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docs(readme): readme update

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Emily Boudreaux
2026-03-24 13:24:01 -04:00
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@@ -35,15 +35,12 @@ Strata supports the refinement of the call graph through three primary filtering
This software was constructed through iterative interactions with a generative artificial intelligence coding assistant. It serves primarily as an experimental test case for the author to evaluate the feasibility of AI-driven software engineering in systems tooling.
### User Directions Provided
The generative model was directed initially by a comprehensive requirements document outlining the functional goals, core design principles, parsing strategies, designated modes of output, filtering semantics, and the underlying mathematical graph specification. Subsequent interactive instructions included verbatim:
1. "I want to be able to do something like collapse all mfem related tools (things built into mfem down). Im not sure the best way to do this but basically this tool is supposed to help me optimize my code which uses mfem, its useful for me to see where I call mfem but I do not need to see the calls mfem makes internally."
2. "okay and now can I do something like cargo install and then use strata anywhere on my computer?"
3. "okay now please write a detailed README. prioriatize professionallism and an academic voice. Do not use emojis or hype language. Make it clear that this program was developed with the assistance of generative AI, document all the instructions I gave you in the readme. Note down the pitfalls of generative AI code and comment on how this code was generateed as a test case for myself and users should use with caution."
The generative model was directed initially by a comprehensive requirements document outlining the functional goals, core design principles, parsing strategies, designated modes of output, filtering semantics, and the underlying mathematical graph specification.
### Cautions Regarding Generative AI Software
As an artifact of generative artificial intelligence, this codebase is subject to several known pitfalls inherent to large language models in software engineering:
- **Latent Edge Cases:** The parser may harbor undocumented assumptions regarding the formatting of the input data (e.g., rigid reliance on semicolon strings or backtick delimiters) which could fail abruptly under slightly heterogeneous logging schemas.
- **Architectural Brittle States:** While functionally demonstrative under tested constraints, AI-generated code occasionally lacks the cohesive architectural foresight necessary for long-term maintainability or seamless extensibility.
- **Architectural Brittle States:** While functionally demonstrative under tested constraints, AI-generated code often lacks the cohesive architectural foresight necessary for long-term maintainability or seamless extensibility.
- **Silent Failures:** Generative integrations may adopt error handling strategies that silently discard malformed data or default to unanticipated fallback states without emitting sufficient diagnostic warnings to the operator.
Consequently, this utility is provided strictly "as-is." Prospective users are urged to exercise due diligence, thoroughly review the source code logic, and apply critical caution when trusting the aggregated profile data generated by this tool in complex production environments.