Software requirement understanding using Pathfinder networks: discovering and evaluating mental models
Understanding and communicating user requirements in a software requirement analysis effort is very important. Misunderstandings of user requirements between software developers and users, will cause problems in terms of satisfying user needs, defects, cost and schedule during the software development process. This paper proposes a new technique that has the ability to represent the mental models of the user and developer communities as network representations using Pathfinder networks. Graphs (mental models) are generated for each of the user and developer groups and compared for similarities/dissimilarities using a graph similarity metric. This paper overviews how this technique is used to categorize requirements and to identify ambiguous and duplicate requirements. We also propose to extend this technique to enhance communication and reduce misunderstanding surrounding the user requirements during the requirement analysis phase.
pathfinder networks mental model software requirement analysis clustering proximity data correlation coefficient