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Visualizing test diversity to support test optimisation

Gomes, Francisco, 1987 (author)
Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik, Software Engineering (GU),Institutionen för data- och informationsteknik, Software Engineering (GU)
Feldt, Robert, 1972 (author)
Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik, Software Engineering (GU),Institutionen för data- och informationsteknik, Software Engineering (GU)
Erlenhov, Linda, 1979 (author)
Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik, Software Engineering (GU),Institutionen för data- och informationsteknik, Software Engineering (GU)
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Nunes, Jose Benardi De Souza (author)
Universidade Federal de Campina Grande,Federal University of Campina Grande
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 (creator_code:org_t)
ISBN 9781728119700
2018
2018
English.
In: Proceedings - Asia-Pacific Software Engineering Conference, APSEC. - 1530-1362. - 9781728119700 ; 2018-December
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Diversity has been used as an effective criteria to optimise test suites for cost-effective testing. Particularly, diversity-based (alternatively referred to as similarity-based) techniques have the benefit of being generic and applicable across different Systems Under Test (SUT), and have been used to automatically select or prioritise large sets of test cases. However, it is a challenge to feedback diversity information to developers and testers since results are typically many-dimensional. Furthermore, the generality of diversity-based approaches makes it harder to choose when and where to apply them. In this paper we address these challenges by investigating: i) what are the trade-off in using different sources of diversity (e.g., diversity of test requirements or test scripts) to optimise large test suites, and ii) how visualisation of test diversity data can assist testers for test optimisation and improvement. We perform a case study on three industrial projects and present quantitative results on the fault detection capabilities and redundancy levels of different sets of test cases. Our key result is that test similarity maps, based on pair-wise diversity calculations, helped industrial practitioners identify issues with their test repositories and decide on actions to improve. We conclude that the visualisation of diversity information can assist testers  in their maintenance and optimisation activities.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Keyword

Software Testing
Search- based Software Testing
Diversity
Empirical Study
Software Testing
Diversity
Search-based Software Testing
Empirical Study

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