Qualitas

A next generation code quality measurement tool that actually works. It measures code quality across five research-backed pillars and returns a single 0–100 Quality Score to guide the health of your code base. It supports TypeScript/JavaScript, Rust, Python, Go, and Java out of the box. The core is written in Rust using oxc_parser and tree-sitter for native-speed analysis, distributed as a native npm package via napi-rs, and provides both a programmatic TypeScript API and a CLI binary for ease of use.

Cognitive Complexity (CC-Sonar, the metric behind SonarQube) is the leading code quality metric for modern languages, but a 2023 PMC study using EEG and eye-tracking found measurable gaps:

CC-Sonar only measures control flow structure. It misses:

• Data complexity — how many variables, operators, and distinct symbols the reader must track simultaneously (Halstead)
• Identifier churn — how often a reader must revisit a variable across a wide scope (eye-tracking research)
• Saturation effect — once code is complex enough, doubling raw CC-Sonar doesn't double perceived difficulty

qualitas addresses all three gaps through a five-pillar composite score with an exponential saturation model.

PMC paper: "Measuring cognitive complexity in software development" — https://pmc.ncbi.nlm.nih.gov/articles/PMC9942489/

# Analyze a file (text output, default)
npx qualitas ./src/myFile.ts

# Analyze a directory
npx qualitas ./src/

# JSON report (writes to qualitas-report.json by default)
npx qualitas ./src/ -f json

# JSON report to a specific file
npx qualitas ./src/ -f json -o report.json

# Show only functions that have flags
npx qualitas ./src/ -f flagged

# Fail CI if any score is below threshold
npx qualitas ./src/ --threshold 65

# Zero-tolerance mode — fail on any warning flag
npx qualitas ./src/ --fail-on-flags warn

npm install qualitas

The correct native binary for your platform is installed automatically as an optional dependency:

No build step required when installing from npm.

Tracks nesting depth during AST traversal and applies progressively larger penalties for deeply nested control flow.

Scoring increments:

Formula: CFC = Σ(1 + nestingDepth) for nesting nodes, +1 flat for non-nesting nodes.

Halstead-inspired metric. Addresses CC-Sonar's largest gap (r=0.901 correlation in the PMC paper vs CC-Sonar's r=0.513).

Counting:

• Operators (η₁ distinct, N₁ total): +, -, *, /, ===, !==, <, >, <=, >=, =, +=, -=, &&, ||, ??, !, typeof, instanceof, ?., ??=, etc.
• Operands (η₂ distinct, N₂ total): identifiers (variables/params), string/numeric/template literals, this, null, undefined, boolean literals

Computed values:

Vocabulary  η = η₁ + η₂
Length      N = N₁ + N₂
Volume      V = N × log₂(η)
Difficulty  D = (η₁/2) × (N₂/η₂)
Effort      E = D × V

Normalized raw score:

DCI_raw = 0.6 × (D / 60) + 0.4 × (V / 3000)

Where 60 = F-tier difficulty threshold, 3000 = F-tier volume threshold.

Why it matters: A function with 20 distinct variable names, 15 distinct operators, and 200 total token appearances forces the reader to hold a large mental vocabulary simultaneously. CC-Sonar scores this identically to a trivial function with the same branching structure.

Novel metric. Inspired by the eye-tracking finding (r=0.963) that revisit count — how often a developer re-reads a variable while understanding code — is the strongest predictor of cognitive load.

Algorithm: For each declared identifier (variable, parameter, destructured binding) in function scope:

cost = referenceCount × log₂(scopeSpanLines + 1)
     where scopeSpanLines = lastReferenceLine − definitionLine

Total IRC = Σ(cost) over all identifiers.

Why it matters: A variable x referenced once on the line after it's declared has cost ≈ 1. A variable config referenced 12 times across a 150-line function has cost ≈ 12 × log₂(151) ≈ 87. The log₂ damping prevents enormous scope spans from completely dominating — matching the paper's finding that saturation occurs.

