Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact Three recent exemplars in the research literature are used to demonstrate the application of these guidelines We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community

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Design science in information systems research

Almost every expert in Object-Oriented Development stresses the importance of iterative development. As you proceed with the iterative development, you need to add function to the existing code base. If you are really lucky that code base is structured just right to support the new function while still preserving its design integrity. Of course most of the time we are not lucky, the code does not quite fit what we want to do. You could just add the function on top of the code base. But soon this leads to applying patch upon patch making your system more complex than it needs to be. This complexity leads to bugs, and cripples your productivity.

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Refactoring: Improving the Design of Existing Code

Research in IT must address the design tasks faced by practitioners. Real problems must be properly conceptualized and represented, appropriate techniques for their solution must be constructed, and solutions must be implemented and evaluated using appropriate criteria. If significant progress is to be made, IT research must also develop an understanding of how and why IT systems work or do not work. Such an understanding must tie together natural laws governing IT systems with natural laws governing the environments in which they operate. This paper presents a two dimensional framework for research in information technology. The first dimension is based on broad types of design and natural science research activities: build, evaluate, theorize, and justify. The second dimension is based on broad types of outputs produced by design research: representational constructs, models, methods, and instantiations. We argue that both design science and natural science activities are needed to insure that IT research is both relevant and effective.

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Design and natural science research on information technology

http://www3.cis.gsu.edu/vvaishnavi/9220Sp07/Documents/March%20Smith%20DSS%201995.pdf

Invited Paper Design and natural science research on information technology

The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three of these problems—the thin spread of application domain knowledge, fluctuating and conflicting requirements, and communication bottlenecks and breakdowns—affected software productivity and quality through their impact on cognitive, social, and organizational processes.

http://www.cs.rug.nl/search/uploads/Teaching/RE2009Fall/paper/1988_Curtis_ACMC_A%20Field%20Study%20of%20the%20Software%20Design%20Process%20for%20Large%20Systems.pdf

A field study of the software design process for large systems

But, as we look to the horizon of a decade hence, we see no silver bullet. There is no single development, in either technology or in management technique, that by itself promises even one order-of-magnitude improvement in productivity, in reliability, in simplicity. In this article, I shall try to show why, by examining both the nature of the software problem and the properties of the bullets proposed.

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Brooks

Papers

No Silver Bullet Essence and Accidents of Software Engineering