coverage-kaizen

name	coverage-kaizen
description	Systematic coverage gap analysis and test writing for the APR Model QA Playbook. Uses pmat query --coverage-gaps for highest-ROI targets, provides test patterns for each crate (proptest for gen, Evidence assertions for runner, MQS scoring for report), handles CommandRunner trait extensions, clippy pedantic/nursery landmines, and ExecutionConfig construction. Target: 95% library coverage.
disable-model-invocation	false
user-invocable	true
allowed-tools	Read, Grep, Glob, Bash
argument-hint	target: crate name (apr-qa-gen, apr-qa-runner, apr-qa-report, apr-qa-certify), function name, or coverage goal (e.g., 96%)

Coverage Kaizen

Continuous improvement workflow for maintaining >= 95% library test coverage across the APR Model QA Playbook workspace.

Quick Start

Find Coverage Gaps

# Top coverage gaps ranked by ROI (MANDATORY: always use pmat query)
pmat query --coverage-gaps --rank-by impact --limit 20 --exclude-tests

# Coverage gaps for a specific crate
pmat query --coverage-gaps --limit 30 --exclude-file "tests" | grep "apr-qa-runner"

# Current coverage percentage
cargo llvm-cov --workspace --lib 2>&1 | grep "^TOTAL"

Verify Compliance

# PMAT compliance check (>= 95%)
make coverage-check

# Or manually
./scripts/coverage-check.sh

# Full HTML coverage report
make coverage
# Opens: target/llvm-cov/html/index.html

Coverage Commands

Command	What It Does
make coverage	HTML report (library code only)
make coverage-summary	Terminal summary
make coverage-check	Verify >= 95% threshold
cargo llvm-cov --workspace --lib	Raw coverage data
cargo llvm-cov --workspace --lib --html	HTML with source annotation

Never use cargo tarpaulin. It's slow, unreliable, and causes hangs.

Kaizen Workflow

Step 1: Identify Targets

pmat query --coverage-gaps --rank-by impact --limit 20 --exclude-tests

Pick the function with the highest impact_score first (best ROI per test written).

Step 2: Read the Function

# Use pmat query to read source (NOT cat/Read)
pmat query "function_name" --include-source --limit 1

Step 3: Write Tests

Follow the crate-specific patterns below. Key rules:

• Tests follow Popperian falsification (design to fail, not to pass)
• Use Evidence::corroborated() (4 args) and Evidence::falsified() (5 args)
• Use ..Default::default() for ExecutionConfig in tests
• Allow clippy::unwrap_used and clippy::expect_used in test code (already cfg_attr-allowed)

Step 4: Verify Improvement

# Re-check coverage
pmat query --coverage-gaps --rank-by impact --limit 20 --exclude-tests

# Verify threshold
make coverage-check

Step 5: Run Full Gate

make check   # fmt-check + lint + test + docs-check

Crate-Specific Test Patterns

apr-qa-gen (Scenario Generation)

Key types: QaScenario, Oracle, OracleResult, ModelId, Modality, Backend, Format

Pattern: Proptest strategies

use proptest::prelude::*;
use crate::proptest_impl::*;

proptest! {
    #[test]
    fn scenario_always_has_valid_id(scenario in scenario_strategy()) {
        prop_assert!(!scenario.id.is_empty());
        prop_assert!(scenario.id.contains('_'));
    }
}

Pattern: Oracle evaluation

#[test]
fn arithmetic_oracle_correct_addition() {
    let oracle = ArithmeticOracle::new();
    let result = oracle.evaluate("What is 3+4?", "The answer is 7.");
    assert!(matches!(result, OracleResult::Corroborated { .. }));
}

#[test]
fn garbage_oracle_detects_repetition() {
    let oracle = GarbageOracle::new();
    let result = oracle.evaluate("test", "abcabcabcabcabcabcabcabcabc");
    assert!(matches!(result, OracleResult::Falsified { .. }));
}

Pattern: Oracle selection

#[test]
fn selects_arithmetic_for_math_prompt() {
    let oracle = select_oracle("What is 5+3?");
    assert_eq!(oracle.name(), "arithmetic");
}

Available proptest strategies:

