2012/10/26 by Corentin Burnay, Burnay, Corentin, Ivan Jureta +3
Computer Science · Decision Sciences · #AI-based Problem Solving and Planning #Data Quality and Management #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Software Engineering (cs.SE) #cs.LO #cs.SE
paper · pdf · doi:10.48550/arxiv.1210.7101
appears in Proceedings of the 4th International Workshop on Acquisition, Representation and Reasoning with Contextualized Knowledge (ARCOE), 2012, Montpellier, France, held at the European Conference on Artificial Intelligence (ECAI-12)
openalex publication_date 2012/10/26 · arxiv created 2012/10/29 · arxiv updated 2012/10/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Requirements engineers should strive to get a better insight into decision making processes. During elicitation of requirements, decision making influences how stakeholders communicate with engineers, thereby affecting the engineers' understanding of requirements for the future information system. Empirical studies issued from Artificial Intelligence offer an adequate groundwork to understand how decision making is influenced by some particular contextual factors. However, no research has gone into the validation of such empirical studies in the process of collecting needs of the future system's users. As an answer, the paper empirically studies factors, initially identified by AI literature, that influence decision making and communication during requirements elicitation. We argue that the context's structure of the decision should be considered as a cornerstone to adequately study how stakeholders decide to communicate or not a requirement. The paper proposes a context framework to categorize former factors into specific families, and support the engineers during the elicitation process.