Entailment-Based Intelligent System for Software Project Monitoring and Control

• Published in: IEEE systems journal Vol. 12; no. 1; pp. 216 - 227
• Main Authors: Chang, Yung-Chun, Shih, Cheng-Wei, Hsu, Wen-Lian
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Control systems; Intelligent systems; Monitoring; Natural language processing; Progress reports; Project management; project monitoring and control; risk management; Schedules; Software; Text recognition; textual entailment recognition
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2016.2563463

In recent years, software project managers compare actual completion of activities against the progress reports filled by project members to identify significant deviations from the estimated schedules and manage software project risks. However, quantitative measurements are limited due to the format of project documents, which are mostly natural languages. In this paper, we propose an intelligent system for software project monitoring and control by using natural language processing techniques to recognize textual entailment of progress reports to further evaluate the level of project fulfillment in a qualitative manner. Our experimental results demonstrate that the proposed method can recognize entailment from text efficiently and outperform other textual entailment approaches. Moreover, we successfully apply the textual entailment technique to project monitoring and control, which not only reduces the project cost and human's effort but also provides a basis for project managers to qualitatively evaluate the performance of each project member.