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An analysis on the applicability of meta-heuristic searching techniques for automated test data generation in automatic programming assessment

Musa, Ja’afar and Romli, Rohaida and Yusoff, Nooraini (2019) An analysis on the applicability of meta-heuristic searching techniques for automated test data generation in automatic programming assessment. Open Access Baghdad Science Journal, 16 (SI). pp. 515-533. ISSN 2078-8665

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Abstract

Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient testing. Nonetheless, thus far the researches on APA have not yet usefully exploited the techniques accordingly to include a better quality program testing coverage. Therefore, this study has conducted a comparative evaluation to identify any applicable MHST to support efficient Automated Test Data Generation (ATDG) in executing a dynamic-functional testing in APA. Several recent MHST are included in the comparative evaluation combining both the local and global search algorithms ranging from the year of 2000 until 2018. Result of this study suggests that the hybridization of Cuckoo Search with Tabu Search and lévy flight as one of promising MHST to be applied, as it’s outperforms other MHST with regards to number of iterations and range of inputs.

Item Type: Article
Uncontrolled Keywords: Automatic Programming Assessment, Automated Test Data Generation, Metaheuristic Search Techniques.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 26 Sep 2019 01:31
Last Modified: 26 Sep 2019 01:31
URI: https://repo.uum.edu.my/id/eprint/26465

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