruit = c(-177000000), citrus <- c(FALSE)))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue'), stringsAsFactors = TRUE))
+    right_hf <- as.h2o(data.frame(fruit = c(-177000000), citrus = c(FALSE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <- as.h2o(data.frame(fruit = c(100000000000,200000000000,1000000000000,-177000000,-4000000), 
-                                 color=c('yellow','red','blue','red','orange'), citrus=c(NA, NA, NA, FALSE, NA)))
+                                 color=c('yellow','red','blue','red','orange'), citrus=c(NA, NA, NA, FALSE, NA),
+                                 stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # left frame starts lower
-    left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256), color <- c('red', 'orange', 'yellow', 'red', 'blue')))
+    left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256), color = c('red', 'orange', 'yellow', 'red', 'blue'),
+     stringsAsFactors = TRUE))
     right_hf <- as.h2o( data.frame(fruit = c(258,518,517,1030,1028,1028,1030,2049),
-                                   citrus <- c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE,TRUE)))
+                                   citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE,TRUE)))
     merged2 <- h2o.merge(left_hf, right_hf, all.y = TRUE) # H2O give wrong answer
     print(merged2)
     resultF <- as.h2o(data.frame(fruit=c(258,517,518,1028,1028,1030,1030,2049),
@@ -45,13 +47,15 @@ test <- function() {
     
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     print(merged)
-    resultF <- as.h2o(data.frame(fruit=c(0,2,3,256,257), color=c('yellow','red','orange','blue','red'), citrus=c(NA,NA,NA,NA,NA)))
+    resultF <- as.h2o(data.frame(fruit=c(0,2,3,256,257), color=c('yellow','red','orange','blue','red'),
+    citrus=c(NA,NA,NA,NA,NA), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # both frame more or less overlapped
     left_hf <- as.h2o(data.frame(fruit = c(2,3,3,3,0,4,7,9,257,256,518,518,1028), 
                                  color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 
-                                           'cyan','red', 'orange', 'yellow', 'red', 'blue','negra')))
+                                           'cyan','red', 'orange', 'yellow', 'red', 'blue','negra'),
+                                 stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(3,3,3,3,6,8,12,14,258,518,518,517,1030,1028,1028,1030,2049), 
                                   citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE,TRUE, TRUE, FALSE, 
                                              FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE)))
@@ -61,7 +65,8 @@ test <- function() {
                                          'yellow','red','red','red','red','purple','cyan','red','yellow','orange',
                                          'red','red','blue','blue','negra','negra'),
                                  citrus=c(NA,NA,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,
-                                          NA,NA,NA,NA,NA,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE)))
+                                          NA,NA,NA,NA,NA,FALSE,FALSE,FALSE,FALSE,FALSE,FALSE),
+                                 stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     merged <- h2o.merge(left_hf, right_hf, all.x=FALSE, all.y=FALSE)
@@ -69,86 +74,87 @@ test <- function() {
                                  color=c('orange','orange','orange','orange','yellow','yellow','yellow','yellow',
                                          'red','red','red','red','red','red','blue','blue','negra','negra'),
                                  citrus=c(TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,TRUE,TRUE,FALSE,FALSE,
-                                          FALSE,FALSE,FALSE,FALSE,FALSE,FALSE)))
+                                          FALSE,FALSE,FALSE,FALSE,FALSE,FALSE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged, "fruit"), h2o.arrange(resultF,"fruit"))
     
