An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment

Musa Et Al

doi:10.21123/bsj.2019.16.2(si).0515

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.

Highlights

Courses related to programming are viewed as the core subject of most of the Information Technology or Computer Science field [1]
The method that was used in this phase is a literature survey that involves the review on existing works with respect to Automatic Programming Assessment (APA), Automated Test Data Generation (ATDG), and an integration of ATDG and APA with the main focus on dynamic-functional testing
The method that was utilized in this phase is a comparative evaluation technique which consists of four activities: a) Selection of the objects for evaluation – in this process, among of the recent Meta-Heuristic Search Techniques (MHST) that are most commonly applied to support ATDG in software testing researches were identified

Summary

Introduction

Courses related to programming are viewed as the core subject of most of the Information Technology or Computer Science field [1]. In achieving the learning outcomes in this field, to be skillful in programming is vital. Manual assessment on students’ source codes and grading them in a large class is practically troublesome and time consuming to lecturers [3]. This is due to the facts that these activities lead to an extensive workload and burdensome tasks and most regularly foster unintended biases and distinctive standard of grading schemes. Many Automatic Programming Assessment Systems (or APAS) were produced such as Assyst [4], BOSS [5], TRAKLA [6], CourseMaster [7], SAC [8] and Bottlenose [9]

Methods

Results

Conclusion