Applying Spectrum-Based Fault Localization On Novice'S Programs

Most introductory programming courses count on automated assessment systems (AAS) to support practical programming assignments and give fast feedback. AAS usually rely on tests results to check the program's functional correctness to provide feedback to students. Novice programmers, however, may find it difficult to map such feedback to the root failures' cause in their programs. It can be even more frustrating when the code is "almost right". In this paper we investigated the use of a fault localization technique on programs produced by students of introductory programming. Our proposed approach is grounded on spectrum-based fault localization (SBFL). The results of our empirical study showed that this lightweight technique is promising. It can be easily adapted to different AAS to generate useful feedback not only to students but also to instructors. We also delineate the scope where SBFL use is jeopardized. The main contribution of this paper is to present the benefits and drawbacks of applying SBFL, in the context of programming learning, as a novel source of information about students' programming assignments faults.