Visible to the public Agile Release Planning Using Natural Language Processing Algorithm

TitleAgile Release Planning Using Natural Language Processing Algorithm
Publication TypeConference Paper
Year of Publication2019
AuthorsSharma, Sarika, Kumar, Deepak
Conference Name2019 Amity International Conference on Artificial Intelligence (AICAI)
Keywordsagile methodology, agile release planning, Algorithm, complex software engineering projects, Currencies, Human Behavior, Java, Java utility, JIRA, natural language processing, natural language processing algorithm, Planning, project management, project release, provided user stories, pubcrawl, R Programming, Rally, Release Planning, Resiliency, RV coefficient NLP algorithm, Scalability, similar user stories, Software, Software algorithms, software development management, software engineering, software prototyping, team working, user story, word corpus
AbstractOnce the requirement is gathered in agile, it is broken down into smaller pre-defined format called user stories. These user stories are then scoped in various sprint releases and delivered accordingly. Release planning in Agile becomes challenging when the number of user stories goes up in hundreds. In such scenarios it is very difficult to manually identify similar user stories and package them together into a release. Hence, this paper suggests application of natural language processing algorithms for identifying similar user stories and then scoping them into a release This paper takes the approach to build a word corpus for every project release identified in the project and then to convert the provided user stories into a vector of string using Java utility for calculating top 3 most occurring words from the given project corpus in a user story. Once all the user stories are represented as vector array then by using RV coefficient NLP algorithm the user stories are clustered into various releases of the software project. Using the proposed approach, the release planning for large and complex software engineering projects can be simplified resulting into efficient planning in less time. The automated commercial tools like JIRA and Rally can be enhanced to include suggested algorithms for managing release planning in Agile.
DOI10.1109/AICAI.2019.8701252
Citation Keysharma_agile_2019