PITMuS: A Tool for Automated Bug Dataset Generation via Source-Level Mutant Reconstruction
Tasfia Tasnim, Soneya Binta Hossain

TL;DR
PITMuS is a tool that generates structured, source-level bug datasets from mutation testing metadata, aiding training and evaluation of bug localization and repair methods.
Contribution
It introduces a method to reconstruct source-level buggy and fixed code pairs from PIT mutation testing metadata using debug information.
Findings
Successfully applied to eight open-source Java systems.
Produces structured datasets with bug and fix pairs, documentation, and metadata.
Facilitates training and evaluation of bug localization and repair techniques.
Abstract
LLM-based software engineering increasingly depends on executable, context-rich bug artifacts: paired correct and buggy code, methods under test (MUTs), documentation, and metadata. These artifacts support the training and evaluation of automated bug localization and repair techniques, testing and test oracle generation methods, and documentation-driven automation. Although curated benchmarks (e.g., Defects4J) remain valuable, they are static and increasingly vulnerable to contamination as code models are trained on large public corpora. A complementary strategy is to generate fresh, cutoff-aware datasets by selecting real system versions and injecting controlled bugs at the source level. Mutation testing is a natural basis for this strategy: it applies predefined mutation operators to programs and records whether the existing test suite detects each injected change. PIT is a…
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