We continue to struggle with a community consensus on appropriate research methodology. Without such a consensus, there remains a problem in assessing papers, research proposals, and research programs. We discuss a recent paper by Cohen AI magazine 121, 1991, pp 16 41 which analyzed research methods in AI. Cohen concludes that there are two methodologies in use in AI system-centered and model-centered and that neither alone is su cient to meet the goals of AI research. The lessons to be learned

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... for SE research include to carefully specify the problem being addressed and the assumptions and environment"; state hypotheses; provide methods used to address the problem; validate the hypotheses; and suggest or indicate what changes or modi cations are necessary for future research. In an NSF-sponsored workshop held in 1989, four methodologies were identi ed. The scienti c method: observe the world, propose a model or theory of behavior, measure and analyze, validate hypotheses of the model or theory, and if possible repeat; the engineering method evolutionary paradigm: observe existing solutions, propose better solutions, build or develop, measure and analyze, repeat until no further improvements are possible; the empirical method revolutionary paradigm: propose a model, develop statistical or other methods, apply to case studies, measure and analyze, validate the model, repeat; the analytical method: propose a formal theory or set of axioms, develop a theory, derive results and if possible compare with empirical observations. How these methodologies might be employed in SE research is discussed.