Title: Entropy-based discretisation for performance prediction of employee: strategy for improving software quality

Authors: Sangita Gupta; Uma Mohan Mokashi; V. Suma

Addresses: Department of Computer Science, Jain University, Bangalore, India ' London School of Commerce, London, UK ' Department of Information Sciences, Dayananda Institutions, Bangalore, India

Abstract: Software engineering focuses upon generation of high quality product through well defined process. Quality can be perceived by two major dimensions namely through process quality and through people quality. Since people drive the process, the quality of software development process is controlled by the quality level of the people. Consequently, it is vital to carry the software development activities with team possessing good skills set. Personnel attributes provide the largest scope for improving software development and enhancing the quality. A fundamental issue is however to assess human performance. An in-depth analysis using data mining techniques is carried out in several software industries and the results thus obtained enable one to gain an insight about the quality of personnel information. These approach further aids to identify the most capable project personnel who can drive the quality of the software being developed.

Keywords: human aspect of software engineering; data mining; classification; entropy-based discretisation; software quality; software development process.

DOI: 10.1504/IJPQM.2017.085252

International Journal of Productivity and Quality Management, 2017 Vol.21 No.4, pp.411 - 428

Received: 10 Dec 2015
Accepted: 17 Apr 2016

Published online: 19 Jul 2017 *

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