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lines changed Original file line number Diff line number Diff line change 11Summary: Papers and talks about PropEr
22kate: replace-tabs-save on; replace-tabs on; tab-width 8;
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4+ * Andreas Löscher and Konstantinos Sagonas.
5+ "Automating Targeted Property-Based Testing",
6+ In Proceedings of the
7+ [ 11th IEEE Conference on Software Testing, Validation and Verification] ( http://www.es.mdh.se/icst2018/ ) ,
8+ Västerås, Sweden, April 2018.
9+ [[ PDF]] ( /papers/icst2018.pdf )
10+ [[ Abstract]] ( /papers/icst2018.txt )
11+ [[ Slides]]
12+ [[ Bib]] ( /papers/icst2018.bib )
13+
14+ * Andreas Löscher, Konstantinos Sagonas, and Thiemo Voigt.
15+ "Property-based Testing of Sensor Networks",
416* Andreas Löscher and Konstantinos Sagonas.
517 "Targeted Property-Based Testing",
618 In Proceedings of the
Original file line number Diff line number Diff line change 1+ @InProceedings {AutomatedTargetedPBT@ICSST-18 ,
2+ author = " Andreas L{\"o}scher and Konstantinos Sagonas" ,
3+ title = " Automating Targeted Property-Based Testing" ,
4+ booktitle = " Proceedings of the 11th IEEE Conference on Software Testing, Validation and Verification" ,
5+ series = { ICST 2018} ,
6+ month = apr,
7+ year = { 2018} ,
8+ publisher = { IEEE} ,
9+ }
Original file line number Diff line number Diff line change 1+ Targeted property-based testing is an enhanced form of property-based testing
2+ (PBT) where the input generation is guided by a search strategy instead of being
3+ random, thereby combining the strengths of QuickCheck-like and search-based
4+ testing techniques.
5+ To use it, however, the user currently needs to specify a search
6+ strategy and also supply all ingredients that the search strategy requires.
7+ This is often a laborious process and makes targeted PBT less attractive
8+ than its random counterpart.
9+ In this paper, we focus on simulated annealing, the default search strategy
10+ of our tool, and present a technique that automatically creates all the
11+ ingredients that targeted PBT requires starting from only a random generator.
12+ Our experiments, comparing the automatically generated ingredients to fine-tuned
13+ manually written ones, show that the performance that one obtains
14+ is sufficient and quite competitive in practice.
15+
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