Tool for Generating Behavior-Driven Development Test-Cases

Raharjana, Indra Kharisma; Harris, Fadel; Justitia, Army

doi:10.20473/jisebi.6.1.27-36

Cited by 14 publications

(5 citation statements)

References 17 publications

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“…A user story is a short, semi-structured sentence that illustrates requirements from the user's perspective. A user story can be used to explain user desire or product description [14]. It consists of three aspects, namely aspects of who, what, and why.…”

Section: User Story and Nlpmentioning

confidence: 99%

User Stories and Natural Language Processing: A Systematic Literature Review

2021

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User stories have been widely accepted as artifacts to capture the user requirements in agile software development. They are short pieces of texts in a semi-structured format that express requirements. Natural language processing (NLP) techniques offer a potential advantage in user story applications. Objective: Conduct a systematic literature review to capture the current state-of-the-art of NLP research on user stories. Method: The search strategy is used to obtain relevant papers from SCOPUS, ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar. Inclusion and exclusion criteria are applied to filter the search results. We also use the forward and backward snowballing techniques to obtain more comprehensive results. Results: The search results identified 718 papers published between January 2009 to December 2020. After applying the inclusion/exclusion criteria and the snowballing technique, we identified 38 primary studies that discuss NLP techniques in user stories. Most studies used NLP techniques to extract aspects of who, what, and why from user stories. The purpose of NLP studies in user stories is broad, ranging from discovering defects, generating software artifacts, identifying the key abstraction of user stories, and tracing links between model and user stories. Conclusion: NLP can help system analysts manage user stories. Implementing NLP in user stories has many opportunities and challenges. Considering the exploration of NLP techniques and rigorous evaluation methods is required to obtain quality research. As with NLP research in general, the ability to understand a sentence's context continues to be a challenge.

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Section: User Story and Nlpmentioning

confidence: 99%

User Stories and Natural Language Processing: A Systematic Literature Review

2021

Self Cite

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“…To clearly illustrate the features of developing software systems and minimize the ambiguity between the requirement specifications and the design, UML models are widely used in the software design phase. By involving users, a software system's blueprint enables developers to avoid misunderstandings regarding software development [2]. Before developing any software, system requirements engineering is the preliminary step to collecting all the business requirements from the stakeholders [3].…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

Molla,

Ahmad,

Wan Kadir

2024

Int J Innov Comp

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Software development life cycle is a continuous process for every developer community, including establishing the user requirements and system design until software maintenance. The system design phase contains the transformation of all-natural language requirements into models. The Unified Modelling Language (UML) use case model is regarded as one of the most helpful diagrams for a software developer to understand the higher version of the software blueprint. It’s very useful to reflects the business requirements for any proposed software system. Manual analysis requires significant time and effort, highlighting the need for automated assistance. This study aims to enhance the machine learning techniques that have been utilized to transform user stories and functional requirements into a UML use case diagram. This research also investigate the use of an automated Natural Language Processing (NLP) tool and framework for mapping use case diagram elements from user stories and functional requirements written in natural languages. The proposed approach using a NLP based machine learning framework called BERT to predict and extract actors, use cases, and the relationship between actors and use cases. This approach has been applicable for both user stories and functional requirements. A dataset has been pre-processed in order to train this model and collected from various sources like Kaggle, software projects. There are 11 user stories and 11 functional requirements were selected to test the proposed solution. The data set from benchmark repositories. The extracted results during the whole NLP process are then mapped into actors, use cases, and relationships. This study was evaluated using both accuracy and precision values for performance measures. By applying NLP technologies, this research offers complete support for extracting elements and generating a use case diagram and revealed the 88% accuracy and 88% precision.

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“…Around 90% of agile practitioners implement user stories as their method to elicit requirements for their software [5], [6], [7]. User stories can also be used as the basis for test cases in software testing processes [8]- [10]. Acceptance criteria assigned to user stories are used as test cases and merged into acceptance tests, which will then be used to check the system behavior compliance with the user stories [11].…”

Section: Introductionmentioning

confidence: 99%

Conversion of User Story Scenarios to Python-Based Selenium Source Code for Automated Testing

et al. 2023

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A user story is an artifact in software development processes that can be used for automated test cases. This study proposes a terminal-based program for converting user stories into source codes for automated testing. We also propose a modified user story format that can be directly converted into functional Python-based Selenium source codes. We then implement the program by creating user stories for several local Django projects and using the converted codes. The implementation results show that the code from the program has a reliability rate of 72% for successfully executing it as the users' intentions.

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Tool for Generating Behavior-Driven Development Test-Cases

Cited by 14 publications

References 17 publications

User Stories and Natural Language Processing: A Systematic Literature Review

User Stories and Natural Language Processing: A Systematic Literature Review

A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

Conversion of User Story Scenarios to Python-Based Selenium Source Code for Automated Testing

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