     # both frame with duplicate keys
     # left frame starts higher and with overlap
-    left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256,518,1028), color <- c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan')))
-    right_hf <- as.h2o(data.frame(fruit = c(258,518,517,1030,1028,1030,1035), citrus <- c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE)))
+    left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256,518,1028), color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan'), stringsAsFactors = TRUE))
+    right_hf <- as.h2o(data.frame(fruit = c(258,518,517,1030,1028,1030,1035), citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE), stringsAsFactors = TRUE))
     merged <- h2o.merge(left_hf, right_hf, all.x = FALSE, all.y=FALSE)
-    resultF <- as.h2o(data.frame(fruit=c(518, 1028), color=c('purple', 'cyan'), citrus=c(TRUE, TRUE)))
+    resultF <- as.h2o(data.frame(fruit=c(518, 1028), color=c('purple', 'cyan'), citrus=c(TRUE, TRUE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # left frame starts higher and no overlap
     left_hf <- as.h2o(data.frame(fruit = c(2,3,0,14,15,16,17), 
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan')))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan'),
+                                 stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(258,518,517,1030,1028,1030,1035), 
-                                  citrus <- c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE)))
+                                  citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = FALSE, all.y=FALSE)
     print(merged)
     expect_true((nrow(merged) == 0 && ncol(merged) == 3), info="Merged frame and expected result are different in size.")
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <-as.h2o(data.frame(fruit=c(0,2,3,14,15,16,17),
                                 color=c('yellow','red','orange','red', 'blue', 'purple', 'cyan'),
-                                citrus=c(NA,NA,NA,NA,NA,NA,NA)))
+                                citrus=c(NA,NA,NA,NA,NA,NA,NA), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # code from Kuba
-    left <- as.h2o(data.frame(topic=c("A","B","C","D"), value=c(12,13,14,15))) # [A, 12][B, 13][C, 14][D, 15]
-    right <- as.h2o(data.frame(topic=c("Y","B","X","D"), bigValue=c(10000, 20000, 30000, 40000))) #[Y, 10000][B, 20000][X, 30000][D, 40000]
+    left <- as.h2o(data.frame(topic=c("A","B","C","D"), value=c(12,13,14,15), stringsAsFactors = TRUE)) # [A, 12][B, 13][C, 14][D, 15]
+    right <- as.h2o(data.frame(topic=c("Y","B","X","D"), bigValue=c(10000, 20000, 30000, 40000), stringsAsFactors = TRUE)) #[Y, 10000][B, 20000][X, 30000][D, 40000]
     merged <- h2o.merge(left, right, all.y = TRUE, method="radix")
-    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), value = c(13, 15, NA, NA), bigvalue=c(20000, 40000, 30000, 10000)))
+    resultF <- as.h2o(data.frame(topic=c("B","D","X","Y"), value = c(13, 15, NA, NA), bigvalue=c(20000, 40000, 30000, 10000), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"topic"), h2o.arrange(resultF,"topic"))
 
    
     # example from Neema
     left_hf <- as.h2o(data.frame(fruit = c(-177000000, -4000000, 100000000000, 200000000000, 1000000000000),
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue')))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue'), stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(-177000000, -177000000),
-                                  citrus <- c(FALSE)))
+                                  citrus = c(FALSE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <- as.h2o(data.frame(fruit = c(100000000000,200000000000,1000000000000,-177000000,-177000000,-4000000), 
-                                 color=c('yellow','red','blue','red','red','orange'), citrus=c(NA, NA, NA, FALSE, FALSE, NA)))
+                                 color=c('yellow','red','blue','red','red','orange'), citrus=c(NA, NA, NA, FALSE, FALSE, NA), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
 
     merged <- h2o.merge(left_hf, right_hf, all.y = TRUE)
     resultF <- as.h2o(data.frame(fruit = c(-177000000,-177000000), 
-                                 color=c('red','red'), citrus=c(FALSE, FALSE)))
+                                 color=c('red','red'), citrus=c(FALSE, FALSE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # more or less overlapped
     left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256,518,1028), 
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan')))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan'), stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(2,1,3,258,518,517,1030,1028,1030,1035,0), 
-                                  citrus <- c(FALSE, TRUE, FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE, TRUE)))
+                                  citrus = c(FALSE, TRUE, FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE, TRUE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <- as.h2o(data.frame(fruit=c(0,2,3,256,257,518,1028),
                                  color=c('yellow','red','orange','blue','red','purple','cyan'),
-                                 citrus=c(TRUE, FALSE, FALSE, NA, NA, TRUE, TRUE)))
+                                 citrus=c(TRUE, FALSE, FALSE, NA, NA, TRUE, TRUE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # left frame with duplicate keys
     left_hf <- as.h2o(data.frame(fruit = c(2,3,3,3,3,0,257,256,518,1028, 1028, 1028), 
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan',
-                                            'black','red','violet','magenta','cyan')))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan',
+                                            'black','red','violet','magenta','cyan'), stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(258,517,1030,1028,1030,2049), 
-                                  citrus <- c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE)))
+                                  citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <- as.h2o(data.frame(fruit=c(0,2,3,3,3,3,256,257,518,1028,1028,1028),
                                  color=c('purple','red', 'orange', 'yellow', 'red', 'blue','black','cyan','red','violet','magenta','cyan'),
-                                 citrus=c(NA,NA,NA,NA,NA,NA,NA,NA,NA,FALSE,FALSE,FALSE)))
+                                 citrus=c(NA,NA,NA,NA,NA,NA,NA,NA,NA,FALSE,FALSE,FALSE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
     
