text_similarity.rs

  1use regex::Regex;
  2use std::{collections::HashMap, sync::LazyLock};
  3
  4use crate::reference::Reference;
  5
  6// TODO: Consider implementing sliding window similarity matching like
  7// https://github.com/sourcegraph/cody-public-snapshot/blob/8e20ac6c1460c08b0db581c0204658112a246eda/vscode/src/completions/context/retrievers/jaccard-similarity/bestJaccardMatch.ts
  8//
  9// That implementation could actually be more efficient - no need to track words in the window that
 10// are not in the query.
 11
 12static IDENTIFIER_REGEX: LazyLock<Regex> = LazyLock::new(|| Regex::new(r"\b\w+\b").unwrap());
 13
 14#[derive(Debug)]
 15pub struct IdentifierOccurrences {
 16    identifier_to_count: HashMap<String, usize>,
 17    total_count: usize,
 18}
 19
 20impl IdentifierOccurrences {
 21    pub fn within_string(code: &str) -> Self {
 22        Self::from_iterator(IDENTIFIER_REGEX.find_iter(code).map(|mat| mat.as_str()))
 23    }
 24
 25    #[allow(dead_code)]
 26    pub fn within_references(references: &[Reference]) -> Self {
 27        Self::from_iterator(
 28            references
 29                .iter()
 30                .map(|reference| reference.identifier.name.as_ref()),
 31        )
 32    }
 33
 34    pub fn from_iterator<'a>(identifier_iterator: impl Iterator<Item = &'a str>) -> Self {
 35        let mut identifier_to_count = HashMap::new();
 36        let mut total_count = 0;
 37        for identifier in identifier_iterator {
 38            // TODO: Score matches that match case higher?
 39            //
 40            // TODO: Also include unsplit identifier?
 41            for identifier_part in split_identifier(identifier) {
 42                identifier_to_count
 43                    .entry(identifier_part.to_lowercase())
 44                    .and_modify(|count| *count += 1)
 45                    .or_insert(1);
 46                total_count += 1;
 47            }
 48        }
 49        IdentifierOccurrences {
 50            identifier_to_count,
 51            total_count,
 52        }
 53    }
 54}
 55
 56// Splits camelcase / snakecase / kebabcase / pascalcase
 57//
 58// TODO: Make this more efficient / elegant.
 59fn split_identifier<'a>(identifier: &'a str) -> Vec<&'a str> {
 60    let mut parts = Vec::new();
 61    let mut start = 0;
 62    let chars: Vec<char> = identifier.chars().collect();
 63
 64    if chars.is_empty() {
 65        return parts;
 66    }
 67
 68    let mut i = 0;
 69    while i < chars.len() {
 70        let ch = chars[i];
 71
 72        // Handle explicit delimiters (underscore and hyphen)
 73        if ch == '_' || ch == '-' {
 74            if i > start {
 75                parts.push(&identifier[start..i]);
 76            }
 77            start = i + 1;
 78            i += 1;
 79            continue;
 80        }
 81
 82        // Handle camelCase and PascalCase transitions
 83        if i > 0 && i < chars.len() {
 84            let prev_char = chars[i - 1];
 85
 86            // Transition from lowercase/digit to uppercase
 87            if (prev_char.is_lowercase() || prev_char.is_ascii_digit()) && ch.is_uppercase() {
 88                parts.push(&identifier[start..i]);
 89                start = i;
 90            }
 91            // Handle sequences like "XMLParser" -> ["XML", "Parser"]
 92            else if i + 1 < chars.len()
 93                && ch.is_uppercase()
 94                && chars[i + 1].is_lowercase()
 95                && prev_char.is_uppercase()
 96            {
 97                parts.push(&identifier[start..i]);
 98                start = i;
 99            }
100        }
101
102        i += 1;
103    }
104
105    // Add the last part if there's any remaining
106    if start < identifier.len() {
107        parts.push(&identifier[start..]);
108    }
109
110    // Filter out empty strings
111    parts.into_iter().filter(|s| !s.is_empty()).collect()
112}
113
114pub fn jaccard_similarity<'a>(
115    mut set_a: &'a IdentifierOccurrences,
116    mut set_b: &'a IdentifierOccurrences,
117) -> f32 {
118    if set_a.identifier_to_count.len() > set_b.identifier_to_count.len() {
119        std::mem::swap(&mut set_a, &mut set_b);
120    }
121    let intersection = set_a
122        .identifier_to_count
123        .keys()
124        .filter(|key| set_b.identifier_to_count.contains_key(*key))
125        .count();
