An empirical study on the effect of programming languages on productivity

Background: Software development productivity is of great practical interest and has been widely investigated in the past. However, due to the rapid evolution of software development techniques and methods and the constant improvement in the use of existing ones, continuously updated evidence on productivity is constantly needed. Objectives: The research documented in this paper has the main goal to identify how different programming languages may affect productivity. Method: We analysed the ISBSG dataset, probably the largest public repository of data on software projects, with focus on the primary programming language used to develop each software project. We followed a rigorous statistical analysis approach. Moreover, we compared our analysis with the productivity data provided by Capers Jones in 1996 and 2013 and with an investigation on open-source software by Delorey et al. Results: The implementation programming language of software projects seems to affect productivity. The comparison between the productivity level of each of the analysed programming languages shows important differences with the results by Capers Jones and Delorey et al. Conclusions: This paper provides some more evidence about how each programming language has its own productivity level and highlights some interesting divergences with the results reported by Capers Jones and Delorey et al.