• model_id_strategy() - Random model IDs from supported families
• modality_strategy() - Run/Chat/Serve
• backend_strategy() - Cpu/Gpu
• format_strategy() - Gguf/SafeTensors/Apr
• arithmetic_prompt_strategy() - Verifiable math prompts
• code_prompt_strategy() - Code completion prompts
• edge_case_prompt_strategy() - Empty, unicode, XSS, SQL injection
• any_prompt_strategy() - Weighted combination
• scenario_strategy() - Complete random scenarios
• temperature_strategy() - 0.0, 0.7, 1.0, or random
• max_tokens_strategy() - 1, 32, 128, 512, 2048, or random

apr-qa-runner (Execution Engine)

Key types: Evidence, Outcome, EvidenceCollector, Executor, ExecutionConfig, CommandRunner

Pattern: Evidence construction

use crate::evidence::{Evidence, Outcome};
use apr_qa_gen::scenario::QaScenario;

fn test_scenario() -> QaScenario {
    QaScenario::new(
        ModelId::new("test/model"),
        Modality::Run,
        Backend::Cpu,
        Format::Gguf,
        "What is 2+2?".to_string(),
        42,
    )
}

#[test]
fn corroborated_evidence_is_pass() {
    let e = Evidence::corroborated("F-QUAL-001", test_scenario(), "output", 100);
    assert!(e.outcome.is_pass());
    assert_eq!(e.reason, "Test passed");
    assert_eq!(e.exit_code, Some(0));
}

#[test]
fn falsified_evidence_is_fail() {
    let e = Evidence::falsified("F-QUAL-001", test_scenario(), "bad output", "", 100);
    assert!(e.outcome.is_fail());
}

Pattern: EvidenceCollector

#[test]
fn collector_counts_outcomes() {
    let mut collector = EvidenceCollector::new();
    collector.add(Evidence::corroborated("F-001", test_scenario(), "", 0));
    collector.add(Evidence::falsified("F-002", test_scenario(), "fail", "", 0));
    assert_eq!(collector.pass_count(), 1);
    assert_eq!(collector.fail_count(), 1);
    assert_eq!(collector.total(), 2);
}

Pattern: ExecutionConfig construction in tests

#[test]
fn executor_respects_timeout() {
    let config = ExecutionConfig {
        default_timeout_ms: 5000,
        dry_run: true,
        ..Default::default()
    };
    let mut executor = Executor::with_config(config);
    // ...
}

Pattern: Custom CommandRunner for testing

When you need to test executor behavior with controlled subprocess responses:

struct MyTestRunner;

impl CommandRunner for MyTestRunner {
    fn run_inference(&self, model_path: &Path, prompt: &str,
                     max_tokens: u32, no_gpu: bool, extra_args: &[&str]) -> CommandOutput {
        CommandOutput::success("The answer is 4.\nCompleted in 100ms")
    }

    fn convert_model(&self, _source: &Path, _target: &Path) -> CommandOutput {
        CommandOutput::success("")
    }

    // MUST implement ALL 28 methods - see CommandRunner Trait section below
    // Most can stub with CommandOutput::success("")
    fn inspect_model(&self, _: &Path) -> CommandOutput { CommandOutput::success("") }
    fn validate_model(&self, _: &Path) -> CommandOutput { CommandOutput::success("") }
    // ... (all 28 methods)
}

#[test]
fn test_with_custom_runner() {
    let config = ExecutionConfig::default();
    let runner = Arc::(MyTestRunner);
      = Executor::(config, runner);
    
}

apr-qa-report (Scoring & Reports)

Key types: MqsScore, MqsCalculator, GatewayResult, CategoryScores

Pattern: MQS scoring

use crate::mqs::MqsCalculator;
use apr_qa_runner::evidence::{Evidence, EvidenceCollector};

#[test]
fn perfect_score_all_corroborated() {
    let mut collector = EvidenceCollector::new();
    collector.add(Evidence::corroborated("F-QUAL-001", scenario(), "ok", 100));
    collector.add(Evidence::corroborated("F-PERF-001", scenario(), "ok", 100));
    let score = MqsCalculator::calculate("test/model", collector.all());
    assert!(score.gateways_passed);
    assert!(score.raw_score > 0);
}

#[test]
fn gateway_failure_zeroes_score() {
    let mut collector = EvidenceCollector::new();
    collector.add(Evidence::crashed("G1-LOAD-001", scenario(), "segfault", 139, 100));
    let score = MqsCalculator::calculate(, collector.());
    (!score.gateways_passed);
    (score.raw_score, );
}

