System assessment and decision support
Code Forensic Assessment for established .NET systems
When a technical assessment helps before stabilization, what information it requires, and how it produces a report, review meeting, and improvement roadmap.
The short answer
The Code Forensic Assessment is useful for a business-critical .NET system that has evolved over years when release risks, dependencies, or technical hotspots need a sound assessment before an investment decision.
The paid analysis takes 2–3 days. It combines Git history, code metrics, and bug metrics with data science methods and my experience. The deliverables are a report, a review meeting, and an improvement roadmap.
Decision context
The assessment establishes a shared technical baseline before a team budgets or implements measures. It shows which findings should be clarified first and which work belongs in a bounded stabilization project.
The analysis does not replace implementation planning for a large project that has already been approved. It supports a decision when the scope, sequence, and expected benefit of technical measures are not yet sufficiently clear.
Signals in day-to-day operation
- Releases take a long time, require many manual steps, or are difficult to plan.
- The technical risks of a change only become visible in the build, during deployment, or in operation.
- The team can no longer fully trace dependencies, concurrency behavior, or responsibilities in the code.
- Known problems compete for budget, but there is no reasoned order for addressing them.
- An independent technical assessment is needed before stabilization or modernization.
Data and prerequisites
- Access to the repositories agreed in advance. The Standard package covers up to three repositories; Full Forensic covers up to ten.
- Build information and relevant logs where they are needed for the agreed questions.
- People who can explain current problems, release history, and known dependencies during the kickoff.
- Access to the production environment is not required. Open technical questions are clarified with the responsible team.
A step-by-step approach
- The kickoff defines the system, current problems, release history, repository scope, and available information.
- The deep analysis combines evidence from Git history, code metrics, and bug metrics with data science methods and my experience.
- Current failures and issues, the biggest risks, and the strongest opportunities for improvement are assessed with clear reasoning.
- You receive the report and improvement roadmap. In a review meeting, we discuss the overall picture and every prioritized item.
Outcome of the analysis
- Report with the findings from the deep, data-driven analysis.
- Review meeting covering failures, issues, risks, and opportunities for improvement.
- Improvement roadmap with prioritized next steps.
- Clear overall understanding of the system for technical and business decisions.
Limits and boundaries
- The assessment ends with analysis and prioritization. Implementation of the measures is a separate stabilization project.
- A time-boxed analysis cannot guarantee that it will find every technical risk in a system.
- Greenfield projects, new builds, and systems outside the .NET ecosystem are outside the described scope.
- The assessment reviews the agreed existing system. Comprehensive modernization is planned only after findings, objectives, and constraints are sufficiently clear.
Questions to check
- The main technical questions and the reason for the assessment are stated.
- The repositories to be reviewed are defined.
- Build information and relevant logs are available.
- A person familiar with the release history and known dependencies attends the kickoff.
- Confidentiality and technical access are clarified before the work starts.
- The recipients of the report and improvement roadmap are known.
Sources and context
The sources support the technical context or define the scope of a related service. Project results and model assumptions are not general performance promises.