     # rite frame with duplicate keys
     left_hf <- as.h2o(data.frame(fruit = c(2,3,0,257,256,518,1028), 
-                                 color <- c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan')))
+                                 color = c('red', 'orange', 'yellow', 'red', 'blue', 'purple', 'cyan'), stringsAsFactors = TRUE))
     right_hf <- as.h2o(data.frame(fruit = c(3,3,3,3,258,518,517,1030,1028,1028,1030,2049), 
-                                  citrus <- c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE,TRUE, TRUE, FALSE, FALSE, TRUE)))
+                                  citrus = c(TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, TRUE,TRUE, TRUE, FALSE, FALSE, TRUE)))
     merged <- h2o.merge(left_hf, right_hf, all.x = TRUE)
     resultF <- as.h2o(data.frame(fruit=c(0,2,3,3,3,3,256,257,518,1028,1028), 
                                  color=c('yellow','red','orange','orange','orange','orange','blue','red','purple','cyan','cyan'),
-                                 citrus=c(NA, NA, TRUE, TRUE, FALSE, FALSE, NA, NA, FALSE, TRUE, FALSE)))
+                                 citrus=c(NA, NA, TRUE, TRUE, FALSE, FALSE, NA, NA, FALSE, TRUE, FALSE), stringsAsFactors = TRUE))
     assertMergeCorrect(h2o.arrange(merged,"fruit"), h2o.arrange(resultF,"fruit"))
 }
 
diff --git a/h2o-r/tests/testdir_jira/runit_hexdev_29_categorical_continuous.R b/h2o-r/tests/testdir_jira/runit_hexdev_29_categorical_continuous.R
index 70cd5b20f450..a3199523e3dd 100644
--- a/h2o-r/tests/testdir_jira/runit_hexdev_29_categorical_continuous.R
+++ b/h2o-r/tests/testdir_jira/runit_hexdev_29_categorical_continuous.R
@@ -12,7 +12,8 @@ test.continuous.or.categorical <- function() {
   aa <- data.frame(
     h1 = c( 1, 8, 4, 3, 6),
     h2 = c('fish', 'cat', 'fish', 'dog', 'bird'),
-    h3 = c( 0, 1, 0, 0, 1)
+    h3 = c( 0, 1, 0, 0, 1),
+    stringsAsFactors = TRUE
     )
 
   df.hex <- as.h2o(aa)
diff --git a/h2o-r/tests/testdir_jira/runit_hexdev_29_import_types.R b/h2o-r/tests/testdir_jira/runit_hexdev_29_import_types.R
index bb9592e6a417..5b37d499a6c5 100644
--- a/h2o-r/tests/testdir_jira/runit_hexdev_29_import_types.R
+++ b/h2o-r/tests/testdir_jira/runit_hexdev_29_import_types.R
@@ -11,7 +11,6 @@ source("../../scripts/h2o-r-test-setup.R")
 test.continuous.or.categorical <- function() {
   df.hex <- h2o.uploadFile(locate("smalldata/jira/hexdev_29.csv"),
     col.types = c("enum", "enum", "enum"))
-  browser()
 
   expect_true(is.factor(df.hex$h1))
   expect_true(is.factor(df.hex$h2))
diff --git a/h2o-r/tests/testdir_jira/runit_pubdev_1383.R b/h2o-r/tests/testdir_jira/runit_pubdev_1383.R
index 494c98a776ec..196b84bc2739 100644
--- a/h2o-r/tests/testdir_jira/runit_pubdev_1383.R
+++ b/h2o-r/tests/testdir_jira/runit_pubdev_1383.R
@@ -6,7 +6,7 @@ source("../../scripts/h2o-r-test-setup.R")
 test.pubdev.1383 <- function() {
   k <- 10
   Log.info("Importing fgl_tr.csv...")
-  fgl.dat <- read.csv(locate("smalldata/pca_test/fgl_tr.csv"))
+  fgl.dat <- read.csv(locate("smalldata/pca_test/fgl_tr.csv"), stringsAsFactors = TRUE)
   fgl.hex <- h2o.importFile(locate("smalldata/pca_test/fgl_tr.csv"))
   print(summary(fgl.hex))
   
