Search: onr:"swepub:oai:research.chalmers.se:402eb270-f2b6-4d39-8aeb-66f0df1b23b4" >
Generating Diverse ...
Generating Diverse Test Suites for Gson Through Adaptive Fitness Function Selection
-
- Almulla, Hussein (author)
- University of South Carolina
-
- Gay, Gregory, 1987 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU)
-
(creator_code:org_t)
- ISBN 9783030597610
- 2020-09-30
- 2020
- English.
-
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030597610 - 9783030597627 ; SSBSE 2020, s. 246-252
- Related links:
-
https://research.cha... (primary) (free)
-
show more...
-
https://research.cha...
-
https://research.cha...
-
https://doi.org/10.1...
-
https://research.cha...
-
https://gup.ub.gu.se...
-
show less...
Table of contents
Abstract
Subject headings
Close
No table of content available
- Many fitness functions - such as those targeting test suite diversity—do not yield sufficient feedback to drive test generation. We propose that diversity can instead be improved through adaptive fitness function selection (AFFS), an approach that varies the fitness functions used throughout the generation process in order to strategically increase diversity. We have evaluated our AFFS framework, EvoSuiteFIT, on a set of 18 real faults from Gson, a JSON (de)serialization library. Ultimately, we find that AFFS creates test suites that are more diverse than those created using static fitness functions. We also observe that increased diversity may lead to small improvements in the likelihood of fault detection.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
Keyword
- Search-based test generation
- fitness function
- reinforcement learning
- Fitness function
- Reinforcement learning
- Search-based test generation
Publication and Content Type
- kon (subject category)
- ref (subject category)
Find in a library
To the university's database