hos-silly-mock-001

Detect unannotated mock data in AI generated TypeScript by applying static analysis to enforce explicit mock annotations and verify source-transform-sink data binding. The engine outputs a reality score indicating code authenticity.

Regex for JSON parsing creates silent failure patterns by bypassing structural validation and error handling, resulting in unbound data variables. Detecting this regex abuse requires static analysis enforcing standard parsers to guarantee complete data binding.

Yes, reality scoring functions as a CI/CD quality gate for JavaScript. The engine generates a 0-100 score with configurable thresholds for development, pre-production, and production environments to block unmaintainable code from deployment.

A reality score threshold is a configurable 0-100 metric evaluating AI code authenticity in quality checks. It measures explicit mock data annotations, standard parser usage, and complete data binding to detect fake, non-functional systems.

Mock data detection works by identifying unannotated mock data patterns, explicitly flagging code lacking proper annotations. It enforces explicit mock data annotations to verify source-transform-sink data binding and prevent fake systems.

A limitation of static analysis for preventing silent failure patterns is its reliance on enforcing source-transform-sink data binding and standard parser usage without runtime execution. It generates a reality score to gate code but cannot catch dynamic execution errors.