Limitations of Current Syntactic Analysis Models for User Stories: A Systematic Literature Review Protocol

Muhammad Arif; Huma Hayat Khan; Nagis Fatima

Authors

Muhammad Arif Department of Software Engineering, National University of Modern Languages, Islamabad, Pakistan
Huma Hayat Khan Department of Software Engineering, National University of Modern Languages, Islamabad, Pakistan
Nagis Fatima Department of Software Engineering, National University of Modern Languages, Islamabad, Pakistan

Keywords:

User Stories, Syntactic Analysis, Natural Language Processing, Large language Models, Fine Tuning

Abstract

User stories serve as the backbone of Agile software development. User stories simply provide an understanding about the user requirements, such that what actually user need to perform a specific task. However stating user stories is not always as per the benchmark format and the frequent changes in the user needs also effect the user stories to be changed frequently. Thus there is the problem to correctly identify the structural elements of the user stories. In this context traditional models as well as large language models can be utilized to analyze user stories for their constituents. Thus the aim of this study is to provide a comprehensive protocol to conduct a systematic literature review which identify the limitation of current syntactic analysis models and also come up with the fine tuning techniques which can overcome the identified limitations.

Author Biographies

Huma Hayat Khan, Department of Software Engineering, National University of Modern Languages, Islamabad, Pakistan

Department: Software Engineering

Rank: Assistant Professor

Nagis Fatima, Department of Software Engineering, National University of Modern Languages, Islamabad, Pakistan

Department: Software Engineering

Rank: Assistant Professor

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