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e5034c3 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 | //! Deduplication logic for code search results across multiple queries.
//!
//! When performing batch semantic searches, the same code node may appear in
//! multiple queries with different scores. This module provides functionality
//! to deduplicate results, keeping each node only in the query where it has
//! the best score.
use std::cmp::Ordering;
use std::collections::HashMap;
use forge_domain::{Node, NodeId};
/// Tracks the best score for a node across multiple queries.
///
/// Implements `Ord` to enable comparison based on score quality.
/// Priority: relevance (higher is better) → distance (lower is better) →
/// similarity (higher is better) → query index (lower is better, tie-breaker).
#[derive(Debug, Clone, PartialEq)]
struct Score {
query_idx: usize,
relevance: Option<f32>,
distance: Option<f32>,
}
impl Score {
/// Creates a new `BestScore` from a query index and search result.
fn new(query_idx: usize, result: &Node) -> Self {
Self {
query_idx,
relevance: result.relevance,
distance: result.distance,
}
}
}
impl Eq for Score {}
impl PartialOrd for Score {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl Ord for Score {
fn cmp(&self, other: &Self) -> Ordering {
/// Helper to compare two `Option<f32>` values (higher is better).
///
/// # Returns
/// - `Some(Ordering)` if comparison is decisive
/// - `None` to continue to next comparison
fn compare(a: Option<f32>, b: Option<f32>) -> Option<Ordering> {
match (a, b) {
(Some(x), Some(y)) => match x.partial_cmp(&y)? {
Ordering::Equal => None, // Continue to next comparison
ord => Some(ord),
},
(Some(_), None) => Some(Ordering::Greater), // Having a value is better than None
(None, Some(_)) => Some(Ordering::Less), // None is worse than having a value
(None, None) => None, // Continue to next comparison
}
}
// Compare in priority order: relevance → distance → similarity → query index
compare(self.relevance, other.relevance) // Higher relevance is better
.or_else(|| compare(other.distance, self.distance)) // Lower distance is better (flipped)
.unwrap_or_else(|| self.query_idx.cmp(&other.query_idx).reverse()) // Lower query index wins (first query wins)
}
}
/// Deduplicates code search results across multiple queries.
///
/// Each node appears only once across all query results, kept in the query
/// where it has the highest score according to the `BestScore` ordering.
///
/// # Arguments
/// * `results` - Vector of search results per query (will be modified in place)
///
/// # Errors
/// Returns an error if node IDs cannot be extracted from results.
pub fn deduplicate_results(results: &mut [Vec<Node>]) {
// Track best score for each node_id across all queries
let mut best_scores: HashMap<NodeId, Score> = HashMap::new();
// First pass: find which query has the best score for each node
for (query_idx, query_results) in results.iter().enumerate() {
for result in query_results {
let current_score = Score::new(query_idx, result);
match best_scores.entry(result.node_id.clone()) {
std::collections::hash_map::Entry::Occupied(mut entry) => {
if current_score > *entry.get() {
entry.insert(current_score);
}
}
std::collections::hash_map::Entry::Vacant(entry) => {
entry.insert(current_score);
}
}
}
}
// Second pass: remove duplicates, keeping only in the query with best score
for (query_idx, query_results) in results.iter_mut().enumerate() {
query_results.retain(|result| {
best_scores
.get(&result.node_id)
.is_none_or(|best| best.query_idx == query_idx)
});
}
}
#[cfg(test)]
mod tests {
use forge_domain::{Node, NodeData};
use pretty_assertions::assert_eq;
use super::*;
/// Test fixture for creating a minimal `CodeSearchResult`.
