Bachelor thesis - Characterizing Solution Spaces in JavaScript

The overall structure of the elements is as follows:

• injectData.js: This will clone the repositories of the groups and preparing the basic test setup, like one overall test folder or copying the needed files.
• /util folder: contains important information: the needed code for getting the coverage, information on where it needs to be inserted into the test cases.
  • codeLines.INI: this file contains information where the code needs to be pasted into the testcases.
  • getUsedJS.js: this is copied into the test structure and then used there.
  • jest.setup.js: this file is needed to get the name of the tests and is copied into the test structure as well.
• /GatheringJSCoverage folder: has the gathered solutions code and the script to obtain it.
  • /JSCoverage folder: contains the executed code for the groups.
  • /test folder: this is the test structure folder.
  • /www folder: this folder contains the solution of the group which is tested at the moment.
  • gatherJSCoverage.js: This script copies each implementation folder of the groups into the www folder and then executes the test cases for this solution.
• /CodeAnalysis folder: contains everything for the code anaylsis.
  • /clustering folder: has the clustering results in it after running the scripts.
  • /clustering_repeats folder: has the clustering results in it, which are produced by the util.py script.
  • /data folder: contains the data for each TestCase for each Group in it.
  • /results folder: contains images of results of the vector spaces and clustering.
  • basicAnalysis.py: This script is for doing the basic anaylsis.
  • complexAnalysis.py: This script executes the complex analysis with Doc2Vec.
  • prepareDataForBasicAnalysis.js: as the name suggests, this prepares the data for the basic analysis. It counts the if, for, while, ..., lines of code, affected files and also the JSHint messages.
  • restructureCoverageFiles.py: restrucutes the gathered JavaScript code of the different groups divided per group and per testcase (which is needed for the analysis).
  • util.py: contains utility functions like obtaining the right number of clusters for given input.