Applying spectrum-based fault localization on novice's programs

Araujo, Eliane Pawlowski de Oliveira; Gaudêncio, Matheus; Serey, Dalton; Figueiredo, Jorge C. A. de

doi:10.1109/fie.2016.7757727

Cited by 12 publications

(8 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The majority of the identified papers focus on creating tools for providing automated feedback, a direct consequence of large-scale introductory programming classes [253]. The tools focus mainly on improving the accuracy of fault-finding through various methods [30,253,278,619] and on improving the timeliness of feedback by automatically reusing feedback generated for previous solutions [252,253].…”

Section: Feedback On Assessmentmentioning

confidence: 99%

Introductory programming: a systematic literature review

Luxton-Reilly

Simón

Albluwi

et al. 2018

Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education

361

127

View full text Add to dashboard Cite

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming.This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.

show abstract

Section: Feedback On Assessmentmentioning

confidence: 99%

Introductory programming: a systematic literature review

Luxton-Reilly

Simón

Albluwi

et al. 2018

Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education

361

127

View full text Add to dashboard Cite

show abstract

“…Therefore, it is widely used in fault localization in student programs. Eliane Araujo [15] and Yuxing Liu [16] both applied SBFL to student programs and conducted empirical studies, and the experiments showed that SBFL was able to locate faults in student programs. Researchers have proposed new approaches to further improve the effectiveness of SBFL in student programs.…”

Section: Spectrum-based Fault Localizationmentioning

confidence: 99%

“…Among them, Spectrum-Based Fault Localization (SBFL) is a lightweight fault localization method that can provide fast feedback. But traditional SBFL techniques cannot obtain satisfactory accuracy in student programs [3], as the SBFL cannot distinguish the suspicion of statements in one function block. Therefore, it is necessary to investigate a fault localization technique for the student programs and thus help students find the faults in the program quickly.…”

Section: Introductionmentioning

confidence: 99%

Boosting Spectrum-Based Fault Localization via Multi-Correct Programs in Online Programming

ZHENG,

HU,

CHEN

et al. 2024

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

Providing students with useful feedback on faulty programs can effectively help students fix programs. Spectrum-Based Fault Location (SBFL), which is a widely studied and lightweight technique, can automatically generate a suspicious value of statement ranking to help users find potential faults in a program. However, the performance of SBFL on student programs is not satisfactory, to improve the accuracy of SBFL in student programs, we propose a novel Multi-Correct Programs based Fault Localization (MCPFL) approach. Specifically, We first collected the correct programs submitted by students on the OJ system according to the programming problem numbers and removed the highly similar correct programs based on code similarity, and then stored them together with the faulty program to be located to construct a set of programs. Afterward, we analyzed the suspiciousness of the term in the faulty program through the Term Frequency-Inverse Document Frequency (TF-IDF). Finally, we designed a formula to calculate the weight of suspiciousness for program statements based on the number of input variables in the statement and weighted it to the spectrum-based fault localization formula. To evaluate the effectiveness of MCPFL, we conducted empirical studies on six student program datasets collected in our OJ system, and the results showed that MCPFL can effectively improve the traditional SBFL methods. In particular, on the EXAM metric, our approach improves by an average of 27.51% on the Dstar formula.

show abstract

“…Using this concept, Su et al constructed a Moodle-based online learning environment to provide feedback for logic errors [21]. In a study related to this technique, the accuracy of logic error detection using only 20% of the source code and the effectiveness of feedback using a lightweight spectrumbased algorithm were verified [22].…”

Section: Related Researchmentioning

confidence: 99%

Logic Error Detection System based on Structure Pattern and Error Degree

Yoshizawa¹,

Watanobe²

2019

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

The importance of programming skills has increased with advances in information and communication technology (ICT). However, the difficulty of learning programming is a major problem for novices. Therefore, we propose a logic error detection algorithm based on structure patterns, which are an index of similarity based on abstract syntax trees, and error degree, which is a measure of appropriateness for feedback. We define structure patterns and error degree and present the proposed algorithm. In addition, we develop a Logic Error Detector (LED) Application Programming Interface (API) based on the proposed algorithm. An implementation of the proposed algorithm is used in experiments using actual data from an e-learning system. The results show that the proposed algorithm can accurately detect logic errors in many programs solving problems in the Introduction to Programming set.

show abstract

Applying spectrum-based fault localization on novice's programs

Cited by 12 publications

References 12 publications

Introductory programming: a systematic literature review

Introductory programming: a systematic literature review

Boosting Spectrum-Based Fault Localization via Multi-Correct Programs in Online Programming

Logic Error Detection System based on Structure Pattern and Error Degree

Contact Info

Product

Resources

About