Code review glossary

Each entry defines a code review term, says why it matters, and describes what Argus does for it, including where Argus does less than the term suggests.

• Code Review Automation

  Code review automation is the use of software tools to analyze, evaluate, and provide feedback on source code changes (typically pull requests) without requiring a human reviewer to manually inspect every line.

• Institutional Memory

  Institutional memory in code review is the accumulated knowledge of a codebase's past decisions, incidents, patterns, and architectural constraints, kept so that later reviews can apply it.

• PR Enrichment

  PR enrichment is the process of augmenting a pull request with context beyond the raw diff, such as architectural diagrams, dependency maps, risk assessments, and scenario analysis, so that reviewers have the information they need without manually tracing code paths.

• Code Simulation

  Code simulation means working out what a code change does under specific conditions, such as increased load, network failures, race conditions, or edge-case inputs.

• Architecture Tracing

  Architecture tracing is the analysis of how code changes propagate through a system's dependency graph — identifying which modules, services, and data flows are affected by a diff, and assessing the architectural risk of the change based on coupling, boundaries, and historical incident patterns.

• Dependency Graph

  A dependency graph is a directed graph representing the import and call relationships between modules in a codebase.

• Pattern Learning

  Pattern learning in code review is the ability of a review system to identify recurring code patterns, anti-patterns, and codebase-specific conventions from past reviews, and apply them in later reviews, so that fewer findings flag what the team does on purpose.

• Static Analysis

  Static analysis is the examination of source code without executing it, using rule-based pattern matching to detect known issues like security vulnerabilities, coding standard violations, and common bug patterns.

• Blast Radius

  Blast radius is a measure of how far the impact of a code change propagates through a system — how many modules, services, endpoints, and data flows are affected if the change introduces a defect.

• SAST (Static Application Security Testing)

  SAST is a category of security testing that analyzes source code, bytecode, or binaries for security vulnerabilities without executing the application.

• Tech Debt Tracking

  Tech debt tracking is the systematic identification, quantification, and monitoring of accumulated technical debt in a codebase: areas where expedient shortcuts were taken that will need refactoring later.

• Failure Scenario Testing

  Failure scenario testing is the practice of analyzing code changes by reasoning about what happens under adverse conditions (network timeouts, concurrent access, data corruption, resource exhaustion) rather than just the happy path.

• Cross-PR Analysis

  Cross-PR analysis is the practice of evaluating how multiple open or recent pull requests interact with each other — detecting conflicting changes, shared dependency modifications, and cumulative architectural drift that only becomes visible when you look across PRs rather than at each one in isolation.

• Review Fatigue

  Review fatigue is the decline in review quality that occurs when reviewers are overloaded with review requests — leading to rubber-stamp approvals, superficial comments, and missed defects.