DPMS プロジェクト: Detection of problems and missing stakeholders during software development meetings


Exploring cognitive modeling for communication analysis in software meetings


Our research is concerning two domains, requirement engineering and cognitive science. In requirement engineering, there are inherently many problems and challenges to elicit requirements during software development meetings. Some of the challenges are identifying problematic situations and topics (lack of consensus), and missing stakeholders. The identifications are very important because elicitation activity is often regarded as the first step in requirement engineering. Moreover, the IEEE Standard 830 gives a summary of the properties that should ideally be part of software requirement specification: correct, unambiguous, complete and consistent. For example, any identification processes that mistakenly recognize someone as a stakeholder will probably include requirements, which do not correspond to any real need (a feature of ‘Correctness’ of the standard). On the other hand, when the identification task fails to detect participants who are needed (someone is missing) for the software project, requirement specifications are no longer ‘Complete’ due to the omission of relevant requirement specifications, and this could give rise to inconsistent specifications. However, given that the nature of software meetings are prone to changes, the meetings itself can be ill-structured. Hence making the identification process tedious and implicit. There has not been any method (yet) that focuses on structuring the observed meetings to detect problematic situations and topics, for enabling the identification of missing stakeholders. Our research proposal is to explore how we can use basic ideas from cognition theories to solve the problems in detecting consensus and missing stakeholders. Specifically we are investigating the use of ‘cognitive processes’ and modeling them as ‘operators’ to reduce the complexity of implementation. The operators are modeled in a communication analysis model enabling the structuring at a contextualized level about: (i) who has said what (topics), (ii) in which situations where problematic topics pertain or might arise, (iii) who is doing what (task role), before systematically identifying who should have said more about ‘what’ (i.e., who is missing)? The expected result from our research is a simple visualization system for project managers allowing them to detect the lack on consensus and missing stakeholders.


National Institute of Informatics : Nik Nailah Binti Abodullah, Shinichi Honiden, Eric Platon
The Open University : Bashar Nuseibeh
Nihon Unisys : Toshihiko Tsumaki