کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
551551 872874 2006 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Optimization of analogy weights by genetic algorithm for software effort estimation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر تعامل انسان و کامپیوتر
پیش نمایش صفحه اول مقاله
Optimization of analogy weights by genetic algorithm for software effort estimation
چکیده انگلیسی

A reliable and accurate estimate of software development effort has always been a challenge for both the software industry and academia. Analogy is a widely adopted problem solving technique that has been evaluated and confirmed in software effort or cost estimation domains. Similarity measures between pairs of effort drivers play a central role in analogy-based estimation models. However, hardly any research has addressed the issue of how to decide on suitable weighted similarity measures for software effort drivers. The present paper investigates the effect on estimation accuracy of the adoption of genetic algorithm (GA) to determine the appropriate weighted similarity measures of effort drivers in analogy-based software effort estimation models. Three weighted analogy methods, namely, the unequally weighted, the linearly weighted and the nonlinearly weighted methods are investigated in the present paper. We illustrate our approaches with data obtained from the International Software Benchmarking Standards Group (ISBSG) repository and the IBM DP services database. The experimental results show that applying GA to determine suitable weighted similarity measures of software effort drivers in analogy-based software effort estimation models is a feasible approach to improving the accuracy of software effort estimates. It also demonstrates that the nonlinearly weighted analogy method presents better estimate accuracy over the results obtained using the other methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information and Software Technology - Volume 48, Issue 11, November 2006, Pages 1034–1045
نویسندگان
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