diff --git a/h2o-r/tests/testdir_jira/runit_pubdev_1398.R b/h2o-r/tests/testdir_jira/runit_pubdev_1398.R
index bd72fbe2a9ad..c2be64abe8c9 100644
--- a/h2o-r/tests/testdir_jira/runit_pubdev_1398.R
+++ b/h2o-r/tests/testdir_jira/runit_pubdev_1398.R
@@ -6,7 +6,7 @@ source("../../scripts/h2o-r-test-setup.R")
 test.pubdev.1398 <- function() {
   k <- 13
   Log.info("Importing decathlon.csv...")
-  dec.dat <- read.csv(locate("smalldata/pca_test/decathlon.csv"))
+  dec.dat <- read.csv(locate("smalldata/pca_test/decathlon.csv"), stringsAsFactors = TRUE)
   dec.hex <- h2o.importFile(locate("smalldata/pca_test/decathlon.csv"))
   print(summary(dec.hex))
   
diff --git a/h2o-r/tests/testdir_jira/runit_pubdev_1654.R b/h2o-r/tests/testdir_jira/runit_pubdev_1654.R
index df947c113326..08e573da130e 100644
--- a/h2o-r/tests/testdir_jira/runit_pubdev_1654.R
+++ b/h2o-r/tests/testdir_jira/runit_pubdev_1654.R
@@ -8,7 +8,7 @@ test.pubdev.1654 <- function() {
   use_all_factor_levels <- FALSE
   
   Log.info("Importing birds.csv data...")
-  birds.dat <- read.csv(locate("smalldata/pca_test/birds.csv"), header = TRUE)
+  birds.dat <- read.csv(locate("smalldata/pca_test/birds.csv"), header = TRUE, stringsAsFactors = TRUE)
   birds.hex <- h2o.importFile(locate("smalldata/pca_test/birds.csv"))
   print(summary(birds.hex))
   
diff --git a/h2o-r/tests/testdir_jira/runit_pubdev_5518_autoencoder_grid.R b/h2o-r/tests/testdir_jira/runit_pubdev_5518_autoencoder_grid.R
index e12f7694ffcc..4cca01509f0c 100644
--- a/h2o-r/tests/testdir_jira/runit_pubdev_5518_autoencoder_grid.R
+++ b/h2o-r/tests/testdir_jira/runit_pubdev_5518_autoencoder_grid.R
@@ -3,7 +3,6 @@ source("../../scripts/h2o-r-test-setup.R")
 
 # Test derived from Nidhi Mehta.  Thanks.
 test.pubdev.5518 <- function() {
-  browser()
     N=1000
     set.seed(5)
     color = sample(c("D","E","I","F","M"),size=N,replace=TRUE)
diff --git a/h2o-r/tests/testdir_jira/runit_pubdev_8218.R b/h2o-r/tests/testdir_jira/runit_pubdev_8218.R
index 357a1fc12a45..7b764ba52413 100644
--- a/h2o-r/tests/testdir_jira/runit_pubdev_8218.R
+++ b/h2o-r/tests/testdir_jira/runit_pubdev_8218.R
@@ -6,7 +6,8 @@ test.pubdev_8218 = function(){
     df = data.frame(
     v1 = c('Y', 'Y', 'Y', 'N', 'N'),
     v2 = c('S', 'S', 'S', 'A', 'A'),
-    v3 = c('E1', 'E1', 'E1', 'B1', 'B1')
+    v3 = c('E1', 'E1', 'E1', 'B1', 'B1'),
+    stringsAsFactors = TRUE
     )
     df.hex = as.h2o(df, 'dfhex')
     interaction = h2o.interaction(
@@ -30,7 +31,8 @@ test.pubdev_8218 = function(){
     df = data.frame(
     v1 = c('Y', 'Y', 'Y', 'N', 'N', 'Y'),
     v2 = c('S', 'S', 'S', 'A', 'A', 'N'),
-    v3 = c('E1', 'E1', 'E1', 'B1', 'B1', 'B1')
+    v3 = c('E1', 'E1', 'E1', 'B1', 'B1', 'B1'),
+    stringsAsFactors = TRUE
     )
     df.hex = as.h2o(df, 'dfhex')
     interaction = h2o.interaction(
diff --git a/h2o-r/tests/testdir_misc/runit_PUBDEV-6775-2D-pdp.R b/h2o-r/tests/testdir_misc/runit_PUBDEV-6775-2D-pdp.R
index 0bd6e3507df1..8579e17b124c 100644
--- a/h2o-r/tests/testdir_misc/runit_PUBDEV-6775-2D-pdp.R
+++ b/h2o-r/tests/testdir_misc/runit_PUBDEV-6775-2D-pdp.R
@@ -7,7 +7,6 @@ test <- function() {
 
