The Conference for Machine Learning Innovation

How are AI and ML helping to boost our agile development process

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Register until September 16:
✓Save up to $290
✓10% team discount
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Join the ML Revolution!
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Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
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✓10 % Team Discount
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Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
✓Save up to 500 €
✓10 % Team Discount
Register Now
Infos
Wednesday, November 23 2022
16:15 - 17:00
Room:
Stage 1

Current trends in software engineering are moving towards adopting agile software development practices. User stories are increasingly gaining a place in the software development process, especially in agile software development. User stories are the most widely used artifact in agile software development that express requirements from the user’s point of view. A user story is a semi-structured specification of requirements written in natural language.

The structure emphasizing the who, what and why of a requirement has become the de facto standard for capturing user stories. The rise of agile software development has attracted researchers and practitioners into this research field. User stories, as the most widely used artifact in agile software development, are challenging to explore. The fact that they are written in natural language makes them easily understandable to stakeholders. However, requirements written in natural language have drawbacks, such as ambiguity, inconsistency, and incompleteness. Natural language processing (NLP) techniques offer potential advantages to improve the quality of user stories. NLP can be used to parse, extract, or analyze user story data. It has been widely used to help in the software engineering domain (e.g., managing software requirements, extraction of actors and actions in requirement document, software feature extraction, software testing, etc.).

Some studies have used the NLP approach applied to user stories to accelerate the software requirements process. As a new research field, it is interesting to obtain a clear understanding of NLP research on the user story direction.

In my presentation I will share results of our developed tool using machine learning approach to support the user stories creation process. The tool help the author creating high quality stories, performing real-time analysis, testing and correlation from the text of user stories. The feedback provided by our tool will help the user to improve the wording used. It will achieve, clearer, concise, complete, consistent requirements. Focus first on Who and What, the tool generates and runs both static and dynamic tests against each user story, that will help find and warn the user of potential conflicts. The approach is evaluated on a set of user stories from real-world application. The results are promising and suggest that machine learning approaches can be beneficially applied to user story and agile development process.

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