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.
KeywordsSoftware EngineeringSoftware MetricsFourth Generation LanguagesCASE ToolsField StudyTools And TechniquesModels And PrinciplesTeam SizeVolatilityDevelopment Platform And TypeProductivityElapsed Development Time
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