diff --git a/TestON/JenkinsFile/SCPF/SCPFbatchFlowResp.R b/TestON/JenkinsFile/SCPF/SCPFbatchFlowResp.R
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+# Copyright 2017 Open Networking Foundation (ONF)
+#
+# Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
+# the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
+# or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
+#
+#     TestON is free software: you can redistribute it and/or modify
+#     it under the terms of the GNU General Public License as published by
+#     the Free Software Foundation, either version 2 of the License, or
+#     (at your option) any later version.
+#
+#     TestON is distributed in the hope that it will be useful,
+#     but WITHOUT ANY WARRANTY; without even the implied warranty of
+#     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#     GNU General Public License for more details.
+#
+#     You should have received a copy of the GNU General Public License
+#     along with TestON.  If not, see <http://www.gnu.org/licenses/>.
+#
+# If you have any questions, or if you don't understand R,
+# please contact Jeremy Ronquillo: jeremyr@opennetworking.org
+
+# **********************************************************
+# STEP 1: File management.
+# **********************************************************
+
+print( "STEP 1: File management." )
+
+# Command line arguments are read. Args usually include the database filename and the output
+# directory for the graphs to save to.
+# ie: Rscript SCPFgraphGenerator SCPFsampleDataDB.csv ~/tmp/
+print( "Reading commmand-line args." )
+args <- commandArgs( trailingOnly=TRUE )
+
+# Import libraries to be used for graphing and organizing data, respectively.
+# Find out more about ggplot2: https://github.com/tidyverse/ggplot2
+#                     reshape2: https://github.com/hadley/reshape
+print( "Importing libraries." )
+library( ggplot2 )
+library( reshape2 )
+library( RPostgreSQL )    # For databases
+
+# Check if sufficient args are provided.
+if ( is.na( args[ 7 ] ) ){
+    print( "Usage: Rscript SCPFbatchFlowResp <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+    q()  # basically exit(), but in R
+}
+
+# Filenames for output graphs include the testname and the graph type.
+# See the examples below. paste() is used to concatenate strings.
+
+errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
+errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" )
+errBarOutputFile <- paste( errBarOutputFile, "_PostGraph.jpg", sep="" )
+
+print( "Reading from databases." )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
+
+command <- paste( "SELECT * FROM batch_flow_tests WHERE branch='", args[ 6 ], sep="" )
+command <- paste( command, "' ORDER BY date DESC LIMIT 3", sep="" )
+
+print( paste( "Sending SQL command:", command ) )
+
+fileData <- dbGetQuery( con, command )
+
+chartTitle <- paste( "Single Bench Flow Latency - Post", "Last 3 Builds", sep = "\n" )
+
+# **********************************************************
+# STEP 2: Organize data.
+# **********************************************************
+
+avgs <- c()
+
+print( "Sorting data." )
+avgs <- c( fileData[ 'posttoconfrm' ], fileData[ 'elapsepost' ] )
+
+dataFrame <- melt( avgs )
+dataFrame$scale <- fileData$scale
+dataFrame$date <- fileData$date
+dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+
+colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
+
+# Format data frame so that the data is in the same order as it appeared in the file.
+dataFrame$type <- as.character( dataFrame$type )
+dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
+
+# **********************************************************
+# STEP 3: Generate graphs.
+# **********************************************************
+
+print( "Generating fundamental graph data." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
+xLabel <- xlab( "date" )
+yLabel <- ylab( "Latency (ms)" )
+fillLabel <- labs( fill="Type" )
+theme <- theme( plot.title=element_text( hjust = 0.5, size = 18, face='bold' ) )
+
+fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+
+
+print( "Generating bar graph with error bars." )
+width <- 0.3
+barGraphFormat <- geom_bar( stat="identity", width = width )
+title <- ggtitle( chartTitle )
+result <- fundamentalGraphData + barGraphFormat + title
+
+
+print( paste( "Saving bar chart to", errBarOutputFile ) )
+ggsave( errBarOutputFile, width = 10, height = 6, dpi = 200 )
+
+print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )
+
+
+# **********************************************************
+# STEP 2: Organize data.
+# **********************************************************
+
+avgs <- c()
+
+print( "Sorting data." )
+avgs <- c( fileData[ 'deltoconfrm' ], fileData[ 'elapsedel' ] )
+
+dataFrame <- melt( avgs )
+dataFrame$scale <- fileData$scale
+dataFrame$date <- fileData$date
+dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+
+colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
+
+# Format data frame so that the data is in the same order as it appeared in the file.
+dataFrame$type <- as.character( dataFrame$type )
+dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
+
+
+# **********************************************************
+# STEP 3: Generate graphs.
+# **********************************************************
+
+print( "Generating fundamental graph data." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
+xLabel <- xlab( "Build Date" )
+yLabel <- ylab( "Latency (ms)" )
+fillLabel <- labs( fill="Type" )
+theme <- theme( plot.title=element_text( hjust = 0.5, size = 18, face='bold' ) )
+
+fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+
+
+print( "Generating bar graph with error bars." )
+width <- 0.3
+barGraphFormat <- geom_bar( stat="identity", width = width )
+chartTitle <- paste( "Single Bench Flow Latency - Del", "Last 3 Builds", sep = "\n" )
+title <- ggtitle( chartTitle )
+result <- fundamentalGraphData + barGraphFormat + title
+
+errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
+errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" )
+errBarOutputFile <- paste( errBarOutputFile, "_DelGraph.jpg", sep="" )
+
+print( paste( "Saving bar chart to", errBarOutputFile ) )
+ggsave( errBarOutputFile, width = 10, height = 6, dpi = 200 )
+
+print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )
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