4 citations · 10 across the 4 of their papers we have counts for
5 papers · 1 filter
Mind the Gap: The Difference Between Coverage and Mutation Score Can Guide Testing Efforts
Kush Jain, Goutamkumar Tulajappa Kalburgi, Claire Le Goues +1
An "adequate" test suite should effectively find all inconsistencies between a system's requirements/specifications and its implementation. Practitioners frequently use code covera…
Contextual Predictive Mutation Testing
Kush Jain, Uri Alon, Alex Groce +1
Mutation testing is a powerful technique for assessing and improving test suite quality that artificially introduces bugs and checks whether the test suites catch them. However, it…
Data Poisoning: Lightweight Soft Fault Injection for Python
Mohammad Amin Alipour, Alex Groce
This paper introduces and explores the idea of data poisoning, a light-weight peer-architecture technique to inject faults into Python programs. This method requires very small mod…
Bounded Model Checking and Feature Omission Diversity
Mohammad Amin Alipour, Alex Groce
In this paper we introduce a novel way to speed up the discovery of counterexamples in bounded model checking, based on parallel runs over versions of a system in which features ha…
Finding Model-Checkable Needles in Large Source Code Haystacks: Modular Bug-Finding via Static Analysis and Dynamic Invariant Discovery
Mohammad Amin Alipour, Alex Groce, Chaoqiang Zhang +2
In this paper, we present a novel marriage of static and dynamic analysis. Given a large code base with many functions and a mature test suite, we propose using static analysis to…