Sunita Chulani

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This paper summarizes several classes of software cost estimation models and techniques: parametric models, expertise-based techniques, learning-oriented techniques, dynamics-based models, regression-based models, and composite-Bayesian techniques for integrating expertisebased and regression-based models. Experience to date indicates that neural-net and(More)
To date many software engineering cost models have been developed to predict the cost, schedule and quality of the software under development. But, the rapidly changing nature of software development has made it extremely difficult to develop empirical models that continue to yield high prediction accuracies. Software development costs continue to increase(More)
Cost, schedule and quality are highly correlated factors in software development. They basically form three sides of the same triangle. Beyond a certain point (the “Quality is Free” point), it is difficult to increase the quality without increasing either the cost or schedule or both for the software under development. Similarly, development schedule cannot(More)
The COCOMO I1 research effort started in 1994 with the aim of updating software cost estimation models, such as the 1981 Constructive Cost Model and its 1987 Ada update. Both the earlier models experienced difficulties in estimating software projects of the 90s due to challenges such as non-sequential and rapiddevelopment process models; reuse-driven(More)
We propose a quantitative measure of socio-technical congruence as an indicator of the performance of an organization in carrying out a software development project. We show how the information necessary to implement that measure can be mined from commonly used software repositories, and we describe how socio-technical congruence can be computed based on(More)
Most quality and cost models use defect density to represent software quality. Customer’s quality expectations are not typically based on size and complexity of the product they buy and their satisfaction can be influenced substantially by other product attributes that are not typically mapped to defects (e.g. Ease of installation and use, timely support,(More)
Traditional software metrics, such as code coverage, McCabe complexity, etc. address the needs of a software engineer. In contrast, managers of software development organizations face a broader set of issues. For example, an executive responsible for multiple products and releases has to understand the customer views of those products and put in place,(More)
It is difficult to understand, let alone improve the quality of software without the knowledge of its software development process and software product. There must be some measurement process to predict the software development, and to evaluate software products. This paper provides a brief view on Software Quality, Software Metrics and Software Metrics(More)