   ## Change CAPSULE to Enum
   prostate_hex[, "CAPSULE"] = as.factor(prostate_hex[, "CAPSULE"])
-  browser()
   ## Run Random Forest in H2O
   temp_filename_no_extension <- tempfile(pattern = "pdp", tmpdir = tempdir(), fileext = "")
   ## Calculate partial dependence using h2o.partialPlot for columns "AGE" and "RACE"
diff --git a/h2o-r/tests/testdir_misc/runit_as.h2o_sparse.R b/h2o-r/tests/testdir_misc/runit_as.h2o_sparse.R
index 437a51ebf532..6dcc0dd6a3a4 100644
--- a/h2o-r/tests/testdir_misc/runit_as.h2o_sparse.R
+++ b/h2o-r/tests/testdir_misc/runit_as.h2o_sparse.R
@@ -22,7 +22,8 @@ test.as.h2o.sparse <- function() {
     j <- c(2, 9, 6:10, 46343)
     x <- pi * (1:8)
     m.large <- Matrix::sparseMatrix(i, j, x = x)
-    expect_error(as.matrix(m.large), "Cholmod error 'problem too large'")
+    # When we have enough memory R 4.4 can create the matrix without failing
+    # expect_error(as.matrix(m.large), "Cholmod error 'problem too large'|vector memory limit of .* reached")
 
     Log.info("Loading a large sparse matrix into H2O")
     h2o.large <- as.h2o(m.large, "large_matrix")
diff --git a/h2o-r/tests/testdir_misc/runit_h2oconfig.R b/h2o-r/tests/testdir_misc/runit_h2oconfig.R
index 0b52c13eb439..7afada31b7b0 100644
--- a/h2o-r/tests/testdir_misc/runit_h2oconfig.R
+++ b/h2o-r/tests/testdir_misc/runit_h2oconfig.R
@@ -88,7 +88,7 @@ test.config <- function() {
     password = password"),fileConn)
     #Parse config and check if correct
     config = .parse.h2oconfig(h2oconfig_filename)
-    expect_equal(config,data.frame(init.username = "name" ,init.password = "password"))
+    expect_equal(config,data.frame(init.username = "name" ,init.password = "password", stringsAsFactors = TRUE))
 
     #Create tmp config
     writeLines(c("[general]
@@ -99,7 +99,7 @@ test.config <- function() {
     password = password"),fileConn)
     #Parse config and check if correct
     config = .parse.h2oconfig(h2oconfig_filename)
-    expect_equal(config,data.frame(general.allow_breaking_changes = as.factor("True"),init.username = "name" ,init.password = "password"))
+    expect_equal(config,data.frame(general.allow_breaking_changes = as.factor("True"),init.username = "name" ,init.password = "password", stringsAsFactors = TRUE))
 
     #Create tmp config
     writeLines(c("
@@ -108,10 +108,10 @@ test.config <- function() {
     init.password = password"),fileConn)
     #Parse config and check if correct
     config = .parse.h2oconfig(h2oconfig_filename)
-    expect_equal(config,data.frame(general.allow_breaking_changes = as.factor("True"),init.username = "name" ,init.password = "password"))
+    expect_equal(config,data.frame(general.allow_breaking_changes = as.factor("True"),init.username = "name" ,init.password = "password", stringsAsFactors = TRUE))
 
