Effort Estimation in Software Cost Using Team Characteristics Based on Fuzzy Analogy Method – A Diverse Approach

Malathi, S.; Sridhar, S.

doi:10.1007/978-3-319-11629-7_1

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…Malashi, et al applied fuzzy theory to calculate the similarity between proposed and completed projects. The cost of the proposed project is derived based on the similarity [10]. The accuracy of this method depends on the calculation of similarity.…”

Section: State Of the Art 1 Software Development Cost Estimationmentioning

confidence: 99%

“…For example, (1) Comprehensive weight calculation First, according the method of above section, the objective weight of each factor can be calculated. The steps are as following: 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21 ,22} U/D={ (1,2,10,14), (3,4,8,9,11,13,15,17,18,19,20,21,22), (5,6,7,12,16)}…”

Section: Algorithm Calculation Processmentioning

confidence: 99%

“…This algorithm uses fuzzy set theory to calculate similarity, which is more objectivite. According to formula (9), (10) and (11), the development cost can be estimated by using the fuzzy algorithm based on the data shown in Tab.4. The results are shown in Tab.6.…”

Section: Table 4 the Fuzzy Memberships Of The Samplesmentioning

confidence: 99%

“…no.1 is used as an example to illustrate the process of software development cost estimation. Accordingto formula(10), the similarity between project nos.1 and 2 can be calculated as follows: to the formula(11) , the development cost estimation value of project no.1 can be calculated as follows:M * =0.866×45+0.8×48×(1-0.866)+0.665×50×(1-0.866) ×(1-0.8)+((1-0.866) ×(1-0.8) ×(1-0.665) ×(45+48+50))/3 =45.3(d*m) Algorithm validity analysis (1) Algorithm accuracy analysisSimilar to the estimation process of the project no.1, the estimated costs of other items are shown in Tab.5.From the analysis of the actual and estimation costs shown in Tab.5, the deviation of the fuzzy rough set algorithm is determined and presented inFig.1.…”

mentioning

confidence: 99%

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A Novel Algorithm for Software Development Cost Estimation Based on Fuzzy Rough Set

Wang¹,

Pin²,

Xu³

et al. 2016

JESTR

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Software project cost estimation is a key point for enterprises to make reasonable project quotations. However, most software cost estimation methods have limited features, such as requiring higher data volume or only having lower estimation accuracy. Aiming to resolve these problems, a novel algorithm for software development cost estimation based on fuzzy rough set was presented. First, the influencing factors of software development cost were analyzed. The objective weight of each influencing factor was obtained from the data analysis of completed projects by using rough set theory. Second, the comprehensive weight of each influencing factor was recalculated by combining the results of the first step with the subjective weight of the factors given by the experts. Combining the comprehensive weight with fuzzy theory, fuzzy similarities were calculated. Third, according to fuzzy similarity, several items that were most similar to the current project were selected as the samples from the completed projects. Then, the software development cost was estimated based on the cost data of samples from the completed project. Finally, this new algorithm was verified to be effective. The result showed that the maximum and average deviations of the fuzzy rough set algorithm were less than 10%, and the estimated maximum and average deviations of the fuzzy rough set algorithm were less than that of the fuzzy analogy algorithm. Thus, the algorithm could estimate the software cost accurately.

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Section: State Of the Art 1 Software Development Cost Estimationmentioning

confidence: 99%