fn result(node_id: &str) -> Node {
Node {
node_id: node_id.into(),
node: NodeData::FileChunk(forge_domain::FileChunk {
file_path: "test.rs".into(),
content: "test".into(),
start_line: 1,
end_line: 1,
}),
relevance: None,
distance: None,
}
}
#[test]
fn test_best_score_ordering_by_relevance() {
let score1 = Score::new(0, &result("node_a").relevance(0.9));
let score2 = Score::new(1, &result("node_a").relevance(0.8));
assert!(score1 > score2);
}
#[test]
fn test_best_score_ordering_by_distance_when_relevance_equal() {
let score1 = Score::new(0, &result("node_a").relevance(0.9).distance(0.1));
let score2 = Score::new(1, &result("node_a").relevance(0.9).distance(0.2));
assert!(score1 > score2);
}
#[test]
fn test_best_score_ordering_by_similarity_when_relevance_distance_equal() {
let score1 = Score::new(0, &result("node_a").relevance(0.9).distance(0.1));
let score2 = Score::new(1, &result("node_a").relevance(0.9).distance(0.1));
assert!(score1 > score2);
}
#[test]
fn test_best_score_ordering_by_query_idx_when_all_equal() {
let score1 = Score::new(0, &result("node_a").relevance(0.9).distance(0.1));
let score2 = Score::new(1, &result("node_a").relevance(0.9).distance(0.1));
assert!(score1 > score2); // Lower query index wins
}
#[test]
fn test_best_score_some_value_better_than_none() {
let score1 = Score::new(0, &result("node_a").relevance(0.5));
let score2 = Score::new(1, &result("node_a"));
assert!(score1 > score2);
}
#[test]
fn test_deduplicate_results_keeps_highest_relevance() {
let mut actual = vec![
vec![
result("node_a").relevance(0.8).distance(0.2),
result("node_b").relevance(0.7).distance(0.3),
],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_c").relevance(0.6).distance(0.4),
],
];
deduplicate_results(&mut actual);
let expected = vec![
vec![result("node_b").relevance(0.7).distance(0.3)],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_c").relevance(0.6).distance(0.4),
],
];
assert_eq!(actual, expected);
}
#[test]
fn test_deduplicate_multiple_duplicates() {
let mut actual = vec![
vec![
result("node_a").relevance(0.8).distance(0.2),
result("node_b").relevance(0.7).distance(0.3),
result("node_c").relevance(0.6).distance(0.4),
],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_b").relevance(0.5).distance(0.5),
result("node_d").relevance(0.95).distance(0.05),
],
];
deduplicate_results(&mut actual);
let expected = vec![
vec![
result("node_b").relevance(0.7).distance(0.3),
result("node_c").relevance(0.6).distance(0.4),
],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_d").relevance(0.95).distance(0.05),
],
];
assert_eq!(actual, expected);
}
#[test]
fn test_deduplicate_equal_relevance_uses_distance_tiebreaker() {
let mut actual = vec![
vec![
result("node_a").relevance(0.9).distance(0.2),
result("node_b").relevance(0.8).distance(0.2),
],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_c").relevance(0.7).distance(0.3),
],
];
deduplicate_results(&mut actual);
let expected = vec![
vec![result("node_b").relevance(0.8).distance(0.2)],
vec![
result("node_a").relevance(0.9).distance(0.1),
result("node_c").relevance(0.7).distance(0.3),
],
];
assert_eq!(actual, expected);
}
#[test]
fn test_deduplicate_across_three_queries() {
let mut actual = vec![
vec![
result("node_a").relevance(0.85).distance(0.15),
result("node_b").relevance(0.75).distance(0.25),
result("node_e").relevance(0.65).distance(0.35),
],
vec![
result("node_a").relevance(0.90).distance(0.10),
result("node_c").relevance(0.80).distance(0.20),
result("node_d").relevance(0.70).distance(0.30),
],
vec![
result("node_a").relevance(0.88).distance(0.12),
result("node_b").relevance(0.78).distance(0.22),
result("node_d").relevance(0.72).distance(0.28),
],
];
deduplicate_results(&mut actual);
let expected = vec![
vec![result("node_e").relevance(0.65).distance(0.35)],
vec![
result("node_a").relevance(0.90).distance(0.10),
result("node_c").relevance(0.80).distance(0.20),
],
vec![
result("node_b").relevance(0.78).distance(0.22),
result("node_d").relevance(0.72).distance(0.28),
],
];
assert_eq!(actual, expected);
}
#[test]
fn test_deduplicate_all_scores_equal_first_query_wins() {
let mut actual = vec![
vec![result("node_a").relevance(0.8).distance(0.2)],
vec![result("node_a").relevance(0.8).distance(0.2)],
];
deduplicate_results(&mut actual);
let expected = vec![vec![result("node_a").relevance(0.8).distance(0.2)], vec![]];
assert_eq!(actual, expected);
}
}
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