Empirical evaluation of fuzzy analogy for Software Development Effort Estimation

TitreEmpirical evaluation of fuzzy analogy for Software Development Effort Estimation
Publication TypeConference Paper
Year of Publication2017
AuthorsAbnane, I, Idri, A, Abran, A
Conference NameProceedings of the ACM Symposium on Applied Computing
Abstract

Software Development Effort Estimation (SDEE) plays a primary role in software project management. Among several techniques suggested for estimating software development effort, analogybased software effort estimation approaches stand out as promising techniques. In this paper, the performance of Fuzzy Analogy is compared with that of six other SDEE techniques (Linear Regression, Support Vector Regression, Multi-Layer Perceptron, M5P and Classical Analogy). The first step of the evaluation aimed to ensure that the SDEE techniques outperformed random guessing by using the Standardized Accuracy (SA). Then, we used a set of reliable performance measures and Borda count to rank them and identify which techniques are the most accurate. The results suggest that Fuzzy Analogy statistically outperformed the other SDEE techniques regardless of the dataset used. © 2017 ACM.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85020898807&doi=10.1145%2f3019612.3019905&partnerID=40&md5=df809b8bee59594505af4961af714d5e
DOI10.1145/3019612.3019905
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