Using Data Envelopment Analysis in software development productivity measurement.
Saved in:
| Title: | Using Data Envelopment Analysis in software development productivity measurement. |
|---|---|
| Authors: | Asmild, Mette1, Paradi, Joseph C.2 paradi@mie.utoronto.ca, Kulkarni, Atin2 |
| Source: | Software Process: Improvement & Practice. Nov2006, Vol. 11 Issue 6, p561-572. 12p. 1 Diagram, 5 Charts. |
| Subjects: | Software engineering management, Computer software development, Financial institution software, Project evaluation, Project management, Data envelopment analysis, Regression analysis |
| Abstract: | The ever-increasing size and complexity of software systems make the cost of developing and maintaining software important. Unfortunately, the process of software production has not been particularly well understood. This article helps clarify the relationship between postimplementation function points (FP) and the corresponding development effort for software development projects in a large Canadian bank. Knowledge of this relationship enables evaluations of the productivity of completed projects and, in particular, provides a predictive tool for future projects. The empirical analysis employs a combination of traditional regression models and Data Envelopment Analysis (DEA). The regression analyses show a log-linear relationship between project size and development effort, which is subsequently used in the DEA models. The DEA models identify best performers and use these as benchmarks, but are not limited to the constant returns to scale assumption of the regression analyses and are capable of including the delivery time as a nondiscretionary input. Finally, by including data from the International Software Benchmarking Standards Group (ISBSG) repository in the DEA models, the bank's projects are benchmarked not only against its own best performers but also against what is globally feasible. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR] |
| Copyright of Software Process: Improvement & Practice is the property of Wiley-Blackwell 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 | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 23297849 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Using Data Envelopment Analysis in software development productivity measurement. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Asmild%2C+Mette%22">Asmild, Mette</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Paradi%2C+Joseph+C%2E%22">Paradi, Joseph C.</searchLink><relatesTo>2</relatesTo><i> paradi@mie.utoronto.ca</i><br /><searchLink fieldCode="AR" term="%22Kulkarni%2C+Atin%22">Kulkarni, Atin</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Software+Process%3A+Improvement+%26+Practice%22">Software Process: Improvement & Practice</searchLink>. Nov2006, Vol. 11 Issue 6, p561-572. 12p. 1 Diagram, 5 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Software+engineering+management%22">Software engineering management</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+development%22">Computer software development</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+institution+software%22">Financial institution software</searchLink><br /><searchLink fieldCode="DE" term="%22Project+evaluation%22">Project evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Project+management%22">Project management</searchLink><br /><searchLink fieldCode="DE" term="%22Data+envelopment+analysis%22">Data envelopment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The ever-increasing size and complexity of software systems make the cost of developing and maintaining software important. Unfortunately, the process of software production has not been particularly well understood. This article helps clarify the relationship between postimplementation function points (FP) and the corresponding development effort for software development projects in a large Canadian bank. Knowledge of this relationship enables evaluations of the productivity of completed projects and, in particular, provides a predictive tool for future projects. The empirical analysis employs a combination of traditional regression models and Data Envelopment Analysis (DEA). The regression analyses show a log-linear relationship between project size and development effort, which is subsequently used in the DEA models. The DEA models identify best performers and use these as benchmarks, but are not limited to the constant returns to scale assumption of the regression analyses and are capable of including the delivery time as a nondiscretionary input. Finally, by including data from the International Software Benchmarking Standards Group (ISBSG) repository in the DEA models, the bank's projects are benchmarked not only against its own best performers but also against what is globally feasible. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Software Process: Improvement & Practice is the property of Wiley-Blackwell 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=23297849 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/spip.298 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 561 Subjects: – SubjectFull: Software engineering management Type: general – SubjectFull: Computer software development Type: general – SubjectFull: Financial institution software Type: general – SubjectFull: Project evaluation Type: general – SubjectFull: Project management Type: general – SubjectFull: Data envelopment analysis Type: general – SubjectFull: Regression analysis Type: general Titles: – TitleFull: Using Data Envelopment Analysis in software development productivity measurement. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Asmild, Mette – PersonEntity: Name: NameFull: Paradi, Joseph C. – PersonEntity: Name: NameFull: Kulkarni, Atin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2006 Type: published Y: 2006 Identifiers: – Type: issn-print Value: 10774866 Numbering: – Type: volume Value: 11 – Type: issue Value: 6 Titles: – TitleFull: Software Process: Improvement & Practice Type: main |
| ResultId | 1 |
