Abstract
When the expression “Software Quality” is used, we usually think in terms of an excellent software product that fulfills our expectations. These expectations are based on the intended use. Number of models has been proposed for evaluation of software quality based on various characteristics. In this paper quality of software product is defined in terms of basic components as constituent part of any program or software and proposed a software quality prediction model based on basic components. It has been justified with example that if any software quality model uses the tacit knowledge that will be better than any other model in terms of quality.
Highlights
For each quality characteristics, a set of attributes, which can be measured, is determined such a definition helps in evaluating the quality of software [10].Effective software quality evaluation and assurance requires models that describe what the software quality is and how can it be traced back to the development process
In this paper quality of software product is defined in terms of basic components as constituent part of any program or software and proposed a software quality prediction model based on basic components
It has been justified with example that if any software quality model uses the tacit knowledge that will be better than any other model in terms of quality
Summary
A set of attributes, which can be measured, is determined such a definition helps in evaluating the quality of software [10]. Number of models [5,6,7,10,11,12] has been proposed to evaluate the quality of software product, based on various quality characteristics. This paper proposed, a quality model based on basic components. Basic components have been chosen based on the five quality attributes: reliability, usability, efficiency, maintainability and portability. This model focused on direct specification & evaluation of quality of software product, which satisfies to the user. Proposed model has been illustrated with example and shown the importance of tacit knowledge for software product quality prediction
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