Improved software cost estimation models: A new perspective based on evolution in Dynamic Environment.
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| Title: | Improved software cost estimation models: A new perspective based on evolution in Dynamic Environment. |
|---|---|
| Authors: | Tripathi, Ashish1, Mishra, K.K.2, Tiwari, Shailesh3 shail.tiwari@yahoo.com, Kumar, Naveen4, Trivedi, Munesh, Kohle, Mohan L. |
| Source: | Journal of Intelligent & Fuzzy Systems. 2018, Vol. 35 Issue 2, p1707-1720. 14p. |
| Subjects: | Computer software costs, Evolutionary algorithms, Estimation theory, MatLab (Computer software), Mathematical optimization |
| Abstract: | Software cost estimation is the process of predicting the most realistic and valid amount of effort necessary for the development of any software. The cost estimation of any software is a difficult assignment due to the involvement of many factors that anyhow affect the estimation process. In literature, many cost estimation models have been developed for more than a decade to maintain accuracy in estimation of the cost of software projects. But, it is found that these models are inefficient to estimate the exact cost of software development because of uncertainties and lack of accuracy associated with them. In this paper, Alla F. Sheta models have been taken for optimization, which are the modified versions of the very famous Boehm’s COCOMO model. Parameters of the Sheta models have been tuned enough by the proposed method to estimate and minimize the consequences of different factors that affect the overall software development cost. Experimental work has been carried out in MATLAB environment and analysis of results is performed on the basis of Magnitude of Relative Error (MRE), Prediction (PRED) at 0.25, Value Accounted For (VAF) and Mean Magnitude of Relative Error (MMRE). Estimation accuracy of the proposed work is tested on NASA software project dataset. It is found that the proposed method shows good estimation capabilities over other state-of-the-art cost estimation models. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 131542908 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Improved software cost estimation models: A new perspective based on evolution in Dynamic Environment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tripathi%2C+Ashish%22">Tripathi, Ashish</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Mishra%2C+K%2EK%2E%22">Mishra, K.K.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Tiwari%2C+Shailesh%22">Tiwari, Shailesh</searchLink><relatesTo>3</relatesTo><i> shail.tiwari@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Kumar%2C+Naveen%22">Kumar, Naveen</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Trivedi%2C+Munesh%22">Trivedi, Munesh</searchLink><br /><searchLink fieldCode="AR" term="%22Kohle%2C+Mohan+L%2E%22">Kohle, Mohan L.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Intelligent+%26+Fuzzy+Systems%22">Journal of Intelligent & Fuzzy Systems</searchLink>. 2018, Vol. 35 Issue 2, p1707-1720. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+software+costs%22">Computer software costs</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+algorithms%22">Evolutionary algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Estimation+theory%22">Estimation theory</searchLink><br /><searchLink fieldCode="DE" term="%22MatLab+%28Computer+software%29%22">MatLab (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Software cost estimation is the process of predicting the most realistic and valid amount of effort necessary for the development of any software. The cost estimation of any software is a difficult assignment due to the involvement of many factors that anyhow affect the estimation process. In literature, many cost estimation models have been developed for more than a decade to maintain accuracy in estimation of the cost of software projects. But, it is found that these models are inefficient to estimate the exact cost of software development because of uncertainties and lack of accuracy associated with them. In this paper, Alla F. Sheta models have been taken for optimization, which are the modified versions of the very famous Boehm’s COCOMO model. Parameters of the Sheta models have been tuned enough by the proposed method to estimate and minimize the consequences of different factors that affect the overall software development cost. Experimental work has been carried out in MATLAB environment and analysis of results is performed on the basis of Magnitude of Relative Error (MRE), Prediction (PRED) at 0.25, Value Accounted For (VAF) and Mean Magnitude of Relative Error (MMRE). Estimation accuracy of the proposed work is tested on NASA software project dataset. It is found that the proposed method shows good estimation capabilities over other state-of-the-art cost estimation models. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3233/JIFS-169707 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1707 Subjects: – SubjectFull: Computer software costs Type: general – SubjectFull: Evolutionary algorithms Type: general – SubjectFull: Estimation theory Type: general – SubjectFull: MatLab (Computer software) Type: general – SubjectFull: Mathematical optimization Type: general Titles: – TitleFull: Improved software cost estimation models: A new perspective based on evolution in Dynamic Environment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tripathi, Ashish – PersonEntity: Name: NameFull: Mishra, K.K. – PersonEntity: Name: NameFull: Tiwari, Shailesh – PersonEntity: Name: NameFull: Kumar, Naveen – PersonEntity: Name: NameFull: Trivedi, Munesh – PersonEntity: Name: NameFull: Kohle, Mohan L. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: 2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 10641246 Numbering: – Type: volume Value: 35 – Type: issue Value: 2 Titles: – TitleFull: Journal of Intelligent & Fuzzy Systems Type: main |
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