By Márcio Barros, Yvan Labiche
This e-book constitutes the refereed lawsuits of the seventh overseas Symposium on Search-Based software program Engineering, SSBSE 2015, held in Bergamo, Italy, in September 2015.
The 12 revised complete papers offered including 2 invited talks, four brief papers, 2 papers of the graduate song, and thirteen problem tune papers have been rigorously reviewed and chosen from fifty one submissions. seek established software program Engineering (SBSE) reviews the applying of meta-heuristic optimization innovations to varied software program engineering difficulties, starting from specifications engineering to software program trying out and maintenance.
Read Online or Download Search-Based Software Engineering: 7th International Symposium, SSBSE 2015, Bergamo, Italy, September 5-7, 2015, Proceedings PDF
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Additional resources for Search-Based Software Engineering: 7th International Symposium, SSBSE 2015, Bergamo, Italy, September 5-7, 2015, Proceedings
ICSE 2009, Vancouver, pp. 364– 374 (2009). uk/∼wbl/biblio/gp-html/Weimer 2009 ICES. html 5. : A genetic programming approach to automated software repair. , et al. ) GECCO 2009, pp. 947–954, ACM, Montreal (2009) (Best paper). html 6. : Automatic program repair with evolutionary computation. Commun. ACM 53(5), 109–116 (2010). html 7. : Designing better ﬁtness functions for automated program repair. , et al. ) GECCO 2010, pp. 965–972. ACM (2010). html 8. : Automated program repair through the evolution of assembly code.
Runs out of the allocated ﬁtness evaluations), it becomes virtually zero. Implementation. The amortised optimisation for JIT parameters is implemented into a Python package called piacin1 . org/ntrolls/ piacin. Amortised Optimisation of Non-functional Properties 37 Table 1. test= nbody&lang=python&id=4. com/p/v8/. com/p/spitﬁre/ need to be set once during the execution of a single user script, piacin similarly only needs to be called twice: when the user script starts (to conﬁgure pypy with the current parameters), and when it ﬁnishes (to record the ﬁtness value associate with the current parameters).
Automatic generation of caching algorithms. , et al. ) Evolutionary Algorithms in Engineering and Computer Science, pp. 127-134, John Wiley and Sons, Jyv¨ askyl¨ a, Finland (1999). bham. html 22. : Evolutionary design of en-route caching strategies. Appl. Soft Comput. 7(3), 890–898 (2006). html 23. : A parallel evolutionary algorithm to optimize dynamic memory managers in embedded systems. Parallel Comput. 36(10–11), 572–590 (2010). ac. html 24. : Deep parameter optimisation. In: GECCO 2015. ACM, Madrid (2015).