An Improved Jaya Algorithm-Based Strategy for T-Way Test Suite Generation

Nasser, Abdullah B.; Hujainah, Fadhl; Alsewari, AbdulRahman A.; Zamli, Kamal Z.

doi:10.1007/978-3-030-33582-3_34

Cited by 9 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…JA is a simple but robust algorithm [25]. JA based strategies have overcome the complexities due to slow convergence and performed well in t-way testing [26].…”

Section: Related Workmentioning

confidence: 99%

Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…JA is a simple but robust algorithm [25]. JA based strategies have overcome the complexities due to slow convergence and performed well in t-way testing [26].…”

Section: Related Workmentioning

confidence: 99%

Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Improved Jaya Algorithm (IJA) [50] is a populationbased algorithm developed to address constrained and unconstrained problems. The key idea behind the algorithm is that every candidate solution will seek the best solution while simultaneously evading the worse solution.…”

Section: Related Workmentioning

confidence: 99%

“…Then, the current test case is updated based on the best and worst test cases. To improve diversity and a quality solution, lévy flight was introduced, as well as a mutation operation, to improve the convergence speed of the proposed method in generating a test suite [50].…”

Section: Related Workmentioning

confidence: 99%

“…To evaluate the performance of the WOA strategy, we compared WOA against six other t-way strategies that were also implemented. The performance evaluation criteria included size (i.e., optimal test suite size) [50]. The experimental results are presented in Tables 10 and 11; Table 10 shows the minimum (i.e., best) test suite size while Table 11 shows the average suite size for each competing strategy.…”

Section: Benchmarking Woa Strategy In the Presence Of Constraints mentioning

confidence: 99%

See 1 more Smart Citation

Combinatorial Test Suites Generation Strategy Utilizing the Whale Optimization Algorithm

et al. 2020

Self Cite

View full text Add to dashboard Cite

The potentially many software system input combinations make exhaustive testing practically impossible. To address this issue, combinatorial t-way testing (where t indicates the interaction strength, i.e. the number of interacting parameters (input)) was adopted to minimize the number of cases for testing. Complimentary to existing testing techniques (e.g. boundary value, equivalence partitioning, cause and effect graphing), combinatorial testing helps to detect faults caused by the faulty interaction between input parameters. In the last 15 years, applications of meta-heuristics as the backbone of t-way test suite generation have shown promising results (e.g. Particle Swarm Optimization, Cuckoo Search, Flower Pollination Algorithm, and Hyper-Heuristics (HHH), to name a few). Supporting the new free lunch theorem, as well as potentially offering new insights into the whole process of t-way generation, this paper proposes a new strategy with constraint support based on the Whale Optimization Algorithm (WOA). Our work is the first attempt to adopt the WOA as part of a search-based software engineering (SBSE) initiative for t-way test suite generation with constraint support. The experimental results of the test-suite generation indicate that WOA produces competitive outcomes compared to some selected single-based and population-based metaheuristic algorithms.

show abstract

Comparative Study of Five Metaheuristic Algorithms for Team Formation Problem

Kader

Zamli

2021

Human-Centered Technology for a Better Tomorrow

View full text Add to dashboard Cite

An Improved Jaya Algorithm-Based Strategy for T-Way Test Suite Generation

Cited by 9 publications

References 17 publications

Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm

Construction of Prioritized T-Way Test Suite Using Bi-Objective Dragonfly Algorithm

Combinatorial Test Suites Generation Strategy Utilizing the Whale Optimization Algorithm

Comparative Study of Five Metaheuristic Algorithms for Team Formation Problem

Contact Info

Product

Resources

About