Measures how many external dependencies and distinct APIs a function/file touches.

At file level:

• importCount — total import statements
• distinctSources — unique module specifiers
• externalRatio — imports from node_modules / total imports

At function level:

• distinctApiCalls — distinct imported-module methods called (e.g., fs.readFile, axios.get = 2)
• closureCaptures — identifiers from outer scope referenced inside

Normalized raw score:

DC_raw = 0.4 × (importCount / 20) + 0.3 × externalRatio + 0.3 × (distinctApiCalls / 15)

Count-based metrics that catch simple but impactful structural issues.

• loc — non-blank, non-comment lines in function body
• parameterCount — formal parameters (destructured objects count as 1)
• maxNestingDepth — maximum block nesting depth
• returnCount — number of return statements

Normalized raw score:

SM_raw = 0.4×(loc/100) + 0.3×(params/6) + 0.2×(nesting/6) + 0.1×(returns/5)

Based on the PMC paper's finding that perceived difficulty saturates — once code is complex enough, doubling raw complexity doesn't double how hard it feels:

saturate(x) = 1 − e^(−k × x)    where k = 1.0

At x=1.0 (exactly at the F-tier threshold): saturate ≈ 0.63 At x=2.0 (twice F-tier): saturate ≈ 0.86 At x=3.0 (three times F-tier): saturate ≈ 0.95

This means once a function is in F-tier territory, further increases cause diminishing marginal penalty — reflecting actual developer experience.

penalty_i = saturate(raw_i) × weight_i × 100    for each pillar i
totalPenalty = Σ(penalty_i)
Quality Score = max(0, 100 − totalPenalty)

Higher score = better quality. Score 100 = no detected complexity.

needsRefactoring = score < 65 (configurable via refactoringThreshold).

Each flag has two thresholds: warn (first trigger) and error (severe). Flags can be individually enabled, disabled, or customized via qualitas.config.js. EXCESSIVE_RETURNS is disabled by default.

qualitas <path> [options]

Arguments:
  path                          File or directory to analyze

Options:
  -f, --format <format>         Output format (default: text)
                                  text | compact | detail | flagged | json | markdown | summary
  -o, --output <path>           Output file for report formats (json, markdown)
  -c, --config <path>           Path to qualitas.config.js (overrides auto-detection)
  -p, --profile <name>          Weight profile: default | cc-focused | data-focused | strict
  -t, --threshold <n>           Exit code 1 if any score is below this (default: 65)
  --fail-on-flags <level>       Exit code 1 if any function has flags: warn | error
  --include-tests               Include test files (*.test.*, *.spec.*) in analysis
  -h, --help                    Show help
  -V, --version                 Show version

Console formats — print to stdout, exit code reflects threshold/flag violations:

Report formats — write to file (defaults to qualitas-report.<ext> or use -o), always exit 0:

By default, the exit code is based only on the score threshold. With --fail-on-flags, the CLI also fails if any function has flags at the specified severity:

• --fail-on-flags warn — fail on any warning or error flag (zero tolerance)
• --fail-on-flags error — fail only on error-level flags

This can also be set in qualitas.config.js via the failOnFlags field.

# Basic file analysis
qualitas ./src/payment.ts

# CI check — fail if any function scores below 70
qualitas ./src/ --threshold 70

# Zero-tolerance mode — fail on any warning or error flag
qualitas ./src/ --fail-on-flags warn

# Markdown report (writes to qualitas-report.md by default)
qualitas ./src/ -f markdown

# Markdown report to a specific path
qualitas ./src/ -f markdown -o quality-report.md

# JSON report to a specific path
qualitas ./src/ -f json -o report.json

# Use a config file from another location
qualitas /path/to/other-repo -c ./qualitas.config.js

# Executive summary with pillar health breakdown
qualitas ./src/ -f summary

# Use cc-focused profile (closer to pure SonarQube behavior)
qualitas ./src/ --profile cc-focused

# Show only flagged functions
qualitas ./src/ -f flagged

import { quickScore, analyzeSource, analyzeFile, analyzeProject } from 'qualitas';
import type { FileQualityReport, QuickScore, AnalysisOptions, QualitasConfig } from 'qualitas';

