sbom-tools 0.1.22

//! Cost model for diff operations.

use serde::{Deserialize, Serialize};

/// Cost model configuration for semantic diff operations.
///
/// Costs are used to determine the minimum-cost alignment between two SBOMs.
/// Higher costs indicate more significant changes.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CostModel {
    /// Cost for adding a new component
    pub component_added: u32,
    /// Cost for removing a component
    pub component_removed: u32,
    /// Cost for patch version change
    pub version_patch: u32,
    /// Cost for minor version change
    pub version_minor: u32,
    /// Cost for major version change
    pub version_major: u32,
    /// Cost for license change
    pub license_changed: u32,
    /// Cost for supplier change
    pub supplier_changed: u32,
    /// Cost for ML model metadata change
    pub ml_model_changed: u32,
    /// Cost for dataset metadata change
    pub dataset_changed: u32,
    /// Cost for ML approach change (e.g. supervised -> reinforcement-learning)
    pub ml_approach_changed: u32,
    /// Cost for ML architecture change (family or name, e.g. cnn -> transformer)
    pub ml_architecture_changed: u32,
    /// Cost for ML task change (e.g. nlp -> computer-vision)
    pub ml_task_changed: u32,
    /// Cost for ML quantization change (e.g. fp32 -> int4); a model-swap signal
    pub ml_quantization_changed: u32,
    /// Cost for ML model-card URL change
    pub ml_model_card_changed: u32,
    /// Cost for adding a training dataset to a model
    pub ml_training_dataset_added: u32,
    /// Cost for removing a training dataset from a model (provenance loss; HIGH)
    pub ml_training_dataset_removed: u32,
    /// Cost for dataset type change (e.g. training -> validation)
    pub dataset_type_changed: u32,
    /// Cost for dataset governance owners change
    pub dataset_governance_changed: u32,
    /// Cost for adding a dataset sensitivity classification (e.g. gaining PII; HIGH)
    pub dataset_sensitivity_added: u32,
    /// Cost for removing a dataset sensitivity classification
    pub dataset_sensitivity_removed: u32,
    /// Cost for introducing a vulnerability
    pub vulnerability_introduced: u32,
    /// Reward (negative cost) for resolving a vulnerability
    pub vulnerability_resolved: i32,
    /// Cost for adding a dependency
    pub dependency_added: u32,
    /// Cost for removing a dependency
    pub dependency_removed: u32,
    /// Cost for hash mismatch (integrity concern)
    pub hash_mismatch: u32,
    /// Cost for crypto algorithm family change
    pub crypto_algorithm_changed: u32,
    /// Cost for crypto security downgrade (weaker algorithm or lower security level)
    pub crypto_downgrade: u32,
    /// Cost for crypto key rotation
    pub crypto_key_rotated: u32,
    /// Cost for certificate expiry date change
    pub crypto_cert_expiry_changed: u32,
    /// Cost for protocol version change
    pub crypto_protocol_changed: u32,
    /// Cost for quantum security level change
    pub crypto_quantum_level_changed: u32,
}

impl Default for CostModel {
    fn default() -> Self {
        Self {
            component_added: 10,
            component_removed: 10,
            version_patch: 2,
            version_minor: 4,
            version_major: 7,
            license_changed: 6,
            supplier_changed: 4,
            ml_model_changed: 6,
            dataset_changed: 5,
            ml_approach_changed: 6,
            ml_architecture_changed: 6,
            ml_task_changed: 5,
            ml_quantization_changed: 8,
            ml_model_card_changed: 3,
            ml_training_dataset_added: 5,
            ml_training_dataset_removed: 12,
            dataset_type_changed: 5,
            dataset_governance_changed: 4,
            dataset_sensitivity_added: 14,
            dataset_sensitivity_removed: 6,
            vulnerability_introduced: 15,
            vulnerability_resolved: -3,
            dependency_added: 5,
            dependency_removed: 5,
            hash_mismatch: 8,
            crypto_algorithm_changed: 8,
            crypto_downgrade: 20,
            crypto_key_rotated: 3,
            crypto_cert_expiry_changed: 5,
            crypto_protocol_changed: 6,
            crypto_quantum_level_changed: 10,
        }
    }
}

