Software engineering metrics and models
Software engineering metrics and models
Tool integration in software engineering environments
Proceedings of the international workshop on environments on Software engineering environments
Software engineering (5th ed.)
Software engineering (5th ed.)
Bayesian Analysis of Empirical Software Engineering Cost Models
IEEE Transactions on Software Engineering
Software Engineering Economics
Software Engineering Economics
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
How to Assess Tools Efficiently and Quantitatively
IEEE Software
Tools That Bind: Creating Integrated Environments
IEEE Software
A Probabilistic Model for Predicting Software Development Effort
IEEE Transactions on Software Engineering
Using industry based data sets in software engineering research
Proceedings of the 2006 international workshop on Summit on software engineering education
An empirical study of process-related attributes in segmented software cost-estimation relationships
Journal of Systems and Software
Software Effort, Quality, and Cycle Time: A Study of CMM Level 5 Projects
IEEE Transactions on Software Engineering
Information and Management
Controversy Corner: A new research agenda for tool integration
Journal of Systems and Software
Statistical process control for software: a systematic approach
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
An application of Bayesian network for predicting object-oriented software maintainability
Information and Software Technology
A probabilistic model for predicting software development effort
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartII
Analysis of effort estimation based on software project models
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
MND-SCEMP: an empirical study of a software cost estimation modeling process in the defense domain
Empirical Software Engineering
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CASE (Computer Aided Software Engineering) tools are believed to have played a critical role in improving software productivity and quality by assisting tasks in software development processes since 1970s. Several parametric software cost models adopt "use of software tools" as one of the environmental factors that affects software development productivity. Several software cost models assess the productivity impacts of CASE tools based just on breadth of tool coverage without considering other productivity dimensions such as degree of integration, tool maturity, and user support. This paper provides an extended set of tool rating scales based on the completeness of tool coverage, the degree of tool integration, and tool maturity/user support. Those scales are used to refine the way in which CASE tools are effectively evaluated within COCOMO (COnstructive COst MOdel) II. In order to find the best fit of weighting values for the extended set of tool rating scales in the extended research model, a Bayesian approach is adopted to combine two sources of (expert-judged and data-determined) information to increase prediction accuracy. The extended model using the three TOOL rating scales is validated by using the cross-validation methodologies, data splitting, and bootstrapping. This approach can be used to disaggregate other parameters that have significant impacts on software development productivity and to calibrate the best-fit weight values based on data-determined and expert-judged distributions. It results in an increase in the prediction accuracy in software parametric cost estimation models and an improvement in insights on software productivity investments.