Predictive Object Points (POP) Sizing Metric: A Good Predictor of Quality of OO Software
Shubha Jain, Shantanu Pant, Raghuraj Singh · Indian Journal of Science and Technology · 2018
Measuring the quality of software is an essential task as it leads to the minimization of cost in allocation of resources for testing or maintenance effort. With the emergence of Object Oriented (OO) technologies as a dominant software engineering practice today, it is required to investigate object-oriented metrics with respect to the software quality. This paper is an attempt for measuring the quality attributes of an OO system during the design phase using Predictive Object Point software sizing metrics set in. This paper relates high-level quality attributes such as reusability, flexibility, understandability, functionality, extendibility and effectiveness to Predictive Object Point Count and hence shows that Predictive Object Point Metrics set can be used to make quality decisions. The proposed model of assessment of quality through POP Count at the design phase has been studied on the several separate versions of three object oriented software which are developed for the same types of requirements and objectives. A quality metric tool has been developed to measure the various design metrics and hence the quality attributes of the projects under study. The trend observed through these quality attributes is compared with the corresponding POP Count values. The results have been analyzed and presented to show that the POP Count can be used to assess the quality of an object oriented system. Keywords: Automation, Object Orientation, Predictive Object Point, Quality Attributes, Quality Measurement, Quality Model, Software Metrics,