An integrated approach of class testing using firefly and moth flame optimization algorithm. Issue 2 (17th February 2020)

• Record Type: Journal Article
• Authors: Sharma, Rashmi; Saha, Anju
• Is Part Of: Journal of information & optimization sciences. Volume 41:Issue 2(2020)
• Page Start: 599
• Page End: 612
• Publication Date: 2020-02-17
• Subjects: 68N30; Software testing -- Metaheuristic -- Firefly Algorithm -- Moth Flame Optimization Algorithm -- Object-Oriented -- Path Testing -- State Machine; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2020.1733192
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: Path testing is an extensively used approach of software testing. Generation of test paths is the core concept of path testing. The recent approaches of software test paths generation are based on the nature-inspired metaheuristic algorithms. An amalgamated approach constructed on the glaring arrangement of fireflies together with the attractive conduct of moths with respect to a flame has been presented in this article. The proposed algorithm combines the individual aspects of two metaheuristics, namely, Moth Flame Optimization Algorithm (MFO) and Firefly Algorithm (FA) for test paths generation. The hybrid algorithm selects a starting node, traverses the connected path and iteratively evolves the complete test path after applying a series of operations. The enactment of the proposed algorithm is verified on the five object-oriented benchmark applications. The proposed algorithm is compared with both MFO and FA. Results confirm full coverage of the path which is the main motive of path testing. Also, reduced and less redundant test paths have been generated via proposed hybrid algorithm as compared to MFO and FA.