Polymetric Views-A Lightweight Visual Approach to Reverse Engineering
IEEE Transactions on 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
Exploring large profiles with calling context ring charts
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
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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Continuous software change may inadvertently introduce a drop in performance at runtime. The longer the performance loss remains undiscovered, the harder it is to address. Current profilers do not efficiently support performance comparison across multiple software versions. As a consequence, identifying the cause of a slow execution caused by a software change is often carried out in an ad-hoc fashion. 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 understanding precisely how a performance aspect evolves along with the version history of the software. We present the key ingredients to make multidimensional profiling effective, and sketch the design of Rizel, an implementation in the Pharo programming language.