Introduction
Traditional code reviews are manual, inconsistent, and heavily depend on individual reviewer expertise. As projects scale — especially enterprise Angular front-end + .NET backend ecosystems — enforcing architectural rules, security standards, and naming conventions becomes increasingly difficult.
An Intelligent Code Review Engine solves this bottleneck by automatically analyzing code changes, detecting violations, predicting risk level, recommending fixes, and optionally applying auto-corrections.
This article walks through how to build such a system, from static analysis and AST-based rule engines to machine learning–based smell detection and CI integration.
Core goals
Enforce coding standards (naming, layering, import patterns, async/sync usage).
Detect architectural violations (feature boundaries, circular dependencies, incorrect service calls).
Identify anti-patterns (God components, duplicate code, deeply nested conditions, unused injections).
Provide suggested fixes—ideally auto-generated.
Integrate with CI to block risky merges or require approval.
High-level architecture
Developer IDE → Local Pre-Check (Plugin)
|
▼
Intelligent Review Engine
(Rule Engine + ML Model)
|
┌──────────────┴──────────────┐
│ Suggested Fixes │
│ Risk Score + Report │
└──────────────┬──────────────┘
|
CI/Git Hook
|
▼
Merge Allowed / Blocked
Main components
| Component | Responsibility |
|---|---|
| Parser layer | Converts source code to AST and dependency graphs |
| Static rule engine | Declarative rule checks (e.g., imports, naming, DI structure) |
| ML-based smell detection | Predicts maintainability, duplication, complexity, code smell probability |
| Auto-fixer | Suggests edits or generates patches |
| CI integration | Enforces thresholds |
Parsing and foundations
Angular parsing
Use
TypeScript Compiler API
ESLint AST (ESTree format)
Ts-morph for strongly typed traversal
Capture
Component metadata
Module structure and imports
Routing hierarchy
Dependency injection metadata
Template bindings (parse via Angular compiler AST)
.NET parsing
Use Roslyn
Get syntax trees
Semantic model
Symbols and type analysis
Dependency graph
Capture
Controller-to-service relationships
DTO layering rules
DI containers (Scrutor scanning, ServiceCollection extensions)
Rule types
1. Syntax-level rules (low complexity)
Examples
File naming conventions
Folder structure enforcement
Enum naming:
PascalCasePrivate fields:
_camelCaseNo inline anonymous functions longer than N lines
Output
❌ File "userService.ts" breaks naming rule. Expected: "user.service.ts"2. Dependency and architecture rules
Examples
Angular component cannot directly call HttpClient if a domain service exists
Shared module cannot depend on feature modules
No repository call allowed inside controllers—must go through service layer
No circular dependency:
ERROR: user.module ↔ profile.module circular reference detected.
Graph approach
Build directed dependency graph (file/package/module)
Detect disallowed edges or cycles
3. Pattern and anti-pattern detection
Large component (>300 lines) → suggest splitting
Service with >8 injected dependencies → smells like God Service
Too deep nesting → recommend refactor
Async calls without try/catch → mark as unsafe
Severity scored by risk model.
4. Security rules
Hardcoded secrets, tokens, endpoints
Unsafe query building (SQL injection risk)
Angular DomSanitizer misuse or missing sanitization
Authentication bypass in controller endpoint
JWT or cookie misconfiguration
Join the conversation! Your thoughts help the community grow.