// Fast check — returns only score, grade, and top flags (no full metric breakdown)
const qs: QuickScore = quickScore(`
  function add(a: number, b: number) { return a + b; }
`, 'add.ts');

console.log(qs.score);               // e.g. 98
console.log(qs.grade);               // 'A'
console.log(qs.needsRefactoring);    // false
console.log(qs.flaggedFunctionCount); // 0
console.log(qs.topFlags);            // []

// Full analysis — returns complete metric breakdown per function/class
const report = analyzeSource(`
  function add(a: number, b: number) {
    return a + b;
  }
`, 'add.ts');

console.log(report.score);   // e.g. 98
console.log(report.grade);   // 'A'
console.log(report.functions[0].metrics.cognitiveFlow.score); // raw CFC value

// Per-language flag overrides via config (e.g., stricter thresholds for Python)
const config: QualitasConfig = {
  languages: {
    python: { flags: { TOO_MANY_PARAMS: { warn: 3, error: 5 } } },
  },
};
const pyReport = analyzeSource(pythonSource, 'app.py', {}, config);

// Analyze a file (config parameter enables per-language flag resolution)
const fileReport = await analyzeFile('./src/payment.ts', {
  profile: 'strict',
  refactoringThreshold: 70,
});

// Analyze a full directory
const projectReport = await analyzeProject('./src/', {
  includeTests: false,
  refactoringThreshold: 65,
});

console.log(projectReport.summary.flaggedFunctions); // count of functions needing refactoring

interface QuickScore {
  score: number;               // 0–100 composite score
  grade: 'A' | 'B' | 'C' | 'D' | 'F';
  needsRefactoring: boolean;
  functionCount: number;
  flaggedFunctionCount: number;
  topFlags: RefactoringFlag[]; // up to 5, from the worst functions
}

interface AnalysisOptions {
  // Named weight profile
  profile?: 'default' | 'cc-focused' | 'data-focused' | 'strict';

  // Override individual pillar weights (must sum to 1.0)
  weights?: {
    cognitiveFlow?: number;       // default: 0.30
    dataComplexity?: number;      // default: 0.25
    identifierReference?: number; // default: 0.20
    dependencyCoupling?: number;  // default: 0.15
    structural?: number;          // default: 0.10
  };

  // Score below which needsRefactoring = true (default: 65)
  refactoringThreshold?: number;

  // Include test files in project analysis (default: false)
  includeTests?: boolean;

  // File extensions to include (default: .ts .tsx .js .jsx .mjs .cjs .py .pyi)
  extensions?: string[];

  // Directories/files to exclude (default: .git, qualitas.config.js)
  // Configure additional excludes (node_modules, dist, etc.) via qualitas.config.js
  exclude?: string[];

  // Per-flag overrides — supports both camelCase and SCREAMING_SNAKE_CASE keys
  flagOverrides?: Record<string, FlagConfig>;
}

interface FileQualityReport {
  filePath: string;
  score: number;           // 0–100
  grade: 'A' | 'B' | 'C' | 'D' | 'F';
  needsRefactoring: boolean;
  flags: RefactoringFlag[];
  functions: FunctionQualityReport[];
  classes: ClassQualityReport[];
  fileDependencies: DependencyCouplingResult;
  totalLines: number;
  functionCount: number;
  classCount: number;
  flaggedFunctionCount: number;
}

interface FunctionQualityReport {
  name: string;
  inferredName?: string;      // e.g. "const myFn = " for arrow functions
  score: number;
  grade: Grade;
  needsRefactoring: boolean;
  flags: RefactoringFlag[];
  metrics: MetricBreakdown;   // raw values for all 5 pillars
  scoreBreakdown: ScoreBreakdown; // per-pillar penalty contributions
  location: SourceLocation;
  isAsync: boolean;
  isGenerator: boolean;
}

Weights derived from the PMC correlation coefficients, calibrated to avoid over-penalizing simple pattern matches (which inflate CFC but carry no real cognitive load):

Boosts CFC to 0.50. Behaves similarly to SonarQube Cognitive Complexity for teams transitioning from that tool.