126    let union = set_a.identifier_to_count.len() + set_b.identifier_to_count.len() - intersection;
127    intersection as f32 / union as f32
128}
129
130pub fn overlap_coefficient<'a>(
131    mut set_a: &'a IdentifierOccurrences,
132    mut set_b: &'a IdentifierOccurrences,
133) -> f32 {
134    if set_a.identifier_to_count.len() > set_b.identifier_to_count.len() {
135        std::mem::swap(&mut set_a, &mut set_b);
136    }
137    let intersection = set_a
138        .identifier_to_count
139        .keys()
140        .filter(|key| set_b.identifier_to_count.contains_key(*key))
141        .count();
142    intersection as f32 / set_a.identifier_to_count.len() as f32
143}
144
145pub fn weighted_jaccard_similarity<'a>(
146    mut set_a: &'a IdentifierOccurrences,
147    mut set_b: &'a IdentifierOccurrences,
148) -> f32 {
149    if set_a.identifier_to_count.len() > set_b.identifier_to_count.len() {
150        std::mem::swap(&mut set_a, &mut set_b);
151    }
152
153    let mut numerator = 0;
154    let mut denominator_a = 0;
155    let mut used_count_b = 0;
156    for (symbol, count_a) in set_a.identifier_to_count.iter() {
157        let count_b = set_b.identifier_to_count.get(symbol).unwrap_or(&0);
158        numerator += count_a.min(count_b);
159        denominator_a += count_a.max(count_b);
160        used_count_b += count_b;
161    }
162
163    let denominator = denominator_a + (set_b.total_count - used_count_b);
164    if denominator == 0 {
165        0.0
166    } else {
167        numerator as f32 / denominator as f32
168    }
169}
170
171pub fn weighted_overlap_coefficient<'a>(
172    mut set_a: &'a IdentifierOccurrences,
173    mut set_b: &'a IdentifierOccurrences,
174) -> f32 {
175    if set_a.identifier_to_count.len() > set_b.identifier_to_count.len() {
176        std::mem::swap(&mut set_a, &mut set_b);
177    }
178
179    let mut numerator = 0;
180    for (symbol, count_a) in set_a.identifier_to_count.iter() {
181        let count_b = set_b.identifier_to_count.get(symbol).unwrap_or(&0);
182        numerator += count_a.min(count_b);
183    }
184
185    let denominator = set_a.total_count.min(set_b.total_count);
186    if denominator == 0 {
187        0.0
188    } else {
189        numerator as f32 / denominator as f32
190    }
191}
192
193#[cfg(test)]
194mod test {
195    use super::*;
196
197    #[test]
198    fn test_split_identifier() {
199        assert_eq!(split_identifier("snake_case"), vec!["snake", "case"]);
200        assert_eq!(split_identifier("kebab-case"), vec!["kebab", "case"]);
201        assert_eq!(split_identifier("PascalCase"), vec!["Pascal", "Case"]);
202        assert_eq!(split_identifier("camelCase"), vec!["camel", "Case"]);
203        assert_eq!(split_identifier("XMLParser"), vec!["XML", "Parser"]);
204    }
205
206    #[test]
207    fn test_similarity_functions() {
208        // 10 identifier parts, 8 unique
209        // Repeats: 2 "outline", 2 "items"
210        let set_a = IdentifierOccurrences::within_string(
211            "let mut outline_items = query_outline_items(&language, &tree, &source);",
212        );
213        // 14 identifier parts, 11 unique
214        // Repeats: 2 "outline", 2 "language", 2 "tree"
215        let set_b = IdentifierOccurrences::within_string(
216            "pub fn query_outline_items(language: &Language, tree: &Tree, source: &str) -> Vec<OutlineItem> {",
217        );
218
219        // 6 overlaps: "outline", "items", "query", "language", "tree", "source"
220        // 7 non-overlaps: "let", "mut", "pub", "fn", "vec", "item", "str"
221        assert_eq!(jaccard_similarity(&set_a, &set_b), 6.0 / (6.0 + 7.0));
222
223        // Numerator is one more than before due to both having 2 "outline".
224        // Denominator is the same except for 3 more due to the non-overlapping duplicates
225        assert_eq!(
226            weighted_jaccard_similarity(&set_a, &set_b),
227            7.0 / (7.0 + 7.0 + 3.0)
228        );
229
230        // Numerator is the same as jaccard_similarity. Denominator is the size of the smaller set, 8.
231        assert_eq!(overlap_coefficient(&set_a, &set_b), 6.0 / 8.0);
232
233        // Numerator is the same as weighted_jaccard_similarity. Denominator is the total weight of
234        // the smaller set, 10.
235        assert_eq!(weighted_overlap_coefficient(&set_a, &set_b), 7.0 / 10.0);
236    }
237}