TY - JOUR

T1 - Using data envelopment analysis in software development productivity measurement

AU - Asmild, Mette

AU - Paradi, Joseph C.

AU - Kulkarni, Atin

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

KW - Bank

KW - Data envelopment analysis (DEA)

KW - Development effort

KW - Function points

KW - Productivity

KW - Software development

U2 - 10.1002/spip.298

DO - 10.1002/spip.298

M3 - Journal article

AN - SCOPUS:33845952862

VL - 11

SP - 561

EP - 572

JO - Software Process Improvement and Practice

JF - Software Process Improvement and Practice

SN - 1077-4866

IS - 6

ER -