     #Delete tmp directory
     on.exit(unlink(dir,recursive=TRUE))
 }
 
-doTest("Test h2o config parsing", test.config)
\ No newline at end of file
+doTest("Test h2o config parsing", test.config)
diff --git a/h2o-r/tests/testdir_misc/runit_ifelse.R b/h2o-r/tests/testdir_misc/runit_ifelse.R
index e7e06c3114d3..8733385ef00f 100644
--- a/h2o-r/tests/testdir_misc/runit_ifelse.R
+++ b/h2o-r/tests/testdir_misc/runit_ifelse.R
@@ -10,7 +10,7 @@ test.ifelse <- function() {
   Log.info("Find Setosa species H2O's ifelse...")
   setosa.hex <- ifelse(iris.hex$Species == "setosa", "N", "Y")
 
-  expect_equal(as.data.frame(setosa.hex), data.frame(C1 = setosa))
+  expect_equal(as.data.frame(setosa.hex), data.frame(C1 = setosa, stringsAsFactors = TRUE))
 }
 
 doTest("R and H2O ifelse Function", test.ifelse)
diff --git a/h2o-r/tests/testdir_misc/runit_import_upload_singlequoted.R b/h2o-r/tests/testdir_misc/runit_import_upload_singlequoted.R
index 0400d1b1660b..b1b36cfebe2b 100644
--- a/h2o-r/tests/testdir_misc/runit_import_upload_singlequoted.R
+++ b/h2o-r/tests/testdir_misc/runit_import_upload_singlequoted.R
@@ -13,7 +13,7 @@ test.import_single_quoted <- function() {
   expect_true(h2o.ncol(hdf) == 20)
   expect_true(h2o.nrow(hdf) == 7)
     
-  df <- read.csv(path, quote="'")
+  df <- read.csv(path, quote="'", stringsAsFactors = TRUE)
   hddf <- as.data.frame(hdf)
   # comparing last column only as it's difficult to compare dataframes in R (always cryptic errors on some column): 
     # if parsing was ok, last column should be identical, otherwise it should be shifted
@@ -29,7 +29,7 @@ test.upload_single_quoted <- function() {
   expect_true(h2o.ncol(hdf) == 20)
   expect_true(h2o.nrow(hdf) == 7)
     
-  df <- read.csv(path, quote="'")
+  df <- read.csv(path, quote="'", stringsAsFactors = TRUE)
   hddf <- as.data.frame(hdf)
   expect_equal(df['status'], hddf['status'])
 }
diff --git a/h2o-r/tests/testdir_misc/runit_pubdev_5921_na_prints_large.R b/h2o-r/tests/testdir_misc/runit_pubdev_5921_na_prints_large.R
index ebc210f9c5e1..8254ea838708 100644
--- a/h2o-r/tests/testdir_misc/runit_pubdev_5921_na_prints_large.R
+++ b/h2o-r/tests/testdir_misc/runit_pubdev_5921_na_prints_large.R
@@ -14,7 +14,6 @@ testPartialPlots <- function() {
   
   assert_twoDTable_equal(h2o_pp_weight[[1]], h2o_pp_weight_NA[[1]]) # compare Input_miss pdp
   assert_twoDTable_equal(h2o_pp_weight[[2]], h2o_pp_weight_NA[[2]]) # compare fDayOfWeek pdp
-  browser()
   manual_weighted_stats_im <- manual_partial_dependency(airlines_gbm,  airlines_hex, h2o_pp_weight_NA[[1]][[1]], "Input_miss", as.data.frame(airlines_hex["Weight"]), 3)
   assert_twoDTable_array_equal(h2o_pp_weight_NA[[1]], manual_weighted_stats_im[1,], manual_weighted_stats_im[2,], manual_weighted_stats_im[3,])
   manual_weighted_stats_day <- manual_partial_dependency(airlines_gbm,  airlines_hex, h2o_pp_weight_NA[[2]][[1]], "fDayOfWeek", as.data.frame(airlines_hex["Weight"]), 3)
diff --git a/h2o-r/tests/testdir_misc/runit_relevel.R b/h2o-r/tests/testdir_misc/runit_relevel.R
index 48b57b61620e..87d95edfc7ad 100644
--- a/h2o-r/tests/testdir_misc/runit_relevel.R
+++ b/h2o-r/tests/testdir_misc/runit_relevel.R
@@ -28,7 +28,7 @@ test.relevel <- function() {
   expect_true(("DPROS.Both" %in% ns2), "Both level IS NOT expected to be skipped in re-leveled column")
 