Boosts DCI+IRC to 0.65 combined. Emphasizes Halstead/data complexity — useful for codebases with complex algorithms and data transformations.

Same weights as default but tighter grade bands: A≥90, B≥75, C≥60, D≥40.

qualitas: src/processPayment.ts
████░░░░░░  score: 42.0  grade: D

  ✗ processPayment()  [D]  score: 42  ← needs refactoring
    Flags:
    [error] Cognitive flow complexity is 44 (threshold: 19)
           → Extract nested branches into separate named functions. Use early returns to flatten the nesting hierarchy.
    [error] Identifier reference complexity is 178.2 (threshold: 71)
           → Variables are referenced many times across a wide scope. Break this function into smaller functions to shorten variable lifetimes.
    [error] Function has 6 parameters (threshold: 5)
           → Group related parameters into an options object: `{ option1, option2, ... }`.
    [error] Maximum nesting depth is 10 (threshold: 5)
           → Use early returns (guard clauses) to flatten the nesting hierarchy.

  ✓ validateCard()    [B]  score: 71
  ✓ formatAmount()    [A]  score: 97

File: D — 42.0  — 1 of 3 function(s) need refactoring

qualitas/
├── crates/
│   ├── qualitas-core/          Language-agnostic analysis engine
│   │   ├── analyzer.rs         Orchestrator: extract → metrics → score → report
│   │   ├── types.rs            All Rust structs (serde → JSON → TypeScript)
│   │   ├── constants.rs        Thresholds, weights, saturation K, grade bands
│   │   ├── ir/                 Intermediate representation (event-based)
│   │   ├── languages/          Language adapters (TypeScript, Rust, Python)
│   │   ├── metrics/            5 metric collectors (CFC, DCI, IRC, DC, SM)
│   │   ├── scorer/             Composite score + flag generation
│   │   └── parser/             Shared parsing utilities (LOC counting, etc.)
│   │
│   ├── qualitas-cli/           Standalone Rust CLI binary
│   │   ├── main.rs             CLI entry point (clap)
│   │   ├── config.rs           qualitas.config.js loader
│   │   └── reporters/          text, compact, detail, flagged, json, markdown, summary
│   │
│   └── qualitas-napi/          Node.js native binding (napi-rs)
│
├── js/                         TypeScript wrapper (thin layer over native binding)
│   ├── index.ts                Public API: analyzeSource, analyzeFile, analyzeProject
│   ├── types.ts                TypeScript interfaces mirroring Rust serde structs
│   ├── cli.ts                  Commander CLI (Node.js)
│   └── reporters/              text, json, markdown reporters
│
├── tests/
│   ├── shared/                 Cross-cutting tests (scoring, config, reporters, project)
│   ├── typescript/             TypeScript adapter tests + fixtures
│   └── _template/              Template for adding new language adapter tests
│
├── qualitas_napi.js            Platform-aware native binding loader (auto-generated)
└── bin/qualitas.js             Node.js CLI entry point shim

• TypeScript / JavaScript — via oxc_parser (.ts, .tsx, .js, .jsx, .mjs, .cjs)
• Rust — via syn (.rs)
• Python — via tree-sitter-python (.py, .pyi)
• Go — via tree-sitter-go (.go)
• Java — via tree-sitter-java (.java)

Adding a new language requires only one adapter file. See CONTRIBUTING_LANGUAGE.md.

