Our new paper, “Predictive Mutation Analysis via Natural Language Channel in Source Code” has been accepted for publication to TOSEM and a preprint is now available at ArXiv. This work has been done by Jinhan Kim (KAIST), Juyoung Jeon (Handong Global Univ.), Shin Hong (Handong Global Univ.), and Shin Yoo (KAIST).
We propose a new technique named Seshat, a Predictive Mutation Analysis (PMA) technique that can accurately predict the entire kill matrix, not just the mutation score of the given test suite. Seshat exploits the natural language channel in code, and learns the relationship between the syntactic and semantic concepts of each test case and the mutants it can kill, from a given kill matrix.