With the advance of computational techniques, the amount of genomic data has risen exponentially, with a rapid rate [1] making it hard to utilize such data in the medical field without appropriate pre-processing, which in turn leads to more complexity and veracity issues [2] eventually creating multiple complications such as storage, analysis, privacy and security. Therefore, genomic data may look easy to handle in terms of its volume, but it actually requires quite a complicated process due to the complexity, heterogeneity and hybridity of its features. This process is entitled knowledge discovery process [3]: • Data recording Includes the different challenges and tools regarding the capture and storage of data. • Data pre-processing Which includes all the operations of cleaning and appropriation of the captured data to the ready to analyze form in order to optimize the analysis step. • Data analysis The task of evaluating data using different algorithms following a logical reasoning to examine each component of the data provided, with the aim of dispensing insightful outcomes.

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The aim of this paper is to evaluate and to compare the Classical Analogy and Fuzzy Analogy for software cost estimation on a Web software dataset. Hence, the paper aims to replicate the results of our precedent experiments on this dataset. Moreover, questions regarding the estimates accuracy, the tolerance of imprecision and uncertainty of cost drivers, and the favorable context to use estimation by analogy are discussed. This study approved the usefulness of Fuzzy Analogy for software cost estimation.

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