AI-Supported SDLC
From practice, I have come to understand that a large part of my creative activities can be generally described using the principles defined in the V-model. In practice, the term Software Development Life Cycle (SDLC) is now commonly used.
Another principle I have understood and explicitly work with is CAA – Context Aware Approach. There is no solution without multiple contexts. Understanding the key contexts has a fundamental impact on the outcome. At the same time, I am aware that there are contexts unknown to me that are of fundamental significance to any solution.
Even when writing this article, I followed these basic principles. The subject in my context for this article is testing AI-Kernaro.
My contexts are:
- Long-term knowledge of Sparx Systems technologies (25+ years) – Enterprise Architect, ProCloud Server, PROLABORATE
- Several years of experience with LieberLieber technology for Git support in parallel modelling – LemonTree
- Regular use of AI in professional and personal solutions across the SDLC
- Long-term personal experience across all SDLC phases: from business and top-level architecture (TOGAF) – concepts and purpose – through testing (ISTQB), operations, and change management (ITIL)
The image highlights the context-aware approach, the division of SDLC into individual phases, and the perspective of Sparx Systems technologies in supporting each phase.
This perspective also defined my testing strategy for AI-Kernaro, described in the next chapter.
Images
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