Semantic Diff: A Tool for Summarizing the Effects of Modifications
ICSM '94 Proceedings of the International Conference on Software Maintenance
A Differencing Algorithm for Object-Oriented Programs
Proceedings of the 19th IEEE international conference on Automated software engineering
Perfdiff: a framework for performance difference analysis in a virtual machine environment
Proceedings of the 6th annual IEEE/ACM international symposium on Code generation and optimization
Tracking performance across software revisions
PPPJ '09 Proceedings of the 7th International Conference on Principles and Practice of Programming in Java
Proceedings of the 5th international symposium on Software visualization
Counting messages as a proxy for average execution time in pharo
Proceedings of the 25th European conference on Object-oriented programming
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An application execution profile has meaning only when it is compared to another profile obtained from a slightly different executing context. Unfortunately, current profilers do not efficiently support performance comparison across multiple profiles. As a consequence, profiling multiple executions is often realized in an ad-hoc fashion, often resulting in missing opportunities for caching. We propose multidimensional profiling as a way to repeatedly profile a software execution by varying some variables of the execution context. Having explicit execution variation points is key to precisely understanding how a particular feature performance evolves along the version history of the software.