Sieve: A Tool for Automatically Detecting Variations Across Program Versions

Software systems often undergo many revisions during their lifetime as new features are added, bugs repaired, abstractions simplified and refactored, and performance improved. When a revision, even a minor one, does occur, the changes it induces must be tested to ensure that invariants assumed in the original version are not violated unintentionally. In order to avoid testing components that are unchanged across revisions, impact analysis is often used to identify code blocks or functions that are affected by a change. In this paper, we present a novel solution to this general problem that uses dynamic programming on instrumented traces of different program binaries to identify longest common subsequences in strings generated by these traces. Our formulation allows us to perform impact analysis and also to detect the smallest set of locations within the functions where the effect of the changes actually manifests itself. Sieve is a tool that incorporates these ideas. Sieve is unobtru...

• Type: Conference
• Year: 2006
• Where: KBSE
• Authors: Murali Krishna Ramanathan, Ananth Grama, Suresh Jagannathan
• Keywords: Impact Analysis, Instrumented Traces, KBSE 2006, Longest Common Subsequences, Software Engineering