When Natural Language Processing Jumps into Collaborative Software Engineering

Abstract

Software engineering is an intrinsically collaborative activity, especially in the era of Agile Software Development. Many actors are partaking in development activities, such that a common understanding should be reached at numerous stages during the overall development life-cycle. For a few years now, Natural Language Processing techniques have been employed either to extract key information from free-form text or to generate models from the analysis of text in order to ease the sharing of knowledge across all parties. A significant part of these approaches focuses on retrieving lost domain and architectural knowledge through the analysis of documents, issue management systems or other forms of knowledge management systems. However, these post-processing methods are time-consuming by nature since they require to invest significant resources into the validation of the extracted knowledge. In this paper, inspired by collaborative tools, bots and Natural Language extraction approaches, we envision new ways to collaboratively record and document design decisions as they are discussed. These decisions will be documented as they are taken and, for some of them, static or behavioural models may be generated on-the-fly. Such an interactive process will ensure everyone agrees on critical design aspects of the software. We believe development teams will benefit from this approach because manual encoding of design knowledge will be reduced and will not be pushed to a later stage, when not forgotten.