Performance assertion checking
SOSP '93 Proceedings of the fourteenth ACM symposium on Operating systems principles
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OOPSLA '00 Addendum to the 2000 proceedings of the conference on Object-oriented programming, systems, languages, and applications (Addendum)
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SRDS '09 Proceedings of the 2009 28th IEEE International Symposium on Reliable Distributed Systems
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Precise regression benchmarking with random effects: improving mono benchmark results
EPEW'06 Proceedings of the Third European conference on Formal Methods and Stochastic Models for Performance Evaluation
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Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
Constructing performance model of JMS middleware platform
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Compared to functional unit testing, automated performance testing is difficult, partially because correctness criteria are more difficult to express for performance than for functionality. Where existing approaches rely on absolute bounds on the execution time, we aim to express assertions on code performance in relative, hardware-independent terms. To this end, we introduce Stochastic Performance Logic (SPL), which allows making statements about relative method performance. Since SPL interpretation is based on statistical tests applied to performance measurements, it allows (for a special class of formulas) calculating the minimum probability at which a particular SPL formula holds. We prove basic properties of the logic and present an algorithm for SAT-solver-guided evaluation of SPL formulas, which allows optimizing the number of performance measurements that need to be made. Finally, we propose integration of SPL formulas with Java code using higher-level performance annotations, for performance testing and documentation purposes.