Pattern: JUnit report generation

#[test]
fn junit_report_valid_xml() {
    let collector = build_test_collector();
    let xml = junit::generate_report("test/model", collector.all());
    assert!(xml.starts_with("<?xml"));
    assert!(xml.contains("<testsuites"));
}

Pattern: Grade assertions

Be careful with float comparison - clippy float_cmp is strict. Use ranges:

// WRONG (clippy::float_cmp)
assert_eq!(score.normalized_score, 95.0);

// CORRECT
assert!(score.normalized_score >= 90.0);
assert!(score.normalized_score <= 100.0);

apr-qa-certify (Certification Tracking)

Key types: ModelCertification, CertificationStatus, SizeCategory

Pattern: CSV parsing

#[test]
fn parse_csv_round_trip() {
    let models = vec![ModelCertification { /* ... */ }];
    let csv = write_csv(&models);
    let parsed = parse_csv(&csv).unwrap();
    assert_eq!(parsed.len(), models.len());
    assert_eq!(parsed[0].model_id, models[0].model_id);
}

Pattern: README table generation

#[test]
fn generated_table_has_headers() {
    let models = vec![sample_model()];
    let table = generate_table(&models);
    assert!(table.contains("| Model |"));
    assert!(table.contains("| Status |"));
}

CommandRunner Trait (28 Methods)

When implementing a custom CommandRunner for tests, you MUST implement all 28 methods. There are currently 4 custom implementations in executor.rs tests that serve as reference.

Complete method list:

#	Method	Signature
1	run_inference	(&self, model: &Path, prompt: &str, max_tokens: u32, no_gpu: bool, extra_args: &[&str]) -> CommandOutput
2	convert_model	(&self, source: &Path, target: &Path) -> CommandOutput
3	inspect_model	(&self, model: &Path) -> CommandOutput
4	validate_model	(&self, model: &Path) -> CommandOutput
5	bench_model	(&self, model: &Path) -> CommandOutput
6	check_model	(&self, model: &Path) -> CommandOutput
7	profile_model	(&self, model: &Path, warmup: u32, measure: u32) -> CommandOutput
8	profile_ci	(&self, model: &Path, min_throughput: Option<f64>, max_p99: Option<f64>, warmup: u32, measure: u32) -> CommandOutput
9	diff_tensors	(&self, model_a: &Path, model_b: &Path, json: bool) -> CommandOutput
10	compare_inference	(&self, model_a: &Path, model_b: &Path, prompt: &str, max_tokens: u32, tolerance: f64) -> CommandOutput
11	profile_with_flamegraph	(&self, model: &Path, output: &Path, no_gpu: bool) -> CommandOutput
12	profile_with_focus	(&self, model: &Path, focus: &str, no_gpu: bool) -> CommandOutput
13	validate_model_strict	(&self, model: &Path) -> CommandOutput
14	fingerprint_model	(&self, model: &Path, json: bool) -> CommandOutput

Stub template for most methods:

fn method_name(&self, /* args */) -> CommandOutput {
    CommandOutput::success("")
}

When adding a new method to the trait: You must update ALL 4 custom implementations in executor.rs tests plus the MockCommandRunner in command.rs.

Clippy Landmine Reference

The workspace uses clippy::pedantic + clippy::nursery + strict custom rules. These are the lints that most commonly trip up new test code.

Workspace-Level Denials

Lint	Level	Impact
unsafe_code	deny	No unsafe anywhere, #![forbid(unsafe_code)] in lib.rs files
unwrap_used	deny	No .unwrap() in library code (allowed in tests via cfg_attr)
panic	deny	No panic!() in library code
expect_used	warn	Prefer map_err / ? over .expect()

Common Pedantic/Nursery Traps

Lint	What Triggers It	Fix
float_cmp	assert_eq!(f64, f64)	Use range: assert!(x >= 0.9 && x <= 1.0)
option_if_let_else	if let Some(x) = opt { a } else { b }	Use opt.map_or(b, |x| a)
manual_let_else	let x = match opt { Some(v) => v, None => return }	Use let Some(x) = opt else { return };
doc_link_with_quotes	/// See ["quoted"] in doc comments	Wrap in backticks: `"quoted"`
or_fun_call	.unwrap_or(String::new())	Use .unwrap_or_default()
cast_precision_loss	x as f64 when x is u64	Already #![allow]'d in most crates
cast_possible_truncation	x as u32 when x is u64	Already #![allow]'d in runner
missing_const_for_fn	Pure function without const	Already #![allow]'d in all crates
struct_excessive_bools	Struct with many bool fields	Already #![allow]'d on ExecutionConfig
too_many_lines	Function > 100 lines	Add #[allow(clippy::too_many_lines)]
too_many_arguments	Function with > 7 args	Add #[allow(clippy::too_many_arguments)]
needless_pass_by_value	fn f(s: String) when &str works	Already #![allow]'d in most crates

