Code Metrics Tool

Code Metrics Tool analyzes codebases to quantify maintainability, complexity, and quality, helping developers and teams plan refactors and manage technical debt.

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About This Tool

The Code Metrics Tool analyzes a codebase to quantify structural quality using standard software metrics. It computes lines of code, function counts, cyclomatic complexity, dependencies, comment density, and Halstead-inspired indicators from a code snapshot or repository input. The output includes a 0–100 summary score plus interpretation, along with a per-file breakdown when provided.
Conceptually, it normalizes raw counts into interpretable indices, applies established formulas, and flags high-risk areas. Users supply required inputs (loc, functions, files) and optional per-file data; the tool aggregates into a summary score, a maintainability index, and a complexity index, with optional per-file data to guide refactoring.
Who benefits includes developers, team leads, architects, project managers, and QA engineers. Unique value lies in combining total and per-file metrics, language weighting, historical trend support, and flexible export formats. Common use cases are onboarding a new codebase, tracking debt across releases, and benchmarking teams. Core features include data ingestion, metric computation, normalization, threshold-based risk categorization, and API-ready payloads.
The tool emphasizes clarity and actionable guidance: it translates metric results into risk levels and prioritized hotspots, enabling focused improvements and faster decision cycles.

How to Use

  1. Provide inputs: loc, functions_count, files_count and optional per-file data.
  2. Choose mode (total or per-file) depending on data.
  3. Run calculation.
  4. Review outputs: summary_score, maintainability_index, complexity_index, risk_level, and per-file metrics.
  5. Export report if needed (JSON/CSV/PDF).
How to use code metrics tool

Frequently Asked Questions

Find Quick Answers

What metrics are computed?
The tool computes lines of code (LOC), function count, file count, cyclomatic complexity, dependencies, comment density, and Halstead-inspired indicators to derive summary_score, maintainability_index, complexity_index, and a risk level.
How should I interpret scores?
Maintainability index (MI) ranges: 85+ is excellent, 65–85 is good, below 65 indicates attention is needed. The summary_score reflects overall quality, balancing complexity, dependencies, and MI to highlight prioritized areas.
Can it handle multi-language repos?
Yes. The tool accepts language specification and can apply language-weighted inputs. It supports per-file metrics and aggregated counts, enabling cross-language comparisons and unified reporting.
Is per-file data required?
No. Per-file data is optional. If provided, per_file_metrics are included in the report and can refine the overall scoring and hotspot identification; otherwise, the tool returns aggregated metrics only.

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