Certified Abstract Cost Analysis

Author:

Albert ElviraORCID,Hähnle ReinerORCID,Merayo Alicia,Steinhöfel DominicORCID

Abstract

AbstractA program containing placeholders for unspecified statements or expressions is called an abstract (or schematic) program. Placeholder symbols occur naturally in program transformation rules, as used in refactoring, compilation, optimization, or parallelization. We present a generalization of automated cost analysis that can handle abstract programs and, hence, can analyze the impact on the cost of program transformations. This kind of relational property requires provably precise cost bounds which are not always produced by cost analysis. Therefore, we certify by deductive verification that the inferred abstract cost bounds are correct and sufficiently precise. It is the first approach solving this problem. Both, abstract cost analysis and certification, are based on quantitative abstract execution (QAE) which in turn is a variation of abstract execution, a recently developed symbolic execution technique for abstract programs. To realize QAE the new concept of a cost invariant is introduced. QAE is implemented and runs fully automatically on a benchmark set consisting of representative optimization rules.

Publisher

Springer International Publishing

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automatic loop invariant generation for data dependence analysis;Proceedings of the IEEE/ACM 10th International Conference on Formal Methods in Software Engineering;2022-05-18

2. Symbolic Execution: Foundations, Techniques, Applications, and Future Perspectives;The Logic of Software. A Tasting Menu of Formal Methods;2022

3. When COSTA Met KeY: Verified Cost Bounds;The Logic of Software. A Tasting Menu of Formal Methods;2022

4. Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules;Ernst Denert Award for Software Engineering 2020;2022

5. Delta-based verification of software product families;Proceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences;2021-10-17

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