This paper introduces the automation of satisfaction assessment: the process of determining the satisfaction mapping of natural language textual requirements to natural language design elements. Satisfaction assessment is useful because it assists in discovering unsatisfied requirements early in the lifecycle when such issues can be corrected with lower cost and impact than later. We define the basic terms and concepts for this process and explore the feasibility of developing baseline methods for its automation. This paper describes the satisfaction assessment approach algorithmically and then evaluates the effectiveness of two proposed information retrieval (IR) methods in two industrial studies - one based on a large dataset including a complete requirements specification and design specification for a NASA science instrument, and one based on a smaller dataset for an open source project management dataset. We found that both approaches have merit, and that the more sophisticated approach outperformed the simpler approach in terms of overall accuracy of the results.


Computer Sciences

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