Assisting software engineering students in analyzing their performance in software development

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Mushtaq Raza (Author) Other; João Pascoal Faria (Author) FEUP; Rafael Salazar (Author) Other

Journal

Title: Software Quality Journal

Vol. 27 No. 3

Pages: 1209-1237

ISSN: 0963-9314

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 3 Citations

Other information

Authenticus ID: P-00Q-3C2

DOI: 10.1007/s11219-018-9433-7

Abstract (EN): Collecting product and process measures in software development projects, particularly in education and training environments, is important as a basis for assessing current performance and opportunities for improvement. However, analyzing the collected data manually is challenging because of the expertise required, the lack of benchmarks for comparison, the amount of data to analyze, and the time required to do the analysis. ProcessPAIR is a novel tool for automated performance analysis and improvement recommendation; based on a performance model calibrated from the performance data of many developers, it automatically identifies and ranks potential performance problems and root causes of individual developers. In education and training environments, it increases students' autonomy and reduces instructors' effort in grading and feedback. In this article, we present the results of a controlled experiment involving 61 software engineering master students, half of whom used ProcessPAIR in a Personal Software Process (PSP) performance analysis assignment, and the other half used a traditional PSP support tool (Process Dashboard) for performing the same assignment. The results show significant benefits in terms of students' satisfaction (average score of 4.78 in a 1-5 scale for ProcessPAIR users, against 3.81 for Process Dashboard users), quality of the analysis outcomes (average grades achieved of 88.1 in a 0-100 scale for ProcessPAIR users, against 82.5 for Process Dashboard users), and time required to do the analysis (average of 252 min for ProcessPAIR users, against 262 min for Process Dashboard users, but with much room for improvement).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 29