Data Envelopment Analysis Journal, 2016, 2: 81–111 On the Use of DEA for Software Development Productivity Measurement Mette Asmild 1 and Francisco Imperatore 2 1 IFRO, University of Copenhagen, Denmark, meas@ifro.ku.dk 2 Pan American Energy, Argentina ABSTRACT This paper first, based on a thorough review of the relevant literature, provides a general discussion of some of the many aspects one should consider when using Data Envelopment Analysis (DEA) to measure the efficiency of software devel- opment. It then contains a case study which investigates a few of the important aspects. Finally it provides recommen- dations and directions for future research in the area. Rather than simply presenting a “final” set of results, the empirical study takes a step-by-step approach to considering, and thus illustrating, some of the issues to be aware of when doing empirical analysis, many of which are not limited to efficiency assessment of software development. Thus this paper, besides providing a thorough literature review and resulting guidelines specifically for the analysis of software development productivity, also aims at providing a practical “how to” guide for the empirical analysis that can be used more generally. In terms of actual empirical results, we find a clear indica- tion of variable returns to scale, of differences between new and evolutions developments and some indications of dif- ferences between programming languages. We also include potentially relevant variables such as requirements volatility, ISSN 2161-1823; DOI 10.1561/103.00000011 © 2016 M. Asmild and F. Imperatore