The core analysis engine is written in Rust for three reasons:

1. Speed: oxc_parser (the parser powering Oxc/Biome/Rolldown) parses TypeScript at ~26ms vs SWC's ~84ms on large files. Arena-allocated AST with no GC pauses means analyzing 100+ file projects completes in under a second.

2. Correctness: Rust's type system enforces exhaustive handling of all AST node variants at compile time. Missing a node type is a compile error, not a runtime bug.

3. Distribution: The napi-rs optional-dependency pattern (same as SWC, Rspack, Oxlint) lets users npm install without any build toolchain. Pre-compiled binaries for all 5 platforms ship as separate optional packages and are selected automatically.

Language adapters parse source code and emit a stream of QualitasEvent values (control flow, operators, operands, nesting, etc.). The 5 metric collectors consume these events without knowing anything about the source language. This makes adding a new language a matter of writing one adapter file — the scoring engine is fully language-agnostic.

Create a qualitas.config.js in your project root. All fields are optional — CLI flags take priority.

Config file search order:

1. Explicit -c / --config path (if provided)
2. Walk up from the analyzed directory looking for qualitas.config.js
3. Look next to the qualitas executable

module.exports = {
  // Exit code 1 if any function scores below this threshold (0-100)
  threshold: 80,

  // Fail on flags regardless of score: 'warn' | 'error'
  failOnFlags: 'error',

  // Weight profile: 'default' | 'cc-focused' | 'data-focused' | 'strict'
  profile: 'default',

  // Directories/files to exclude from analysis.
  // Only .git and qualitas.config.js are excluded by default — configure all others here.
  exclude: ['node_modules', 'dist', 'build', 'coverage', 'target'],

  // Per-flag configuration (enable/disable, custom thresholds).
  // Both camelCase and SCREAMING_SNAKE_CASE keys are supported.
  flags: {
    TOO_MANY_PARAMS: { warn: 5, error: 7 },
    EXCESSIVE_RETURNS: true,  // re-enable (disabled by default)
    DEEP_NESTING: false,      // disable entirely
  },

  // Per-language configuration
  languages: {
    typescript: {
      testPatterns: ['.test.', '.spec.', 'tests/'],
    },
    python: {
      testPatterns: ['test_', '_test.py', 'tests/', 'conftest.py'],
      // Per-language flag overrides (take precedence over global flags)
      flags: {
        TOO_MANY_PARAMS: { warn: 4, error: 6 },
      },
    },
    rust: {
      testPatterns: ['_test.rs', '_tests.rs', 'tests/'],
    },
  },
};

Prerequisites: Rust toolchain (≥1.75), Node.js (≥18), @napi-rs/cli v3

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Install napi-rs CLI
npm install -g @napi-rs/cli

# Clone and build
git clone https://github.com/An631/qualitas.git
cd qualitas
npm install

# Build native binary (debug, fast)
npm run build:debug

# Build native binary (release, optimized)
npm run build

# Build TypeScript wrapper
npm run build:ts

# Run all tests
cargo test -p qualitas-core   # 146 Rust unit tests
npm run test:ts               # 69 JS integration tests

146 tests across all modules. Cover:

• Per-language conformance tests (TypeScript, Rust, and Python adapters)
• CFC, DCI, IRC, DC, SM metric collectors via event-based IR
• Composite scorer saturation invariants (sublinearity, score bounds)
• Flag generation with default and custom thresholds
• Grade assignment across all profiles

69 tests across tests/shared/ and tests/typescript/. Exercise the full stack (Rust → napi → JS):

• Scoring invariants, config loading/merging, reporter output, project analysis
• Flag overrides: camelCase and SCREAMING_SNAKE_CASE keys, custom thresholds, enable/disable
• Per-language flag overrides via config parameter
• TypeScript adapter: function collection patterns, class methods, arrow functions
• Python adapter: function/class extraction, comprehensions, decorators, async/await
• Weight profiles, threshold configuration, scope filtering

MIT