Great topic - and thanks for posting the video. There's a lot more to explore here, especially as we move to graphical requirements - not just a bunch of shall statements.
Dr. Carson went direct to the point: The great added value from AI would be to automatically extract the requirements from the architecture you are modelling. 🎯
Reverse engineering requirements is a useful capability. There are some limited capabilities to conduct quality assessments and refine requirements. There is still a need to generate requirements and specifications, which is within our reach. This is where we can introduce domain knowledge and mapping between component models for Persona, Profile, Preferences, Jobs, Outcomes, Processes, and Measures that are contextualized around scenarios. This is a very different approach than conventional document-centric business analysis and requirements capture. Then we can build forward and reverse engineering of requirements and systems engineering. As we shift towards synthetic systems and services to support dynamic adaptation of systems in the digital ecosystem, these capabilities will likely become mainstream in order to keep pace with change and ensure relevancy in the digital market of interoperable services and products.
Great topic - and thanks for posting the video. There's a lot more to explore here, especially as we move to graphical requirements - not just a bunch of shall statements.
Dr. Carson went direct to the point: The great added value from AI would be to automatically extract the requirements from the architecture you are modelling. 🎯
Wont it be solution oriented approach if we extract requirements from Architecture ? ( Interesting Perspective )
I see it as an iterative process.
Wow. Very good thought process :)
Would like to learn the advancements .
Reverse engineering requirements is a useful capability.
There are some limited capabilities to conduct quality assessments and refine requirements.
There is still a need to generate requirements and specifications, which is within our reach. This is where we can introduce domain knowledge and mapping between component models for Persona, Profile, Preferences, Jobs, Outcomes, Processes, and Measures that are contextualized around scenarios. This is a very different approach than conventional document-centric business analysis and requirements capture. Then we can build forward and reverse engineering of requirements and systems engineering. As we shift towards synthetic systems and services to support dynamic adaptation of systems in the digital ecosystem, these capabilities will likely become mainstream in order to keep pace with change and ensure relevancy in the digital market of interoperable services and products.