current-distortion

To detect code distortions in legacy repositories, run a two-phase workflow that collects risks and generates a structured Part A/B/C Markdown report. This process identifies root causes and maps remediation ideas across multi-repo projects.

Cross-repo risk patterns P1-P11 and root-cause mappings A-E are structured classifications used to identify governance and design flaws across service boundaries. They guide the consolidation of distortion findings into a unified remediation report.

Generating a structured distortion report involves running Phase 1 to collect risks across target repositories, then executing Phase 2 to consolidate findings into a unified Part A/B/C Markdown report. This surfaces root causes and remediation strategies.

Yes, distortion analysis is applicable across multi-repository projects and cross-service boundaries. It reveals governance and design flaws by relying on business-process mappings and risk patterns to surface underlying root causes.

The workflow for identifying legacy code distortions enforces a two-phase process using business-process mappings and risk patterns. It consolidates findings into a Part A/B/C report to reveal root causes and guide remediation planning.

You need a structured risk analysis report when dealing with legacy code across multiple repositories to enable structured decision-making. It organizes lurking risks and maps root causes to guide remediation planning across services.