1992
DOI: 10.1109/32.163607
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Software effort models for early estimation of process control applications

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Cited by 155 publications
(28 citation statements)
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“…The accuracy and reliability of a model is highly important as it directly affects the success or the failure of system effort prediction. Project scheduling, controlling, coordination and staffing decisions are always depending on accurate estimation [13]. However, sometimes an inaccurate model can still be consistent if it uniformly misestimates effort for only a set of software project data.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The accuracy and reliability of a model is highly important as it directly affects the success or the failure of system effort prediction. Project scheduling, controlling, coordination and staffing decisions are always depending on accurate estimation [13]. However, sometimes an inaccurate model can still be consistent if it uniformly misestimates effort for only a set of software project data.…”
Section: Discussionmentioning
confidence: 99%
“…Similarly, FPA method is used to make predication of program size using inputs, master files, logical files, interfaces and outputs. Although this method has been widely used by organizations, particularly in Europe, than LOC, it is still not known yet until the design phase is complete [13]. Due to problems of calibrating early effort estimate using both LOC and FPA, it is, therefore, needed to propose a general model for making effort estimates for small and medium application software.…”
Section: Introductionmentioning
confidence: 99%
“…Other research concludes that in specific application domains, process control application, it is possible to estimate the software size from the user specified application features. The limitation here is that the application is restricted to a very specific domain (Mukhopadhyay et al, 1992). Sarah Jane Delay states that it appears impossible to identify features early in the life cycle that defines the size of the project (Delay, 1998).…”
Section: Introductionmentioning
confidence: 99%
“…One subsample is reserved as validation (testing) data, while the remaining K-1 subsamples are used as training data to build the model. To evaluate the performance of the built models, we have to set up the evaluation criteria first, usually MMRE and Pred(m) [27]. The cross-validation process is to be repeated K times, and the K results are then averaged to find out the final performance of that model.…”
Section: Cross-validationmentioning
confidence: 99%