{"record":{"id":"db7709b7ee9be4bd","repo":"affaan-m/ECC","slug":"minimum-samples-must-be-positive","errorCode":null,"errorMessage":"minimum samples must be positive","messagePattern":"minimum samples must be positive","errorType":"validation","errorClass":null,"httpStatus":null,"severity":"error","filePath":"ecc2/src/harness_eval.rs","lineNumber":508,"sourceCode":"    pub min_mean_delta: f64,\n    pub min_win_rate: f64,\n}\n\n#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]\npub struct Comparison {\n    pub passed: bool,\n    pub sample_count: usize,\n    pub candidate_mean: f64,\n    pub baseline_mean: f64,\n    pub mean_delta: f64,\n    pub win_rate: f64,\n    pub failures: Vec<String>,\n}\n\nimpl PromotionPolicy {\n    pub fn validate(self) -> Result<()> {\n        if self.min_samples == 0 {\n            bail!(\"minimum samples must be positive\");\n        }\n        if !self.min_mean_delta.is_finite() {\n            bail!(\"minimum mean delta must be finite\");\n        }\n        if !self.min_win_rate.is_finite() || !(0.0..=1.0).contains(&self.min_win_rate) {\n            bail!(\"minimum win rate must be between 0 and 1\");\n        }\n        Ok(())\n    }\n\n    pub fn compare(self, samples: &[PairedSample]) -> Result<Comparison> {\n        self.validate()?;\n        if samples.is_empty() {\n            bail!(\"samples cannot be empty\");\n        }\n        if samples\n            .iter()\n            .map(|sample| sample.seed)","sourceCodeStart":490,"sourceCodeEnd":526,"githubUrl":"https://github.com/affaan-m/ECC/blob/8321021c54d670126ce3b2969d5deb880b4b0c2a/ecc2/src/harness_eval.rs#L490-L526","documentation":"`PromotionPolicy::validate` checks that `min_samples` is at least 1 before any statistical comparison. A policy requiring zero samples is meaningless — no result could ever fail the threshold — so it is rejected as a configuration mistake.","triggerScenarios":"Constructing a `PromotionPolicy` with `min_samples: 0` (explicitly or via `Default`/partial builder) and then calling `compare` (or `validate` directly) on a sample slice.","commonSituations":"Deserializing a policy from JSON/TOML where min_samples defaulted to 0; a computed `min_samples` that underflowed; users confusing 'minimum extra samples' with total sample count.","solutions":["Set `min_samples` to a positive value (e.g. 30 for a reasonable paired-comparison baseline) before calling `compare`","Validate the policy right after deserialization and fail with a clear config error","Guard computed values with `min_samples.max(1)`"],"exampleFix":"// before\nlet policy = PromotionPolicy { min_samples: 0, .. };\nlet comparison = policy.compare(&samples)?;\n// after\nlet policy = PromotionPolicy { min_samples: 30, .. };\nlet comparison = policy.compare(&samples)?;","handlingStrategy":"validation","validationCode":"fn policy_is_valid(min_samples: usize) -> bool {\n    min_samples > 0\n}","typeGuard":null,"tryCatchPattern":"match policy.compare(&samples) {\n    Ok(comparison) => comparison,\n    Err(e) if e.to_string().contains(\"minimum samples must be positive\") => {\n        eprintln!(\"PromotionPolicy misconfigured: {e}\");\n        // fall back to a sane default policy\n        PromotionPolicy { min_samples: 30, ..policy }.compare(&samples)?\n    }\n    Err(e) => return Err(e),\n}","preventionTips":["Validate PromotionPolicy immediately after deserialization, before use","Provide a `Default` with min_samples >= 1 and never hand-roll a zero default","Treat 0 in config as 'unset' and substitute a documented default"],"tags":["validation","promotion-policy","config"],"backgroundTag":"invalid-config-value","analyzedSha":"8321021c54d670126ce3b2969d5deb880b4b0c2a","analyzedAt":"2026-09-16T10:08:13.343Z","contentChangedAt":"2026-09-16T10:08:13.343Z","schemaVersion":2},"datasetVersion":"2026-09-23T08:17:48.524Z"}