pmat 3.11.0

PMAT - Zero-config AI context generation and code quality toolkit (CLI, MCP, HTTP)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137

#![cfg_attr(coverage_nightly, coverage(off))]
///! Popperian falsification audit retest - Vector 1.1 (Clone Army) and Vector 1.2 (Empty Shell)
use crate::services::lightweight_provability_analyzer::{
    FunctionId, LightweightProvabilityAnalyzer,
};

/// Get project root path for reliable test file resolution
fn project_file(relative: &str) -> String {
    let manifest = env!("CARGO_MANIFEST_DIR");
    format!("{manifest}/{relative}")
}

/// Vector 1.1: Clone Army - verify 5 real project functions produce spread > 0.01
#[tokio::test]
async fn audit_retest_v1_1_clone_army_spread() {
    let analyzer = LightweightProvabilityAnalyzer::new();

    // 5 real project functions with different profiles
    let functions = vec![
        // Pure fn: compute_confidence (no I/O, no unsafe, no unwrap)
        FunctionId {
            file_path: project_file("src/services/lightweight_provability_analyzer.rs"),
            function_name: "compute_confidence".to_string(),
            line_number: 503,
        },
        // I/O fn: read_function_source (reads files)
        FunctionId {
            file_path: project_file("src/services/lightweight_provability_analyzer.rs"),
            function_name: "read_function_source".to_string(),
            line_number: 391,
        },
        // Async fn: start_dashboard_server (async, network I/O)
        FunctionId {
            file_path: project_file("src/tdg/web_dashboard.rs"),
            function_name: "start_dashboard_server".to_string(),
            line_number: 429,
        },
        // Fn with .expect(): normalize_identifiers (uses regex .expect())
        FunctionId {
            file_path: project_file("src/services/similarity.rs"),
            function_name: "normalize_identifiers".to_string(),
            line_number: 360,
        },
        // Constructor: new() on LightweightProvabilityAnalyzer
        FunctionId {
            file_path: project_file("src/services/lightweight_provability_analyzer.rs"),
            function_name: "new".to_string(),
            line_number: 288,
        },
    ];

    let results = analyzer.analyze_incrementally(&functions).await;
    assert_eq!(results.len(), 5, "Expected 5 results");

    let scores: Vec<f64> = results.iter().map(|r| r.provability_score).collect();
    let min_score = scores.iter().cloned().fold(f64::INFINITY, f64::min);
    let max_score = scores.iter().cloned().fold(f64::NEG_INFINITY, f64::max);
    let spread = max_score - min_score;

    println!("=== VECTOR 1.1: Clone Army Retest ===");
    for (i, (func, score)) in functions.iter().zip(scores.iter()).enumerate() {
        println!("  [{i}] {:<40} => {:.4}", func.function_name, score);
    }
    println!("  min={min_score:.4}, max={max_score:.4}, spread={spread:.4}");

    assert!(
        spread > 0.01,
        "FAIL: spread {spread:.4} <= 0.01 -- scores are clone-army flat"
    );
    println!("  PASS: spread {spread:.4} > 0.01");
}

/// Vector 1.2a: Empty Shell - 50 empty fns should NOT score 1.0
#[tokio::test]
async fn audit_retest_v1_2_empty_shell_low_score() {
    let analyzer = LightweightProvabilityAnalyzer::new();

    // Create temp file with 50 empty functions
    let temp_dir = tempfile::tempdir().expect("create temp dir");
    let temp_file = temp_dir.path().join("empty_fns.rs");
    let mut content = String::new();
    for i in 0..50 {
        content.push_str(&format!("fn empty_fn_{i}() {{}}\n"));
    }
    std::fs::write(&temp_file, &content).expect("write temp file");

    let functions: Vec<FunctionId> = (0..50)
        .map(|i| FunctionId {
            file_path: temp_file.to_string_lossy().to_string(),
            function_name: format!("empty_fn_{i}"),
            line_number: i + 1,
        })
        .collect();

    let results = analyzer.analyze_incrementally(&functions).await;
    let avg_score: f64 =
        results.iter().map(|r| r.provability_score).sum::<f64>() / results.len() as f64;

    println!("=== VECTOR 1.2a: Empty Shell (50 empty fns) ===");
    println!("  avg_score = {avg_score:.4}");

    assert!(
        avg_score < 0.5,
        "FAIL: empty fns avg {avg_score:.4} >= 0.5 -- empty shell still scores high"
    );
    println!("  PASS: avg {avg_score:.4} < 0.5 (empty fns are penalized)");
}

/// Vector 1.2b: Nonexistent file FunctionIds should score < 0.5
#[tokio::test]
async fn audit_retest_v1_2_nonexistent_file() {
    let analyzer = LightweightProvabilityAnalyzer::new();

    let functions: Vec<FunctionId> = (0..10)
        .map(|i| FunctionId {
            file_path: "/tmp/this_file_does_not_exist_at_all.rs".to_string(),
            function_name: format!("ghost_fn_{i}"),
            line_number: i * 10,
        })
        .collect();

    let results = analyzer.analyze_incrementally(&functions).await;
    let avg_score: f64 =
        results.iter().map(|r| r.provability_score).sum::<f64>() / results.len() as f64;

    println!("=== VECTOR 1.2b: Nonexistent File ===");
    println!("  avg_score = {avg_score:.4}");
    for (i, r) in results.iter().enumerate() {
        println!("  [{i}] score={:.4}", r.provability_score);
    }

    assert!(
        avg_score < 0.5,
        "FAIL: nonexistent file avg {avg_score:.4} >= 0.5 -- phantom functions scored high"
    );
    println!("  PASS: avg {avg_score:.4} < 0.5 (nonexistent file correctly penalized)");
}