166 citations · 172 across the 4 of their papers we have counts for
4 papers
Learning How to Mutate Source Code from Bug-Fixes
Michele Tufano, Cody Watson, Gabriele Bavota +3
Mutation testing has been widely accepted as an approach to guide test case generation or to assess the effectiveness of test suites. Empirical studies have shown that mutants are…
An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation
Michele Tufano, Cody Watson, Gabriele Bavota +3
Millions of open-source projects with numerous bug fixes are available in code repositories. This proliferation of software development histories can be leveraged to learn how to f…
Mining Android App Usages for Generating Actionable GUI-based Execution Scenarios
Mario Linares-Vasquez, Martin White, Carlos Bernal-Cardenas +2
GUI-based models extracted from Android app execution traces, events, or source code can be extremely useful for challenging tasks such as the generation of scenarios or test cases…
Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities
Martin White, Michele Tufano, Matias Martinez +2
In the field of automated program repair, the redundancy assumption claims large programs contain the seeds of their own repair. However, most redundancy-based program repair techn…