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P. C. Pendharkar and J. A. Rodger, “A Probabilistic Model and a Belief Updating Procedure for Predicting Software Development Effort,” IEEE Transactions on Software Engineering, Vol. 31, No. 7, 2005, pp. 615-624. doi:10.1109/TSE.2005.75

has been cited by the following article:

• TITLE: Knowledge Management of Software Productivity and Development Time

  AUTHORS: James A. Rodger, Pankaj Pankaj, Ata Nahouraii

  KEYWORDS: Software Engineering, Software Metrics, Fourth Generation Languages, CASE Tools, Field Study, Tools And Techniques, Models And Principles, Team Size, Volatility, Development Platform And Type, Productivity, Elapsed Development Time

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.4 No.11, November 21, 2011

  ABSTRACT: In this paper, we identify a set of factors that may be used to forecast software productivity and software development time. Software productivity was measured in function points per person hours, and software development time was measured in number of elapsed days. Using field data on over 130 field software projects from various industries, we empirically test the impact of team size, integrated computer aided software engineering (ICASE) tools, software development type, software development platform, and programming language type on the software development productivity and development time. Our results indicate that team size, software development type, software development platform, and programming language type significantly impact software development productivity. However, only team size significantly impacts software development time. Our results indicate that effective management of software development teams, and using different management strategies for different software development type environments may improve software development productivity.