A Hybrid Artificial Bee Colony Strategy for t-way Test Set Generation with Constraints Support. (April 2020)
- Record Type:
- Journal Article
- Title:
- A Hybrid Artificial Bee Colony Strategy for t-way Test Set Generation with Constraints Support. (April 2020)
- Main Title:
- A Hybrid Artificial Bee Colony Strategy for t-way Test Set Generation with Constraints Support
- Authors:
- Alazzawi, Ammar K
Rais, Helmi Md
Basri, Shuib
Alsariera, Yazan A.
Balogun, Abdullateef Oluwagbemiga
Imam, Abdullahi Abubakar - Abstract:
- Abstract: t -way interaction testing is a systematic approach for exhaustive test set generation. It is a vital test planning method in software testing, which generates test sets based on interaction between parameters to cover every possible test sets combinations. t -way strategy clarifies the interaction strength between the number of parameters. However, there are some test sets combinations that should be excluded when generating the final test set as a result of invalid outputs, impossible or unwanted test sets combinations (e.g. system requirements set). These types of set combinations are known as constraint's combinations or forbidden combinations. From existing studies, several t -way strategies have been proposed to address the test set combination problem, however, generating the optimal test set is still open research being an NP-hard problem. Therefore, this study proposed a novel hybrid artificial bee colony (HABC) t -way test set generation strategy with constraints support. The proposed approach is based on a hybrid artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. PSO was integrated as the exploratory agent for the ABC hence the hybrid nature. The information sharing ability of PSO via the Weight Factor is used to enhance the performance of ABC. The output of the hybrid ABC is a set of promising optimal test set combinations. The results of the experiments showed that HABC outperformed and yielded better test setsAbstract: t -way interaction testing is a systematic approach for exhaustive test set generation. It is a vital test planning method in software testing, which generates test sets based on interaction between parameters to cover every possible test sets combinations. t -way strategy clarifies the interaction strength between the number of parameters. However, there are some test sets combinations that should be excluded when generating the final test set as a result of invalid outputs, impossible or unwanted test sets combinations (e.g. system requirements set). These types of set combinations are known as constraint's combinations or forbidden combinations. From existing studies, several t -way strategies have been proposed to address the test set combination problem, however, generating the optimal test set is still open research being an NP-hard problem. Therefore, this study proposed a novel hybrid artificial bee colony (HABC) t -way test set generation strategy with constraints support. The proposed approach is based on a hybrid artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. PSO was integrated as the exploratory agent for the ABC hence the hybrid nature. The information sharing ability of PSO via the Weight Factor is used to enhance the performance of ABC. The output of the hybrid ABC is a set of promising optimal test set combinations. The results of the experiments showed that HABC outperformed and yielded better test sets than existing methods (HSS, LAHC, SA_SAT, PICT, TestCover, mATEG_SAT). … (more)
- Is Part Of:
- Journal of physics. Volume 1529:Number 4(2020)
- Journal:
- Journal of physics
- Issue:
- Volume 1529:Number 4(2020)
- Issue Display:
- Volume 1529, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 1529
- Issue:
- 4
- Issue Sort Value:
- 2020-1529-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-04
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1529/4/042068 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14061.xml