The stages in the above methodology should be expanded, which as i suggested, you can have AI do it for you. Note that you must be the "human-in-the-loop" and give the explicit go ahead after every stage i.e. checkpoint.
As part of your "Architectural Constraints", always list your specific libraries/frameworks/design patterns/code techniques that you are familiar with and want to be used while excluding everything else. For example you could say something like; "Do not use any design patterns outside of the GoF book", "Use <name> async framework only" etc. Guardrails are everything with AI.
The idea is that you should be able to read the generated code without too much difficulty.
Note that we are using DbC as one level of Formal Verification at runtime during development only. For verifying it statically we can have it mapped onto Lean4 (using tools) or to a SMT solver via SMT-LIB; see my comment here - https://news.ycombinator.com/item?id=50108112
The stages in the above methodology should be expanded, which as i suggested, you can have AI do it for you. Note that you must be the "human-in-the-loop" and give the explicit go ahead after every stage i.e. checkpoint.
As part of your "Architectural Constraints", always list your specific libraries/frameworks/design patterns/code techniques that you are familiar with and want to be used while excluding everything else. For example you could say something like; "Do not use any design patterns outside of the GoF book", "Use <name> async framework only" etc. Guardrails are everything with AI.
The idea is that you should be able to read the generated code without too much difficulty.
Note that we are using DbC as one level of Formal Verification at runtime during development only. For verifying it statically we can have it mapped onto Lean4 (using tools) or to a SMT solver via SMT-LIB; see my comment here - https://news.ycombinator.com/item?id=50108112
See also; Combining Tests and Proofs with Contracts for Better Software Verification by Bertrand Meyer et al. - https://dl.acm.org/doi/10.1145/3793869