ABSTRACT
The functional correctness of safety- and security-critical software is of utmost importance. Nowadays, this can be achieved through computer assisted verification.
While formal verification itself typically poses a steep learning-curve for anyone who wants to apply it, its applicability is further hindered by its (typically) low runtime performance.
With the increasing popularity of algorithm parameter tuning and genetic improvement, we see a great opportunity for assisting verification engineers in their daily tasks.
- B. Beckert, R. Hähnle, and P. H. Schmitt, editors. Verification of Object-Oriented Software: The KeY Approach. Springer, 2007. Google ScholarDigital Library
- B. Beckert, T. Bormer, and M. Wagner. Heuristically creating test cases for program verification systems. In Metaheuristics International Conference (MIC), 2013.Google Scholar
- B. Bérard, M. Bidoit, A. Finkel, F. Laroussinie, A. Petit, L. Petrucci, and P. Schnoebelen. Systems and software verification: model-checking techniques and tools. Springer, 2010. Google ScholarDigital Library
- M. A. Bokhari, T. Bormer, and M. Wagner. 7th International Symposium on Search-Based Software Engineering (SSBSE), chapter An Improved Beam-Search for the Test Case Generation for Formal Verification Systems, pages 77--92. Springer, 2015.Google Scholar
- B. R. Bruce, J. Petke, and M. Harman. Reducing energy consumption using genetic improvement. In Genetic and Evolutionary Computation (GECCO), pages 1327--1334. ACM, 2015. Google ScholarDigital Library
- E. W. Dijkstra. Guarded commands, nondeterminacy and formal derivation of programs. Communications of the ACM, 18 (8): 453--457, 1975. Google ScholarDigital Library
- F. Hutter, D. Babic, H. H. Hoos, and A. J. Hu. Boosting verification by automatic tuning of decision procedures. In Formal Methods in Computer Aided Design (FMCAD), pages 27--34, 2007. Google ScholarDigital Library
- F. Hutter, H. H. Hoos, and K. Leyton-Brown. Sequential model-based optimization for general algorithm configuration. In Learning and Intelligent Optimization (LION), pages 507--523, 2011. Google ScholarDigital Library
- M. Wagner. Maximising axiomatization coverage and minimizing regression testing time. In IEEE Congress on Evolutionary Computation (CEC), pages 2885--2892, 2014.Google ScholarCross Ref
- F. Wu, W. Weimer, M. Harman, Y. Jia, and J. Krinke. Deep parameter optimisation. In Genetic and Evolutionary Computation Conference (GECCO), pages 1375--1382. ACM, 2015. Google ScholarDigital Library
Index Terms
Speeding up the Proof Strategy in Formal Software Verification
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