What If People Learn Requirements Over Time? A Rough Introduction to Requirements Economics

The overall objective of Requirements Engineering is to specify, in a systematic way, a system that satisfies the expectations of its stakeholders. Despite tremendous effort in the field, recent studies demonstrate this is objective is not always achieved. In this paper, we discuss one particularly challenging factor to Requirements Engineering projects, namely the change of requirements. We proposes a rough discussion of how learning and time explain requirements changes, how it can be introduced as a key variable in the formulation of the Requirements Engineering Problem, and how this induces costs for a requirements engineering project. This leads to a new discipline of requirements economics

Influence of Context on Decision Making during Requirements Elicitation

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.Comment: 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