Test-Specific Allowances

These are already allowed in #[cfg(test)] blocks via cfg_attr:

• clippy::unwrap_used - OK to unwrap in tests
• clippy::expect_used - OK to expect in tests
• clippy::redundant_closure_for_method_calls
• clippy::redundant_clone
• clippy::float_cmp (only in apr-qa-report)
• clippy::uninlined_format_args (only in apr-qa-runner)
• clippy::cast_sign_loss (only in apr-qa-runner)

Per-Crate Allow Lists

Each crate has specific #![allow(...)] in its lib.rs. Check the relevant lib.rs before writing tests to know which lints are pre-allowed.

Most restrictive: apr-qa-certify (almost no allows) Most lenient: apr-qa-report (20+ allows for scoring math)

Evidence Constructor Cheat Sheet

corroborated(gate_id, scenario, output, duration_ms)     → 4 args, reason="Test passed"
falsified(gate_id, scenario, reason, output, duration_ms) → 5 args
timeout(gate_id, scenario, timeout_ms)                    → 3 args
crashed(gate_id, scenario, stderr, exit_code, duration_ms)→ 5 args
skipped(gate_id, scenario, reason)                        → 3 args

Key facts:

• Evidence.output is String, NOT Option<String>
• Evidence.stderr is Option<String> (only Some for Crashed)
• Evidence.exit_code is Option<i32> (Some(0) for corroborated, None for falsified)
• Constructor uses impl Into<String> so both &str and String work

Gate ID Conventions

Gate IDs map to MQS categories via prefix:

Prefix	Category	Max Points
F-QUAL-*	Quality	200
F-PERF-*	Performance	150
F-STAB-*	Stability	200
F-COMP-*	Compatibility	150
F-EDGE-*	Edge Cases	150
F-REGR-*	Regression	150
F-CONV-*	Compatibility (conversion)	150
F-CONV-RT*	Regression (round-trip)	150
F-CONTRACT-*	Compatibility (contract)	150
G0-*	Stability (integrity)	200
G1-* through G4-*	Gateway (zeroes all)	-

When writing tests, use F-{CATEGORY}-{NNN} format for gate IDs to ensure correct MQS category scoring.

Common Test Count Gotcha

When adding new test phases to the executor's execute() method (like contract tests, parity tests):

1. Existing tests that assert total_scenarios counts will break because the executor now runs more tests
2. Fix: Update the expected counts in affected tests
3. Prevention: Search for total_scenarios assertions before adding phases:

   pmat query --literal "total_scenarios" --exclude-tests --limit 10
   

ExecutionConfig Construction

In library code (apr-qa-cli/src/lib.rs): Constructed explicitly field-by-field, NO ..Default::default(). When adding a new field, you must update both construction sites in lib.rs.

In test code: Use ..Default::default():

let config = ExecutionConfig {
    dry_run: true,
    default_timeout_ms: 5000,
    ..Default::default()
};

Current field count: 21 fields. Check executor.rs line ~81 for the latest.

See Also

References

• test-patterns.md - Extended test pattern cookbook
• clippy-landmines.md - Full clippy configuration reference

Commands

make test           # Run all tests
make lint           # Clippy with zero warnings
make check          # Full gate: fmt + lint + test + docs
make coverage       # HTML coverage report
make coverage-check # Verify >= 95%

Key Files

File	Purpose
Cargo.toml (root)	Workspace lint configuration
crates/*/src/lib.rs	Per-crate allow lists
crates/apr-qa-runner/src/command.rs	CommandRunner trait (28 methods)
crates/apr-qa-runner/src/executor.rs	ExecutionConfig + 4 test runners
crates/apr-qa-runner/src/evidence.rs	Evidence constructors
scripts/coverage-check.sh	95% threshold check