Bug Pattern Analysis of Codes Produced By Beginner Programmers Using Association Rule Mining Techniques

Keywords

Computer Programming,
Bug Patterns,
Data Mining
Association Rule Mining

Abstract

Abstract Bugs are errors in computer programs that cause unexpected results or programs to behave in unintended ways. Bug pattern are erroneous coding practices that mainly arise from poor programming design pattern and misunderstanding of language features. Beginner programmers elicit the feeling of fears like lack of selfconfidence, low level of comfort and high level of anxiety in apprehension of programming. This is termed to be boring and they spent many hours in debugging single bug in a program. For discovering the most prevalent and detectable bug pattern, we propose an association rule mining techniques to predict and analyze the bugs commonly incurred among the young programmers. Result from the study generated set of rules that was used to predict the bug patterns in beginner programmers’ codes. Also, further statistical analysis of the study shows from the comparative analysis that semantic, syntax and logic errors form the order of magnitudes at which bugs are commonly incurred in prospective programmers’ codes. As they progress in the study, the reverse is the case with logic, syntax and semantic errors in the programming. Our findings are useful tools and techniques for improving learning process by students and tutoring process by programming tutors; this can be achieved by including it in the learning curriculum. The result of this project will not only creating awareness for novice programmers of the possible bugs commonly incurred, but also served as a milestone for software professionals.