Introduction

This repository contains the reproduction package of the large scale evaluation of search-based crash reproduction reported in the following paper: Soltani, M., Derakhshanfar, P., Devroey, X. and van Deursen, A. (2020). A benchmark-based evaluation of search-based crash reproduction. In Empirical Software Engineering. 25, 1 (Jan. 2020), pp. 96–138. (open access).

@article{Derakhshanfar2020,
  author    = {Soltani, Mozhan and Derakhshanfar, Pouria and Devroey, Xavier and van Deursen, Arie},
  title     = {A benchmark-based evaluation of search-based crash reproduction},
  journal   = {Empirical Software Engineering},
  volume    = {25},
  number    = {1},
  pages     = {96--138},
  year      = {2020},
  doi       = {10.1007/s10664-019-09762-1}
}

This reproduction package provides 3 parts: sample, evaluation, and results. Sample is an example which replicates the XWIKI-13031 stack trace using ExRunner. Evaluation may be used to replicate our full results, presented in the paper. Results presents complete results of the paper, including details of the statistical and manual analysis performed. We also detail the steps to add a new stack trace to CrashPack and include it in ExRunner, and how to extend ExRunner to another crash replication tool.

Running Sample

For sample, ExRunner applies EvoCrash 10 times on each frame of the XWIKI-13031 stack trace.

1. Run Init.py in Sample/pythonScripts directory:

python Sample/pythonScripts/Init.py <Number of Threads>

The default <Number of Threads> is 5.

During the execution of ExRunner, we can monitor the progress of EvoCrash on the case.

2. Collect the results:

Results of the execution (including final fitness value of each case) are saved in Sample/pythonScripts/outputs/csv/result.csv. In addition, if a test case has been generated (i.e., EvoCrash succeeded to reproduce the stack trace), it is saved in Sample/JarFiles/GGA-tests.

Reproducing the evaluation

For Evaluation, ExRunner applies EvoCrash 10 times on all of the stack traces selected for evaluation.

Attention: to reproduce evaluation in a reasonable amount of time, one need a powerful machine with a large amount of memory to be able to increase the <Number of Threads>. In our evaluation, we distributed the execution on several machines.

1. Run Init.py in Evaluation/pythonScripts directory:

  python Evaluation/pythonScripts/Init.py <Number of Threads>

2. Collect the results:

Results of the execution are saved in Evaluation/pythonScripts/outputs/csv/result.csv. In addition, the generated test cases (if any) are saved in Evaluation/JarFiles/GGA-tests.

Add a new stack trace

There are 3 steps to add a new stack trace to ExRunner: 1. adding stack trace, 2. adding dependencies, 3. adding the information of new issue in input.csv file.

1. Adding the stack trace

• Add a <PROJECT> directory (project name should be in upper case) to JarFiles/resources/logs/. For instance, JarFiles/resources/logs/XWIKI.

• Add a <issue-name> directory to JarFiles/resources/logs/<PROJECT>. For instance, JarFiles/resources/logs/XWIKI/XCOMMONS-928. The <issue-name> should denote the issue in the <PROJECT> from which the stack trace has been collected.

• Add a <issue-name>.log file to JarFiles/resources/logs/<PROJECT>/<issue-name>. For instance, JarFiles/resources/logs/XWIKI/XCOMMONS-928/XCOMMONS-928.log. File <issue-name>.log contains the stack trace without any other information. For instance:

java.lang.NullPointerException: null
    at org.xwiki.extension.repository.internal.installed.DefaultInstalledExtensionRepository.applyInstallExtension(DefaultInstalledExtensionRepository.java:449)
    at org.xwiki.extension.repository.internal.installed.DefaultInstalledExtensionRepository.installExtension(DefaultInstalledExtensionRepository.java:691)
    at org.xwiki.extension.job.internal.AbstractExtensionJob.installExtension(AbstractExtensionJob.java:257)
    at org.xwiki.extension.job.internal.AbstractExtensionJob.applyAction(AbstractExtensionJob.java:204)
    at org.xwiki.extension.job.internal.AbstractExtensionJob.applyActions(AbstractExtensionJob.java:151)
    at org.xwiki.extension.job.internal.InstallJob.runInternal(InstallJob.java:150)
    at org.xwiki.job.AbstractJob.runInContext(AbstractJob.java:205)
    at org.xwiki.job.AbstractJob.run(AbstractJob.java:188)
    at org.xwiki.platform.wiki.creationjob.internal.ExtensionInstaller.installExtension(ExtensionInstaller.java:73)
    at org.xwiki.platform.wiki.creationjob.internal.steps.ProvisionWikiStep.execute(ProvisionWikiStep.java:78)
    at org.xwiki.platform.wiki.creationjob.internal.WikiCreationJob.runInternal(WikiCreationJob.java:80)
    at org.xwiki.job.AbstractJob.runInContext(AbstractJob.java:205)
    at org.xwiki.job.AbstractJob.run(AbstractJob.java:188)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
    at java.lang.Thread.run(Unknown Source)

2. Adding dependencies

• Add a <PROJECT>-bins directory (project name should be in upper case) to JarFiles/resources/targetedSoftware/. For instance, JarFiles/resources/targetedSoftware/XWIKI-bins.