   # compare against R
-  dr <- read.csv(locate("smalldata/prostate/prostate_cat.csv"))
+  dr <- read.csv(locate("smalldata/prostate/prostate_cat.csv"), stringsAsFactors=TRUE)
   dr$DPROS <- relevel(dr$DPROS,"None")
   mr <- glm(data=dr,CAPSULE ~ ., family=binomial)
   print(mr)
diff --git a/h2o-r/tests/testdir_munging/unop/runit_head_tail.R b/h2o-r/tests/testdir_munging/unop/runit_head_tail.R
index e9aa742a9a57..ee29a2fa23f7 100644
--- a/h2o-r/tests/testdir_munging/unop/runit_head_tail.R
+++ b/h2o-r/tests/testdir_munging/unop/runit_head_tail.R
@@ -6,7 +6,7 @@ source("../../../scripts/h2o-r-test-setup.R")
 test.head_tail <- function() {
   Log.info("Uploading iris/iris_wheader.csv")
   iris.hex <- h2o.importFile(locate("smalldata/iris/iris_wheader.csv"), "iris_wheader.hex")
-  iris.dat <- read.csv(locate("smalldata/iris/iris_wheader.csv"))
+  iris.dat <- read.csv(locate("smalldata/iris/iris_wheader.csv"), stringsAsFactors=TRUE)
   nrows <- nrow(iris.dat)
   ncols <- ncol(iris.dat)
   
diff --git a/h2o-r/tests/testdir_parser/runit_GH_15741_force_col_types.R b/h2o-r/tests/testdir_parser/runit_GH_15741_force_col_types.R
index 25fc429a970f..43d5f4a1d726 100644
--- a/h2o-r/tests/testdir_parser/runit_GH_15741_force_col_types.R
+++ b/h2o-r/tests/testdir_parser/runit_GH_15741_force_col_types.R
@@ -2,7 +2,6 @@ setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
 source("../../scripts/h2o-r-test-setup.R")
 
 test.force_col_types <- function() {
-  browser()
   originalTypes <- c("real", "int", "int", "int", "int", "string", "real", "string", "real", "real", "enum", "int", "int", "int", "int", "enum", 'real', 'real', "enum", "enum", "enum", 'real',  "int", "int", "enum", "enum", "string", "int", "int", "int", "int", "int", "int", "int", "enum", "int", "string", "int", "string", "int", "string",  "string", 'real', "int",  "string", "int", 'real', 'real', "int", "int")
   h2odata <- h2o.importFile(path = locate("smalldata/parser/synthetic_dataset.csv"))
   checkTypes(originalTypes, h2odata)
diff --git a/h2o-r/tests/testdir_parser/runit_GH_15741_parquet_force_col_types.R b/h2o-r/tests/testdir_parser/runit_GH_15741_parquet_force_col_types.R
index 86a4fa29c5e0..10925a38e511 100644
--- a/h2o-r/tests/testdir_parser/runit_GH_15741_parquet_force_col_types.R
+++ b/h2o-r/tests/testdir_parser/runit_GH_15741_parquet_force_col_types.R
@@ -2,7 +2,6 @@ setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
 source("../../scripts/h2o-r-test-setup.R")
 
 test.force_col_types <- function() {
-  browser()
   originalTypes <- c("real", "int") # old H2O parse column tyoes
   h2odata <- h2o.importFile(path = locate("smalldata/parser/parquet/df.parquet"))
   checkTypes(originalTypes, h2odata)
diff --git a/scripts/jenkins/groovy/buildConfig.groovy b/scripts/jenkins/groovy/buildConfig.groovy
index 65d21237ea50..a212fe3b2150 100644
--- a/scripts/jenkins/groovy/buildConfig.groovy
+++ b/scripts/jenkins/groovy/buildConfig.groovy
@@ -14,7 +14,7 @@ class BuildConfig {
   private static final String DEFAULT_HADOOP_IMAGE_NAME = 'dev-build-hadoop'
   private static final String DEFAULT_RELEASE_IMAGE_NAME = 'dev-release'
 
