kimun 0.20.0

//! Piecewise linear normalization curves for the code health score.
//!
//! Each quality dimension (cognitive complexity, duplication, indent,
//! Halstead, file size) uses a curve of breakpoints to map raw metric
//! values to a 0–100 score. Breakpoints are calibrated based on industry
//! thresholds and empirical testing. Values between breakpoints are
//! linearly interpolated; values beyond the endpoints are clamped.

/// A single point on a piecewise linear curve, mapping an `input` metric
/// value to an output `score` (0–100).
struct Breakpoint {
    /// Raw metric value (e.g. complexity count, dup percentage).
    input: f64,
    /// Corresponding normalized score on the 0–100 scale.
    score: f64,
}

/// Piecewise linear interpolation.  Values below the first breakpoint clamp to its score;
/// values above the last clamp to its score.
fn piecewise(value: f64, curve: &[Breakpoint]) -> f64 {
    debug_assert!(
        curve.windows(2).all(|w| w[0].input <= w[1].input),
        "Breakpoints must be sorted by input in ascending order"
    );
    if curve.is_empty() {
        return 0.0;
    }
    if value <= curve[0].input {
        return curve[0].score;
    }
    for w in curve.windows(2) {
        if value <= w[1].input {
            let frac = (value - w[0].input) / (w[1].input - w[0].input);
            return w[0].score + frac * (w[1].score - w[0].score);
        }
    }
    curve.last().unwrap().score
}

/// Cognitive complexity curve: max per-function cognitive complexity to 0–100.
/// Based on SonarQube threshold (15) and Clippy threshold (25).
/// ≤4 → 100 (simple), 9 → 85, 14 → 65, 24 → 35, 50 → 5, ≥100 → 0.
const COGNITIVE_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 4.0,
        score: 100.0,
    },
    Breakpoint {
        input: 9.0,
        score: 85.0,
    },
    Breakpoint {
        input: 14.0,
        score: 65.0,
    },
    Breakpoint {
        input: 24.0,
        score: 35.0,
    },
    Breakpoint {
        input: 50.0,
        score: 5.0,
    },
    Breakpoint {
        input: 100.0,
        score: 0.0,
    },
];

/// Duplication percentage curve: % of duplicated lines mapped to 0–100.
/// ≤5% → 100 (excellent), 10% → 80, 20% → 40, 40% → 10, 100% → 0.
const DUPLICATION_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 5.0,
        score: 100.0,
    },
    Breakpoint {
        input: 10.0,
        score: 80.0,
    },
    Breakpoint {
        input: 20.0,
        score: 40.0,
    },
    Breakpoint {
        input: 40.0,
        score: 10.0,
    },
    Breakpoint {
        input: 100.0,
        score: 0.0,
    },
];

/// Indentation complexity curve: stddev of indent depth mapped to 0–100.
/// ≤1.0 → 100 (flat), 1.5 → 80, 2.0 → 50, 3.0 → 20, ≥5.0 → 0 (deeply nested).
const INDENT_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 1.0,
        score: 100.0,
    },
    Breakpoint {
        input: 1.5,
        score: 80.0,
    },
    Breakpoint {
        input: 2.0,
        score: 50.0,
    },
    Breakpoint {
        input: 3.0,
        score: 20.0,
    },
    Breakpoint {
        input: 5.0,
        score: 0.0,
    },
];

/// Halstead effort-per-LOC curve: effort/code_lines mapped to 0–100.
/// ≤1000 → 100 (low cognitive load), 5000 → 70, 10000 → 40, ≥20000 → 0.
const HALSTEAD_EPL_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 1000.0,
        score: 100.0,
    },
    Breakpoint {
        input: 5000.0,
        score: 70.0,
    },
    Breakpoint {
        input: 10000.0,
        score: 40.0,
    },
    Breakpoint {
        input: 20000.0,
        score: 0.0,
    },
];

/// File size curve: code lines mapped to 0–100.
/// ≤500 → 100 (ideal), 1000 → 60, 2000 → 20, ≥4000 → 0 (too large).
const FILE_SIZE_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 500.0,
        score: 100.0,
    },
    Breakpoint {
        input: 1000.0,
        score: 60.0,
    },
    Breakpoint {
        input: 2000.0,
        score: 20.0,
    },
    Breakpoint {
        input: 4000.0,
        score: 0.0,
    },
];

/// Normalize max cognitive complexity to a 0–100 score (lower complexity = higher score).
pub fn normalize_cognitive(max_complexity: usize) -> f64 {
    piecewise(max_complexity as f64, COGNITIVE_CURVE)
}

/// Normalize duplication percentage to a 0–100 score (lower duplication = higher score).
pub fn normalize_duplication(dup_percent: f64) -> f64 {
    piecewise(dup_percent, DUPLICATION_CURVE)
}

/// Normalize indentation stddev to a 0–100 score (lower stddev = higher score).
pub fn normalize_indent(stddev: f64) -> f64 {
    piecewise(stddev, INDENT_CURVE)
}

/// Normalize Halstead effort per LOC to a 0–100 score.
/// Returns 50 (neutral) when effort or code_lines is zero (missing data).
pub fn normalize_halstead(effort: f64, code_lines: usize) -> f64 {
    if effort <= 0.0 || code_lines == 0 {
        return 50.0; // neutral for missing data
    }
    piecewise(effort / code_lines as f64, HALSTEAD_EPL_CURVE)
}

/// Normalize file size (code lines) to a 0–100 score (smaller files score higher).
pub fn normalize_file_size(code_lines: usize) -> f64 {
    piecewise(code_lines as f64, FILE_SIZE_CURVE)
}

// --- Legacy model curves (v0.13: MI + Cyclomatic) ---

/// Maintainability Index curve (legacy model): MI score (0–100+) to 0–100.
/// 100→100 (excellent), 75→90, 50→60, 25→20, 0→0 (unmaintainable).
const MI_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 0.0,
        score: 0.0,
    },
    Breakpoint {
        input: 25.0,
        score: 20.0,
    },
    Breakpoint {
        input: 50.0,
        score: 60.0,
    },
    Breakpoint {
        input: 75.0,
        score: 90.0,
    },
    Breakpoint {
        input: 100.0,
        score: 100.0,
    },
];

/// Cyclomatic complexity curve (legacy model): max per-function complexity to 0–100.
/// ≤5→100, 10→85, 15→65, 25→35, 50→5, ≥100→0.
const COMPLEXITY_CURVE: &[Breakpoint] = &[
    Breakpoint {
        input: 5.0,
        score: 100.0,
    },
    Breakpoint {
        input: 10.0,
        score: 85.0,
    },
    Breakpoint {
        input: 15.0,
        score: 65.0,
    },
    Breakpoint {
        input: 25.0,
        score: 35.0,
    },
    Breakpoint {
        input: 50.0,
        score: 5.0,
    },
    Breakpoint {
        input: 100.0,
        score: 0.0,
    },
];

/// Normalize Maintainability Index to a 0–100 score (legacy model).
pub fn normalize_mi(mi_score: f64) -> f64 {
    piecewise(mi_score, MI_CURVE)
}

/// Normalize max cyclomatic complexity to a 0–100 score (legacy model).
pub fn normalize_complexity(max_complexity: usize) -> f64 {
    piecewise(max_complexity as f64, COMPLEXITY_CURVE)
}

#[cfg(test)]
#[path = "normalize_test.rs"]
mod tests;