@article {Idri2016990, title = {Improved estimation of software development effort using Classical and Fuzzy Analogy ensembles}, journal = {Applied Soft Computing Journal}, volume = {49}, year = {2016}, note = {cited By 1}, pages = {990-1019}, abstract = {Delivering an accurate estimate of software development effort plays a decisive role in successful management of a software project. Therefore, several effort estimation techniques have been proposed including analogy based techniques. However, despite the large number of proposed techniques, none has outperformed the others in all circumstances and previous studies have recommended generating estimation from ensembles of various single techniques rather than using only one solo technique. Hence, this paper proposes two types of homogeneous ensembles based on single Classical Analogy or single Fuzzy Analogy for the first time. To evaluate this proposal, we conducted an empirical study with 100/60 variants of Classical/Fuzzy Analogy techniques respectively. These variants were assessed using standardized accuracy and effect size criteria over seven datasets. Thereafter, these variants were clustered using the Scott-Knott statistical test and ranked using four unbiased errors measures. Moreover, three linear combiners were used to combine the single estimates. The results show that there is no best single Classical/Fuzzy Analogy technique across all datasets, and the constructed ensembles (Classical/Fuzzy Analogy ensembles) are often ranked first and their performances are, in general, higher than the single techniques. Furthermore, Fuzzy Analogy ensembles achieve better performance than Classical Analogy ensembles and there is no best Classical/Fuzzy ensemble across all datasets and no evidence concerning the best combiner. {\textcopyright} 2016 Elsevier B.V.}, doi = {10.1016/j.asoc.2016.08.012}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84997417515\&doi=10.1016\%2fj.asoc.2016.08.012\&partnerID=40\&md5=b29d5f00b8c137b8fef1ba5d0c2a68a1}, author = {Idri, A.a and Hosni, M.a and Abran, A.b} } @conference {Amazal2014247, title = {Improving fuzzy analogy based software development effort estimation}, booktitle = {Proceedings - Asia-Pacific Software Engineering Conference, APSEC}, volume = {1}, year = {2014}, note = {cited By 0}, pages = {247-254}, abstract = {Analogy-based estimation has recently emerged as a promising technique and a viable alternative to other conventional estimation methods. One of the most important research areas for analogy-based cost estimation is how to predict the effort of software projects when they are described by mixed numerical and categorical data. To address this issue, we have proposed, in an earlier work, a new approach called fuzzy analogy combining the key features of fuzzy logic and analogybased reasoning. However, fuzzy analogy may only be used when the possible values of the categorical attributes are derived from a numerical domain. The current study aims to extend our former approach to correctly handle categorical data. To this end, the fuzzy k-modes algorithm is used with two initialization techniques. The performance of the proposed approach was compared with that of classical analogy using the International Software Benchmarking Standards Group (ISBSG) dataset. The obtained results show significant improvement in estimation accuracy. {\textcopyright} 2014 IEEE.}, doi = {10.1109/APSEC.2014.46}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84951282652\&doi=10.1109\%2fAPSEC.2014.46\&partnerID=40\&md5=864ca37db60e0c0338a8f4ae557a43a4}, author = {Amazal, F.A.a and Idri, A.a and Abran, A.b} }