Investigating the effect of pair programming and software size on software quality and programmer productivity

• Main Author: Sison, Raymund
• Format: text
• Published: Animo Repository 2009
• Subjects: Computer software—Development; Computer software—Quality control; Computer Sciences; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/473; https://animorepository.dlsu.edu.ph/context/faculty_research/article/1472/type/native/viewcontent
• Institution: De La Salle University

Although pair programming has been studied since the late 1990s, it is only recently that the results of earlier studies are being fine-tuned. For example, the results of a 2007 study conducted in Europe suggests that although pair programming might not always increase software quality, it can do so when the software being built is relatively complex and junior developers are on the team. This paper describes two experiments involving the development of small systems (10,000 to less than 100,000 lines of code) and very small programs (less than 10,000 lines of code) by student programmers in an Asian university. The results involving the small systems, which were actually complete systems designed to support the Personal Software Process (PSP), showed that defect densities of systems written by the pair programming teams were significantly lower than those written by the teams that used the traditional approach of individual coding and testing of units, followed by integration testing. On the other hand, results involving the very small (and therefore much less complex) programs did not show any significant differences between the defect densities of the programs written by the pair programmers and of those written by the solo programmers, though they did show significantly greater productivity of the solo programmers when writing simpler code. The combined results of the two experiments suggest that pair programming might increase software quality without decreasing productivity when projects are sufficiently large (or complex) for the programmers working on them. © 2009 IEEE.