(M) Detection of Conflicting Requirements in Agile Development Projects

In the rapidly changing business world, agile software engineering methodologies have advanced the software development landscape by emphasizing flexibility, collaboration, and rapid response to change. However, the inherent dynamism of agile environments can cause requirements to change constantly, which can create conflicts between requirements, posing a considerable challenge to project success. However, rapid response to change also demands a rapid impact analysis (e.g., identifying requirements conflicts). This thesis topic explores the challenges of identifying conflicting requirements in agile software engineering environments and aims to gain insight into the automated detection and identification of conflicting requirements via Natural Language Processing (NLP) techniques. In particular, the use of the combination of the NLP techniques “Part-Of-Speech” and “Semantic Dependency Parsing” has achieved good results in recent research to identify semantic conflicts.

The aim of this thesis topic shall:

(a) survey the literature on NLP techniques using CoreNLP;

(b) select and evaluate at least two NLP techniques for their suitability and compatibility with agile software engineering

(c) and evaluate the selected NLP techniques using an example data set of user stories.

This thesis topic is suitable for Master students. The ideal student for this thesis topic has successfully completed the module SWT-FSE (agile methods & requirements analysis) and has a keen interest in requirements engineering, agile methods, and the machine learning technique of Natural Language Processing (NLP). Knowledge in Python would be advantageous. Missing knowledge in some areas or technologies can be acquired during the conduct of the thesis project.

1. Anand, R.V. and Dinakaran, M., 2017. Handling stakeholder conflict by agile requirement prioritization using Apriori technique. Computers & Electrical Engineering, 61, pp.126-136.
   
2. Elhassan, H., Abaker, M., Abdelmaboud, A. and Rehman, M.B., 2022. Requirements Engineering: Conflict Detection Automation Using Machine Learning. Intelligent Automation & Soft Computing, 33(1).
   
3. Gupta, A., Poels, G. and Bera, P., 2022. Using Conceptual Models in Agile Software Development: A Possible Solution to Requirements Engineering Challenges in Agile Projects. IEEE Access, 10, pp.119745-119766.
   
4. Guo, W., Zhang, L. and Lian, X., 2021. Automatically detecting the conflicts between software requirements based on finer semantic analysis. arXiv preprint arXiv:2103.02255.