Complexity measurement of a graphical programming language
Software—Practice & Experience
Experimental design and analysis in software engineering, part 5: analyzing the data
ACM SIGSOFT Software Engineering Notes
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Predicting Source-Code Complexity at the Design Stage
IEEE Software
Software Development Cost Estimation Using Function Points
IEEE Transactions on Software Engineering
Robust estimation in software experiments
ACM SIGSOFT Software Engineering Notes
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Software development, like other scientific developments, requires formal experiments with a great deal of plan and analysis if they are to provide meaningful results[11]. This paper uses examples to extend the discussion to a certain statistical analysis, the prediction confidence interval, which have been pointed out but never been fully discussed. The purpose of this paper is to provide a better understanding of a statistical analysis for software experimenters when the experimental data is not as nice as expected.