IFPUG Function Points to COSMIC Function Points convertibility: A fine-grained statistical approach.
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| Title: | IFPUG Function Points to COSMIC Function Points convertibility: A fine-grained statistical approach. |
|---|---|
| Authors: | Abualkishik, Abedallah Zaid1 azasoft1@gmail.com, Lavazza, Luigi2 luigi.lavazza@uninsubria.it |
| Source: | Information & Software Technology. May2018, Vol. 97, p179-191. 13p. |
| Subjects: | Function point analysis, Regression analysis, Computer software development, Machine learning, International Function Point Users Group (Organization) |
| Abstract: | Background Functional size measurement is widely used in software organizations because it supports the estimation of software development effort. Function Point Analysis was the first functional size measurement method and became quite popular. The COSMIC method is considered a second-generation method, due to its novel design, and has also gained wide acceptance. Since the proposal of the COSMIC method, the measure convertibility issue arose. Many studies have investigated this issue: several conversion techniques have been proposed and their accuracy has been evaluated through empirical studies. Objective The goal of the paper is to explore statistic conversion criteria that leverage the similarity between the Base Functional Components of the considered functional measurement methods, especially concerning elementary processes and functional processes. Method Statistical models of the relationship between the considered measures were built, using Least Median of Squares linear regression. The models use measures of Function Point Analysis Base Functional Components and COSMIC Base Functional Components as independent and dependent variables, respectively. Accuracy of conversion was assessed via leave-one-out cross validation. Results The proposed method was tested on three datasets, and was compared with other conversion methods. The proposed method achieved results that are never less accurate – and sometimes much more accurate – than alternative methods’. Conclusions The proposed method requires that when traditional Function Points are measured, information concerning Base Functional Components are recorded. If such information is available, the proposed approach is – according to the collected evidence – preferable to other conversion methods, with respect to both the effort required to obtain the results and their accuracy. [ABSTRACT FROM AUTHOR] |
| Copyright of Information & Software Technology is the property of Elsevier B.V. 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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 128347986 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: IFPUG Function Points to COSMIC Function Points convertibility: A fine-grained statistical approach. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Abualkishik%2C+Abedallah+Zaid%22">Abualkishik, Abedallah Zaid</searchLink><relatesTo>1</relatesTo><i> azasoft1@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Lavazza%2C+Luigi%22">Lavazza, Luigi</searchLink><relatesTo>2</relatesTo><i> luigi.lavazza@uninsubria.it</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Information+%26+Software+Technology%22">Information & Software Technology</searchLink>. May2018, Vol. 97, p179-191. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Function+point+analysis%22">Function point analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+development%22">Computer software development</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22International+Function+Point+Users+Group+%28Organization%29%22">International Function Point Users Group (Organization)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Background Functional size measurement is widely used in software organizations because it supports the estimation of software development effort. Function Point Analysis was the first functional size measurement method and became quite popular. The COSMIC method is considered a second-generation method, due to its novel design, and has also gained wide acceptance. Since the proposal of the COSMIC method, the measure convertibility issue arose. Many studies have investigated this issue: several conversion techniques have been proposed and their accuracy has been evaluated through empirical studies. Objective The goal of the paper is to explore statistic conversion criteria that leverage the similarity between the Base Functional Components of the considered functional measurement methods, especially concerning elementary processes and functional processes. Method Statistical models of the relationship between the considered measures were built, using Least Median of Squares linear regression. The models use measures of Function Point Analysis Base Functional Components and COSMIC Base Functional Components as independent and dependent variables, respectively. Accuracy of conversion was assessed via leave-one-out cross validation. Results The proposed method was tested on three datasets, and was compared with other conversion methods. The proposed method achieved results that are never less accurate – and sometimes much more accurate – than alternative methods’. Conclusions The proposed method requires that when traditional Function Points are measured, information concerning Base Functional Components are recorded. If such information is available, the proposed approach is – according to the collected evidence – preferable to other conversion methods, with respect to both the effort required to obtain the results and their accuracy. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Information & Software Technology is the property of Elsevier B.V. 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: 10.1016/j.infsof.2018.01.012 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 179 Subjects: – SubjectFull: Function point analysis Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Computer software development Type: general – SubjectFull: Machine learning Type: general – SubjectFull: International Function Point Users Group (Organization) Type: general Titles: – TitleFull: IFPUG Function Points to COSMIC Function Points convertibility: A fine-grained statistical approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abualkishik, Abedallah Zaid – PersonEntity: Name: NameFull: Lavazza, Luigi IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 09505849 Numbering: – Type: volume Value: 97 Titles: – TitleFull: Information & Software Technology Type: main |
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