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For software designers to effectively collaborate, they must share an understanding of how software design artifacts contribute to the execution of software processes (the artifact’s operational meaning). However, during design, artifact descriptions often lack sufficient detail to unequivocally establish operational meaning. This is because during design, artifact descriptions are initially usually first-cut, and are then successively refined to include additional design details, until the operational meaning of artifacts can be unequivocally demonstrated. Ensuring shared meaning in larger projects is particularly difficult because of the plethora of interrelated artifacts designers deal with, and because the design details in descriptions of different artifacts can vary greatly. In this paper we argue that a semiotic meaning analysis supports clarifying the operational meaning of artifacts during software design, and can help in identifying whether and in what way artifact descriptions must be further elaborated. We further argue that clarifying the operational meaning of artifacts is closely intertwined with design decision-making. Adapting an existing semiotic agent modelling approach, we propose an approach to capturing the evolving operational meaning of artifacts during software design and decision processes, and illustrate the approach with examples taken from a large design project at an insurance company.

RESOLVING ARTIFACT DESCRIPTION AMBIGUITIES DURING SOFTWARE DESIGN USING SEMIOTIC AGENT MODELLING