Difference between revisions of "Requirements Management"
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* 2) How ChatGPT can help us build our own custom requirements template | * 2) How ChatGPT can help us build our own custom requirements template | ||
* 3) Other use cases of ChatGPT for business analysts | * 3) Other use cases of ChatGPT for business analysts | ||
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| + | <youtube>eu6pT-eNi-s</youtube> | ||
| + | <b>Analysis of Software Requirements with Natural Language Processing | ||
| + | </b><br>Prof. Lionel Briand University of Luxembourg, Luxembourg Huawei Workshop on Applications of Artificial Intelligence to Software Engineering December 15th 2017 | ||
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| + | <youtube>QRB_cs-Uh54</youtube> | ||
| + | <b>User Stories Using [[OpenAI]] [[ChatGPT]] (as a Business Analyst) | ||
| + | </b><br>Can OpenAI's ChatGPT produce requirements? The answer shocked me, and it will likely shock you. | ||
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| + | * Community • https://bablocks.com/membership/ | ||
| + | * Course • https://bablocks.com/bapc/ | ||
| + | * Podcast • https://bablocks.com/podcast/ | ||
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| + | <youtube>_bCMjacjSGQ</youtube> | ||
| + | <b>Analyzing the Entire Program: Applying Natural Language Processing to Software Engineering | ||
| + | </b><br>A powerful, but limited, way to view software is as source code alone. Mathematical techniques, such as abstract interpretation and model checking, can indicate whether the program satisfies a formal specification. But, where does the formal specification come from? A program consists of much more than a sequence of instructions. Developers make use of test cases, documentation, variable names, program structure, the version control repository, and more. I argue that it is time to take the blinders off of software analysis tools: tools should use all these artifacts to deduce more powerful and useful information about the program. Researchers are beginning to make progress towards this vision. In this talk, I will discuss four initial results that find bugs and generate code, by making use of variable names, error messages, procedure documentation, and user questions. | ||
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| + | <youtube>aB0tnT36UaI</youtube> | ||
| + | <b>Applying Machine Learning Techniques to the Flexible Assessment of Requirements Quality | ||
| + | </b><br>In the world of systems engineering, the importance of having high quality requirements is well known and that is why there are standards and guidelines that establish the characteristics that the requirements must have for considering them of good quality. To obtain quality measurements of the requirements it is common to use quantitative quality metrics based on established standards. However, the risk is to build assessment methods and tools that are both arbitrary and rigid in the parameterization and combination of metrics. This webinar is focused on the presentation of a flexible method to assess and improve the quality of requirements that can be easily adapted to different contexts, projects, organizations and quality standards, with a high degree of automation. In the method proposed, the domain experts contribute with an initial set of requirements that they have classified according to their quality, and their quality metrics are extracted. Then machine learning techniques are used to emulate the implicit expert’s quality function. A procedure to suggest least-effort improvements in bad requirements is also provided. The method is easily tailorable to different contexts, different styles to write requirements, and different demands in quality. The whole process of inferring and applying the quality rules adapted to each organization is highly automated. | ||
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Revision as of 12:06, 26 February 2023
Youtube search... ...Google search
- Case Studies
- Business Strategy/Consulting
- AI Governance
- Traditional Architecture
- Enterprise Portfolio Management (EPM)
- Architectures supporting machine learning
- AIOps / MLOps
- Assistants ... Hybrid Assistants ... Agents ... Negotiation
- Natural Language Processing (NLP) ...Generation ...LLM ...Tools & Services
- Application Development Trends - ADTmag
- Artificial Intelligence: The Bumpy Path Through Defense Acquisition | Eric J. Ehn
- AI driven requirements management ...IBM Engineering Lifecycle Management (ELM) | IBM
- Tools & Trends in Requirements Engineering | Hubert Spieß
- Why Agile Methodologies Miss The Mark For AI & ML Projects | Kathleen Walch - Forbes
- Managing workflow of customer requirements using machine learning | A. Lyutov, Y. Uyguna, and M. Thorsten Hütt - ScienceDirect
- reQlab | IT-Designers ...a state-of-the-art artificial intelligence tool improving natural language requirements. With its integration in Polarion, it can be used during the normal process of writing your requirements.
- Requirements Modeling Technology: A Vision For Better, Faster, And Cheaper Systems | Darrell Barker
- RE4AI ...motivating cross fertilization between AI and Requirements Engineering (RE)
- Defense: Requirements Development | DOD AcqNotes
Being semi-structured, requirements led themselves to Natural Language Processing (NLP) nicely.
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Requirements Management Tools
- The Best Requirements Management Tools Of 2020 | Ben Aston - dpm
- Artificial Intelligence & The Future Of Project Management (With Dennis Kayser From Forecast) | Ben Aston - dpm
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Discipline
(testable, cohesive, complete, consistent, atomic, traceable, unambiguous, prioritized, and solution-agnostic):
- 20+ Requirements Analysis Templates & Examples | Word Templates Onine
- Requirements Analysis Report | UVI, INESC, TUDA, UVA (lead), TANet, AZEV, ABB ...Adventure: The Plug-and-Play Virtual Factory
- User Requirements Analysis Report | D M Sergeant, S Andrews, and A Farquhar ...Embedding a VRE
The Expert
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