An Expert-Based Requirements Effort Estimation Model Using Bayesian Networks

Mendes, Emilia; Vaz, Verônica T.; Muradas, Fernando

doi:10.1007/978-3-319-27033-3_6

Cited by 2 publications

(1 citation statement)

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“…The application of segmentation, statistical, and classification techniques in software development effort estimation is particularly accepted . Research conducted primarily by Menzies and Boetticher and Mendes et al as well as that of others confirms the applicability of these methods. Typically, to solve estimation problems, authors apply techniques from a single class of data mining learners.…”

Section: Related Researchmentioning

confidence: 96%

Application of data mining methods for effort estimation of software projects

2018

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Summary Information technology companies currently use data mining techniques in different areas with the goal of increasing the quality of decision‐making and to improve their business performance. The study described in this paper uses a data mining approach to produce an effort estimation of a software development process. It is based on data collected in a Croatian information technology company. The study examined 27 software projects with a total effort exceeding 42 000 work hours. The presented model employs a modified Cross‐Industry Standard Process for Data Mining, where prior to model creation, additional clustering of projects is performed. The results generated by the proposed approach generally had a smaller effort estimation error than the results of human experts. The applied approach has proved that sound results can be gained through the use of data mining within the studied area. As a result, it would be wise to use such estimates as additional input in the decision‐making process.

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Section: Related Researchmentioning

confidence: 96%