Course Objective & Scope
In growing codebases, high cyclomatic complexity, duplicated logic and undocumented side effects slow down feature delivery—yet asking an LLM to rewrite working code without a safety net invites regressions. This course combines objective static analysis with disciplined, test-backed AI refactoring.
Identifying hotspots via SonarQube/linter metrics and Git churn, mapping dependencies and side effects with LLMs, generating characterization tests before touching code, applying structured refactoring patterns with coding agents, and resolving N+1, memory and algorithmic bottlenecks are practised hands-on.
Who Should Attend?
- Software developers and senior engineers
- Tech leads and software architects
- Teams maintaining and evolving brownfield enterprise codebases
- Prerequisite: experience with object-oriented or functional programming and unit testing
Key Takeaways
- Prioritise high-impact technical debt by combining static complexity metrics with Git churn
- Map control flow, hidden state and side effects in undocumented modules using LLMs
- Generate characterization (golden master) tests that lock in current behaviour before refactoring
- Decompose large functions and god-classes in small, behaviour-preserving commits
- Fix database query, memory and concurrency bottlenecks backed by profiling evidence
Curriculum
Codebase Comprehension and Technical Debt Hotspots
- Selecting targets with cyclomatic/cognitive complexity, coupling and Git churn data
- Extracting call graphs and implicit business rules from unfamiliar code with LLMs
Code Smell Detection and Architectural Boundary Analysis
- Spotting god classes, long methods, primitive obsession and layer leaks
- Triaging static analysis findings (SonarQube, ESLint, Ruff, Roslyn) with AI
Building the Safety Net: Characterization Tests
- Generating snapshot and golden-master tests before touching untested legacy code
- Locking in edge cases and existing error behaviours
Step-by-Step Behaviour-Preserving Refactoring
- Extract method/class, guard clauses, strategy patterns and isolating pure functions
- Keeping structural refactoring commits strictly separate from behaviour changes
Performance Analysis and Resource Optimisation
- Identifying N+1 ORM queries, redundant serialisation, memory leaks and async blocking
- Before/after benchmarking and regression-free delivery
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