impl CostModel {
    /// Create a security-focused cost model
    #[must_use]
    pub fn security_focused() -> Self {
        Self {
            vulnerability_introduced: 25,
            vulnerability_resolved: -5,
            hash_mismatch: 15,
            supplier_changed: 8,
            crypto_downgrade: 30,
            crypto_quantum_level_changed: 15,
            crypto_algorithm_changed: 12,
            // Model-swap and data-governance escalations are security-relevant:
            // gaining a sensitivity classification (e.g. PII), losing training-data
            // provenance, or silently re-quantizing a model all warrant higher cost.
            dataset_sensitivity_added: 22,
            ml_training_dataset_removed: 18,
            ml_quantization_changed: 12,
            ..Default::default()
        }
    }

    /// Create a compliance-focused cost model
    #[must_use]
    pub fn compliance_focused() -> Self {
        Self {
            license_changed: 12,
            supplier_changed: 8,
            ..Default::default()
        }
    }

    /// Get cost for version change based on semver
    #[must_use]
    pub const fn version_change_cost(
        &self,
        old: &Option<semver::Version>,
        new: &Option<semver::Version>,
    ) -> u32 {
        match (old, new) {
            (Some(old_ver), Some(new_ver)) => {
                if old_ver.major != new_ver.major {
                    self.version_major
                } else if old_ver.minor != new_ver.minor {
                    self.version_minor
                } else if old_ver.patch != new_ver.patch {
                    self.version_patch
                } else {
                    0
                }
            }
            (None, Some(_)) | (Some(_), None) => self.version_minor,
            (None, None) => 0,
        }
    }

    /// Calculate total semantic score from change counts
    #[allow(clippy::too_many_arguments)]
    #[must_use]
    pub const fn calculate_semantic_score(
        &self,
        components_added: usize,
        components_removed: usize,
        version_changes: usize,
        license_changes: usize,
        vulns_introduced: usize,
        vulns_resolved: usize,
        deps_added: usize,
        deps_removed: usize,
    ) -> f64 {
        let score = (components_added as u32 * self.component_added)
            + (components_removed as u32 * self.component_removed)
            + (version_changes as u32 * self.version_minor)
            + (license_changes as u32 * self.license_changed)
            + (vulns_introduced as u32 * self.vulnerability_introduced)
            + (deps_added as u32 * self.dependency_added)
            + (deps_removed as u32 * self.dependency_removed);

        let reward = vulns_resolved as i32 * self.vulnerability_resolved;

        (score as i32 + reward) as f64
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_default_cost_model() {
        let model = CostModel::default();
        assert_eq!(model.component_added, 10);
        assert_eq!(model.component_removed, 10);
        assert_eq!(model.version_patch, 2);
        assert_eq!(model.version_minor, 4);
        assert_eq!(model.version_major, 7);
        assert_eq!(model.license_changed, 6);
        assert_eq!(model.supplier_changed, 4);
        assert_eq!(model.ml_model_changed, 6);
        assert_eq!(model.dataset_changed, 5);
        assert_eq!(model.ml_approach_changed, 6);
        assert_eq!(model.ml_architecture_changed, 6);
        assert_eq!(model.ml_task_changed, 5);
        assert_eq!(model.ml_quantization_changed, 8);
        assert_eq!(model.ml_model_card_changed, 3);
        assert_eq!(model.ml_training_dataset_added, 5);
        assert_eq!(model.ml_training_dataset_removed, 12);
        assert_eq!(model.dataset_type_changed, 5);
        assert_eq!(model.dataset_governance_changed, 4);
        assert_eq!(model.dataset_sensitivity_added, 14);
        assert_eq!(model.dataset_sensitivity_removed, 6);
        assert_eq!(model.vulnerability_introduced, 15);
        assert_eq!(model.vulnerability_resolved, -3);
        assert_eq!(model.hash_mismatch, 8);
        assert_eq!(model.crypto_algorithm_changed, 8);
        assert_eq!(model.crypto_downgrade, 20);
        assert_eq!(model.crypto_key_rotated, 3);
        assert_eq!(model.crypto_cert_expiry_changed, 5);
        assert_eq!(model.crypto_protocol_changed, 6);
        assert_eq!(model.crypto_quantum_level_changed, 10);
    }