• Add a <PROJECT>-<Version> directory (project name should be in upper case) to JarFiles/resources/targetedSoftware/<PROJECT>-bins. For instance, JarFiles/resources/targetedSoftware/XWIKI-bins/XWIKI-7.2. <Version> is the version of the <PROJECT> the will be used by EvoCrash to replicate the stack trace.

• Put the Jar file of version <Version> of the <PROJECT> and all its dependencies in JarFiles/resources/targetedSoftware/<PROJECT>-bins/<PROJECT>-<Version>.

3. Adding new issue to input.csv

• Open data.py in input_generator directory.

• Add a project entry to projects array. Add a list of 3 indexes to the array:

  1. id: a unique number for the project.
  2. name: project name (<PROJECT>).
  3. package: name of the project in stack traces. Example:

  {"id":"0","name":"xwiki","package":"xwiki"}
  

• Add an issue entry to cases array. A list with 7 indexes:

  1. id: a unique number for issue.
  2. project: id of the project in projects array.
  3. name: the issue name which we used to create directory of stack trace (<issue-name>).
  4. version: the affected version of stack trace (<Version>).
  5. fixed (optional): 1 if it is a fixed issue, and 0 if the issue is still unresolved.
  6. fixed_version (optional): fixed version.
  7. buggy_frame (optional): frame which triggers the bug. Example:

  {"id": "7", "project": "0", "name": "XCOMMONS-928", "version": "7.4.2", "fixed": "1", "fixed_version": "7.4.3","buggy_frame": "5"}
  

• Run input_generator/init.py that will update input.csv in /pythonScripts/inputs.

Run other crash replication tools with ExRunner

To perform crash replication benchmarking with another tool, ExRunner has to be modified to match input and output formats of this tool.

1. Implement an adaptor for the new tool:

ExRunner uses an adaptor to handle execution of crash replication tool. This adaptor is a class with a main method that is called for each line in input.csv. For instance, the adaptor for EvoCrash is defined in JarFiles/src/Run.java.

2. Modify input CSV file:

Arguments for the crash replication tool are defined in /pythonScripts/inputs/input.csv. Each line of this CSV file is one stack trace with specific configurations. Indexes of the columns in input.csv that are passed to the adaptor are specified in useful_indexes array in pythonScripts/input.py. For instance, if the needed configurations are only in 2 first columns of input.csv, useful_indexes would be [0,1].

**Attention:** application, case, and round columns are mandatory for CSV file.

3. Customise csv_results array in RunJar.py:

There is a for loop at line 147 of pythonScripts/RunJar.py that checks each line of output and saves data to csv_results array. Depending on the output of the crash replication tool, this loop has to be modified accordingly.

4. Collect execution logs:

ExRunner writes results and output logs of the tool in pythonScripts/outputs/logs.

Reproduce analysis of the paper

Results folder contains different subfolders with the complete results of our evaluation. A Makefile is available in the Results/ to launch the R analysis (requires R to be installed and Rscripts command to be available). The different goals (to be launched from the Results/ folder) are:

• make analysebenchmark prints various statistics on the CrashPack benchmark;
• make analyseresults prints various statistics on the results of our evaluation;
• make plots prints the .pdf plots describing the benchmark and the evaluation results in plots/;
• make tables prints the .tex tables describing the benchmark and the evaluation results in tables/;
• make all all of the above goals;
• make clean deletes plots/ and tables/.

Other files in Results/ include:

• csv/ with csv files with data on the benchmark (in csv/benchmark/benchmark.csv) and the results of our 10 rounds of evaluation (in /csv/round[1-10]/results.csv);
• logs/ with the output logs of EvoCrash for each round of each case;
• manual-analysis/ the manual analysis performed on the unreproducible cases (see /manual-analysis/classification.csv for the classification of the cases);
• tests/ the tests generated by EvoCrash (if any) for the different cases.

Funding

This work is partially funded by research project STAMP (European Commission - H2020)