This is an artifact for the paper "Automatic and Scalable Detection of Logical Errors in Functional Programming Assignments" submitted to OOPSLA 2019. The artifact is licensed under the MIT license.


The file artifact.zip provides VM and documentation for reproducing the evaluation results in the paper. The VM contains source codes for implementating the algorithm, benchmarks used in evaluation, and a python script for reproducing the Table 1 and Table 2 in the paper. Specically, you can see that the main parts of our algorithm are implemented in the following files:

  • engine/TestML/testGenerator.ml: Our overall algirthm and symbolic test case generation
  • engine/TestML/sym_exec.ml: Symbolic verification