Modeling Metrics for Monitoring Software Project Performance Based On the GQM Model
There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1097054Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1817
 Standish Group, “CHAOS Summary Report”, 2009.
 Sivathanu Pillai, Joshi, Srinivasa Rao, “Performance measurement of R&D projects in a multi-project, concurrent engineering environment”. International Journal of Project Management 20, 165-177, 2002.
 Neely, A.D., Gregory, M., Platts, K.,” Performance measurement system design: a literature review and research agenda”. International Journal of Operations and Production Management 25(12), 1228–1263, 2005.
 Kanhaiya Jethani, “Software metrics for effective project management”. International Journal System Assurance Management 4(4), 335-340, 2013.
 Frank van Latum, Rini van Solingen, Adopting GQM-Based Measurement in an Industrial Environment.IEEE Xplore, 1998.
 Victor Basili, V.R., C.Caldiera, H.D. Rombach, “Goal Question Metric Paradigm”, Encylopedia of Software Engineering,(Marcianik, J.J., editor), Volume 1, John Willey and Sons, pp. 528532, 1994a.
 B. Kitchenham, “ Guidelines for performing systematic literature reviews in software engineering (version 2.3), Software Engineering Group, School of Computer Science and Mathemathics, Keele University and Department of Computer Science, University of Durham, 2007.
 Clarke, and Braun, V., 2013. “Teaching Themeatic Analysis: Overcoming challengges and devloping strategies for effective learning”. The Psychologist, 26 (2). pp. 120-123, ISSN 0952-8229,2013.