    #[test]
    fn test_security_focused_model() {
        let model = CostModel::security_focused();
        let default = CostModel::default();
        assert!(model.vulnerability_introduced > default.vulnerability_introduced);
        assert!(model.hash_mismatch > default.hash_mismatch);
        assert!(model.vulnerability_resolved < default.vulnerability_resolved);
        assert!(model.crypto_downgrade > default.crypto_downgrade);
        assert!(model.crypto_quantum_level_changed > default.crypto_quantum_level_changed);
        assert!(model.dataset_sensitivity_added > default.dataset_sensitivity_added);
        assert!(model.ml_training_dataset_removed > default.ml_training_dataset_removed);
        assert!(model.ml_quantization_changed > default.ml_quantization_changed);
    }

    #[test]
    fn test_compliance_focused_model() {
        let model = CostModel::compliance_focused();
        let default = CostModel::default();
        assert!(model.license_changed > default.license_changed);
        assert!(model.supplier_changed > default.supplier_changed);
    }

    fn ver(major: u64, minor: u64, patch: u64) -> semver::Version {
        semver::Version::new(major, minor, patch)
    }

    #[test]
    fn test_version_change_cost_major() {
        let model = CostModel::default();
        let old = Some(ver(1, 0, 0));
        let new = Some(ver(2, 0, 0));
        assert_eq!(model.version_change_cost(&old, &new), model.version_major);
    }

    #[test]
    fn test_version_change_cost_minor() {
        let model = CostModel::default();
        let old = Some(ver(1, 0, 0));
        let new = Some(ver(1, 1, 0));
        assert_eq!(model.version_change_cost(&old, &new), model.version_minor);
    }

    #[test]
    fn test_version_change_cost_patch() {
        let model = CostModel::default();
        let old = Some(ver(1, 0, 0));
        let new = Some(ver(1, 0, 1));
        assert_eq!(model.version_change_cost(&old, &new), model.version_patch);
    }

    #[test]
    fn test_version_change_cost_same() {
        let model = CostModel::default();
        let old = Some(ver(1, 2, 3));
        let new = Some(ver(1, 2, 3));
        assert_eq!(model.version_change_cost(&old, &new), 0);
    }

    #[test]
    fn test_version_change_cost_none_to_some() {
        let model = CostModel::default();
        let new = Some(ver(1, 0, 0));
        assert_eq!(model.version_change_cost(&None, &new), model.version_minor);
    }

    #[test]
    fn test_version_change_cost_some_to_none() {
        let model = CostModel::default();
        let old = Some(ver(1, 0, 0));
        assert_eq!(model.version_change_cost(&old, &None), model.version_minor);
    }

    #[test]
    fn test_version_change_cost_none_none() {
        let model = CostModel::default();
        assert_eq!(model.version_change_cost(&None, &None), 0);
    }

    #[test]
    fn test_semantic_score_zero() {
        let model = CostModel::default();
        let score = model.calculate_semantic_score(0, 0, 0, 0, 0, 0, 0, 0);
        assert_eq!(score, 0.0);
    }

    #[test]
    fn test_semantic_score_basic() {
        let model = CostModel::default();
        // 2 added (10 each) + 1 removed (10) + 1 version change (4) = 34
        let score = model.calculate_semantic_score(2, 1, 1, 0, 0, 0, 0, 0);
        assert_eq!(score, 34.0);
    }

    #[test]
    fn test_semantic_score_with_resolved() {
        let model = CostModel::default();
        // 1 vuln introduced (15) + 2 resolved (2 * -3 = -6) = 9
        let score = model.calculate_semantic_score(0, 0, 0, 0, 1, 2, 0, 0);
        assert_eq!(score, 9.0);
    }
}