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Publication Detail
Assessing the effectiveness of approximate functional sizing approaches for effort estimation
Abstract
Context: Functional Size Measurement (FSM) methods, like Function Points Analysis (FPA) or COSMIC, are well-established approaches to estimate software size. Several approximations of these methods have been recently proposed as they require less time/information to be applied, however their effectiveness for effort prediction is not known. Objective: The effectiveness of approximated functional size measures for estimating the development effort is a key open question, since an approximate sizing approach may miss to capture factors affecting the effort. Therefore, we empirically investigated the use of approximate FPA and COSMIC sizing approaches, also compared with their standard versions, for effort estimation. Method: We measured 25 industrial software projects realised by a single company by using FPA, COSMIC, two approximate sizing approaches proposed by IFPUG for FPA (i.e. High Level and Indicative FPA), and three approximate sizing approaches proposed by the COSMIC organisation for COSMIC (i.e. Average Functional Process, Fixed Size Classification, and Equal Size Band). Then we investigated the quality of the regression models built using the obtained measures to estimate the development effort. Results: Models based on High Level FPA are effective, providing a prediction accuracy comparable to the one of the original FPA, while those based on the Indicative FPA method show poor estimation accuracy. Models based on COSMIC approximate sizing methods are also quite effective, in particular those based on the Equal Size Band approximation provided an accuracy similar to the one of standard COSMIC. Conclusion: Project managers should be aware that predictions based on High Level FPA and standard FPA can be similar, making this approximation very interesting and effective, while Indicative FPA should be avoided. COSMIC approximations can also provide accurate effort estimates, nevertheless, the Fixed Size Classification and Equal Size Band approaches introduce subjectivity in the measurement.
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Dept of Computer Science
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