The paper can be found here
The training and testing dataset is a derivative of the js150 dataset. Duplicates and common entries between the training and testing set have been removed.
compare.jar is a slightly modified version of the JSNice jar distribution and is primarily used for evaluating performance i.e. accuracy of predicted names given the ground-truth. The primary change is the disabling of exclusion of files based on their size, and computation of some additional stats such as number of unique names recovered etc.
The following sections state the commands to be used for various scenarios.
python3 data_scripts/prepare_corpus.py --minify --force "eval_list.txt" # Minification
python3 data_scripts/prepare_corpus.py --minify --no-mangle --force "eval_list.txt" # Normaliation
python3 data_scripts/prepare_corpus.py --minify --force "training_list.txt" # Minification
python3 data_scripts/prepare_corpus.py --minify --no-mangle --force "training_list.txt" # Normaliation
node context2name/c2n_client.js -l -f "eval_list.txt" --outfile "eval.csv"
node context2name/c2n_client.js -l -f "training_list.txt" --outfile "training.csv"
python3 context2name/training.py
npm install esprima escodegen estraverse sync-request argparse js-priority-queue
python3 context2name/c2n_server.py &
node context2name/c2n_client.js -l -f "eval_list.txt" -r -s --ext "c2n.js"
First make sure that the output of JSNaughty is stored as *.jsnaughty.js and its timing results are stored as *.jsnaughty.timing.stats
java -jar compare.jar --eval_jsnice --jsnice_features=ASTREL,NODEFLAG,ARGALIAS,FNAMES --jsnice_infer=NAMES --use_inp_file_list eval_list.txt --save_recovered_files --use_normalized --print_stats > log_analysis.jsnice
java -jar compare.jar --eval_jsnice --jsnice_features=ASTREL,NODEFLAG,ARGALIAS,FNAMES --jsnice_infer=NAMES --use_inp_file_list eval_list.txt --eval_metrics_only --custom_ext "c2n" --use_normalized --print_stats > log_analysis.c2n
java -jar compare.jar --eval_jsnice --jsnice_features=ASTREL,NODEFLAG,ARGALIAS,FNAMES --jsnice_infer=NAMES --use_inp_file_list eval_list.txt --eval_metrics_only --custom_ext "jsnaughty" --use_normalized --print_stats > log_analysis.jsnaughty
python3 data_scripts/generate_csvs.py eval_list.txt
python3 data_scripts/analysis.py --accuracies --timing --filestats --venn --save_venn "venn_no_time_limit_weighted.png" --venn_weighted eval_list.txt
python3 data_scripts/analysis.py --accuracies --timing --filestats --venn --save_venn "venn_time_limit_weighted.png" --venn_weighted --tlimit 600000 eval_list.txt