Special Issue: Design Rationale

The process of designing can be viewed as making a series of design decisions. These decisions, the alternatives considered, the reasons for and against the decisions, and the dependencies among all of these form the rationale for the design. This design rationale provides a history of the design process as well as capturing the intent behind the decisions made. Design rationale has been an active area of research since the 1970s with the introduction of issue-based information systems (IBIS) as a means for representing argumentation-based rationale (Kunz & Rittel, 1970). Rationale research has been applied to many design disciplines including engineering design (Lee, 1997), human–computer interaction (Moran & Carroll, 1996), and software engineering (Dutoit et al., 2006)(Burge et al., 2008). Despite over 30 years of research, there are still few rationale systems used in practice. There is a strong consensus that rationale is very valuable, but there is an equally strong concern that the costs of its capture may be too high. In order to justify the costs of its capture, it is essential to establish ways in which rationale can be useful that exceed the simple provision of additional design documentation. The seven articles in this Special Issue address the usefulness of rationale. One article points out how much is still unknown about both the cost of capturing the rationale and how it can be most useful. It concludes that successful technology transfer cannot occur until more is known about where rationale is really needed and how well current approaches meet those needs. The remaining articles describe research into the uses of rationale that include capturing and maintaining design constraints, understanding existing designs, supporting design research, providing traceability for customer needs during the early design stage, capturing knowledge generated during building redesign, and supporting the reuse of highlevel software designs. These articles describe a wide spectrum of design rationale uses and methodologies in multiple domains and at multiple levels of formality. “Researching Under Uncertainty,” by Burge, describes the controversy over the usefulness of rationale versus the potential cost of its collection. The arguments both for and against rationale are presented along with a list of rationale approaches and how they were evaluated. Although there has been significant research activity proposing rationale approaches over the last 30 years, little data on the actual use and usefulness of rationale have been collected. The article also presents the results of a survey of software practitioners and their predictions of how rationale could be used. The results of this survey appear counterintuitive and indicate the need for more emphasis on gathering and reporting data on the uses for rationale and its usefulness. “Constraint Capture and Maintenance in Engineering Design,” by Ajit, Sleeman, Fowler, and Knott, tackles the important task of ensuring that designs are consistent with their specification and design rules defined by the organization developing the design. The relationship of the design rules to the problem can be defined as constraints. It is necessary to capture these constraints and to understand the conditions (assumptions and context) under which a constraint applies. These conditions form part of the rationale for the constraint. The methodology that is described supports constraint maintenance by detecting inconsistencies, subsumption, and redundancy as well as performing fusion between constraints and assisting with constraint refinement. “How to Evaluate Reading and Interpretation of Differently Structured Engineering Design Rationales,” by Aurisicchio, Gourtovaia, Bracewell, and Wallace, describes an empirical study on reading and interpreting technical documentation that is provided to aerospace trainees in a structured text format provided by DRed (using IBIS-style argumentation) and as unstructured text design definition reports. The article provides the results of this evaluation as well as a methodology for similar empirical tool evaluations. The experiment participants were provided with information in one of the two formats and asked a series of questions about it. The results indicate that the more structured DRed format has a positive impact on both the answers to the questions and the time required. Reprint requests to: Janet E. Burge, Computer Science and Systems Analysis Department, Miami University, Oxford, OH 45056, USA. E-mail: burgeje@muohio.edu Artificial Intelligence for Engineering Design, Analysis and Manufacturing (2008), 22, 309–310. Printed in the USA. Copyright # 2008 Cambridge University Press 0890-0604/08 $25.00 doi:10.1017/S0890060408000206