The Structure of Design Theories, and an Analysis of their Use in Software Engineering Experiments

In this paper we analyse possible reasons for the relatively low use of theories in software engineering (SE) papers found by Hannay et al. [16]. We provide an initial explanation in terms of properties of theories, test this by analyzing 32 of the 40 theories reviewed by Hannay et al., and then revise our analysis based on this test. Our analysis revealed that background theories from other disciplines are context-free and make idealizing assumptions, which make it easier for them to be (re)used across settings. Theories built in SE are mid-range and context-sensitive, and make less idealizing assumptions. This is normal for engineering theories, but it does make them harder to (re)use across settings. We also found that background theories from other disciplines usually provide explanations for phenomena in terms of mechanisms, whereas SE theories are statistical models of phenomena observed in an experiment, which also makes them harder to (re)use across settings. We end the paper with a recommendation of bottom-up development of theories about mechanisms in software engineering projects by doing case studies.