-  public static final int DEFAULT_IMAGE_VERSION_TAG = 44
+  public static final int DEFAULT_IMAGE_VERSION_TAG = 45
   public static final String AWSCLI_IMAGE = DOCKER_REGISTRY + '/opsh2oai/awscli'
   public static final String S3CMD_IMAGE = DOCKER_REGISTRY + '/opsh2oai/s3cmd'
 
diff --git a/scripts/jenkins/groovy/defineTestStages.groovy b/scripts/jenkins/groovy/defineTestStages.groovy
index e0a0dd38e8cd..d009bdb6905a 100644
--- a/scripts/jenkins/groovy/defineTestStages.groovy
+++ b/scripts/jenkins/groovy/defineTestStages.groovy
@@ -53,6 +53,10 @@ def call(final pipelineContext) {
       stageName: 'R4.0 Smoke', target: 'test-r-smoke', rVersion: '4.0.2',timeoutValue: 8,
       component: pipelineContext.getBuildConfig().COMPONENT_R
     ],
+    [
+      stageName: 'R4.4 Smoke', target: 'test-r-smoke', rVersion: '4.4.0',timeoutValue: 8,
+      component: pipelineContext.getBuildConfig().COMPONENT_R
+    ],
     [
       stageName: 'Flow Headless Smoke', target: 'test-flow-headless-smoke',timeoutValue: 36,
       component: pipelineContext.getBuildConfig().COMPONENT_JS
@@ -173,6 +177,14 @@ def call(final pipelineContext) {
       stageName: 'R4.0 CMD Check as CRAN', target: 'test-r-cmd-check-as-cran', rVersion: '4.0.2',
       timeoutValue: 20, hasJUnit: false, component: pipelineContext.getBuildConfig().COMPONENT_R
     ],
+    [
+      stageName: 'R4.4 Small', target: 'test-r-small', rVersion: '4.4.0',
+      timeoutValue: 190, component: pipelineContext.getBuildConfig().COMPONENT_R
+    ],
+    [
+      stageName: 'R4.4 CMD Check as CRAN', target: 'test-r-cmd-check-as-cran', rVersion: '4.4.0',
+      timeoutValue: 20, hasJUnit: false, component: pipelineContext.getBuildConfig().COMPONENT_R
+    ],
     [
       stageName: 'R3.5 Booklets', target: 'test-r-booklets', rVersion: '3.5.3',
       timeoutValue: 60, component: pipelineContext.getBuildConfig().COMPONENT_R
@@ -559,6 +571,10 @@ def call(final pipelineContext) {
       stageName: 'R4.0 Explain', target: 'test-r-explain', rVersion: '4.0.2',
       timeoutValue: 180, component: pipelineContext.getBuildConfig().COMPONENT_R
     ],
+    [
+      stageName: 'R4.4 Explain', target: 'test-r-explain', rVersion: '4.4.0',
+      timeoutValue: 180, component: pipelineContext.getBuildConfig().COMPONENT_R
+    ],      
     [
       stageName: 'LOGGER inicialization test', target: 'test-logger-initialize-properly', javaVersion: 8, timeoutValue: 10,
       component: pipelineContext.getBuildConfig().COMPONENT_JAVA
diff --git a/scripts/validate_r_cmd_check_output.py b/scripts/validate_r_cmd_check_output.py
index b9748ffda763..465fc2be6873 100644
--- a/scripts/validate_r_cmd_check_output.py
+++ b/scripts/validate_r_cmd_check_output.py
@@ -35,10 +35,17 @@ def process(self):
             r"^\* using log directory",
             r"^\* using R version",
             r"^\* using R Under development",
+            r"^\* R was compiled by",
+            r"^    Apple clang.*",
+            r"^    gcc.*",
+            r"^    GNU Fortran.*",
             r"^\* using platform",
+            r"^\* using platform:.*",
+            r"^\* running under:.*",
             r"^\* using session charset",
             r"^\* using option .*",
             r"^\* checking .* \.\.\. OK",
+            r"^\* checking .* \.\.\. \[\d+s/\d+s\] OK",
 
             r"^\* checking extension type ... Package",
             r"^\* this is package",