Visualizing test diversity to support test optimisation
Paper in proceeding, 2018

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 testersĀ  in their maintenance and optimisation activities.

Software Testing

Search- based Software Testing

Diversity

Empirical Study

Author

Francisco Gomes

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Robert Feldt

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Linda Erlenhov

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Jose Benardi De Souza Nunes

Federal University of Campina Grande

Proceedings - Asia-Pacific Software Engineering Conference, APSEC

15301362 (ISSN)

Vol. 2018-December
9781728119700 (ISBN)

25th Asia-Pacific Software Engineering Conference (APSEC)
Nara , Japan,

Subject Categories

Software Engineering

Computer Science

Computer Systems

DOI

10.1109/APSEC.2018.00029

ISBN

9781728119700

More information

Latest update

7/17/2024