Improve method name suggestions

Attempts to improve method name suggestions when a matching method name
is not found. The approach taken is use the Levenshtein distance and
account for substrings having a high distance but can sometimes be very
close to the intended method (eg. empty vs is_empty).

compiler/rustc_span/src/lev_distance.rs

@@ -46,6 +46,62 @@ pub fn lev_distance(a: &str, b: &str, limit: usize) -> Option<usize> {
     (dcol[m] <= limit).then_some(dcol[m])
 }
 
+/// Provides a word similarity score between two words that accounts for substrings being more
+/// meaningful than a typical Levenshtein distance. The lower the score, the closer the match.
+/// 0 is an identical match.
+///
+/// Uses the Levenshtein distance between the two strings and removes the cost of the length
+/// difference. If this is 0 then it is either a substring match or a full word match, in the
+/// substring match case we detect this and return `1`. To prevent finding meaningless substrings,
+/// eg. "in" in "shrink", we only perform this subtraction of length difference if one of the words
+/// is not greater than twice the length of the other. For cases where the words are close in size
+/// but not an exact substring then the cost of the length difference is discounted by half.
+///
+/// Returns `None` if the distance exceeds the limit.
+pub fn lev_distance_with_substrings(a: &str, b: &str, limit: usize) -> Option<usize> {
+    let n = a.chars().count();
+    let m = b.chars().count();
+
+    // Check one isn't less than half the length of the other. If this is true then there is a
+    // big difference in length.
+    let big_len_diff = (n * 2) < m || (m * 2) < n;
+    let len_diff = if n < m { m - n } else { n - m };
+    let lev = lev_distance(a, b, limit + len_diff)?;
+
+    // This is the crux, subtracting length difference means exact substring matches will now be 0
+    let score = lev - len_diff;
+
+    // If the score is 0 but the words have different lengths then it's a substring match not a full
+    // word match
+    let score = if score == 0 && len_diff > 0 && !big_len_diff {
+        1 // Exact substring match, but not a total word match so return non-zero
+    } else if !big_len_diff {
+        // Not a big difference in length, discount cost of length difference
+        score + (len_diff + 1) / 2
+    } else {
+        // A big difference in length, add back the difference in length to the score
+        score + len_diff
+    };
+
+    (score <= limit).then_some(score)
+}
+
+/// Finds the best match for given word in the given iterator where substrings are meaningful.
+///
+/// A version of [`find_best_match_for_name`] that uses [`lev_distance_with_substrings`] as the score
+/// for word similarity. This takes an optional distance limit which defaults to one-third of the
+/// given word.
+///
+/// Besides the modified Levenshtein, we use case insensitive comparison to improve accuracy
+/// on an edge case with a lower(upper)case letters mismatch.
+pub fn find_best_match_for_name_with_substrings(
+    candidates: &[Symbol],
+    lookup: Symbol,
+    dist: Option<usize>,
+) -> Option<Symbol> {
+    find_best_match_for_name_impl(true, candidates, lookup, dist)
+}
+
 /// Finds the best match for a given word in the given iterator.
 ///
 /// As a loose rule to avoid the obviously incorrect suggestions, it takes
@@ -54,11 +110,20 @@ pub fn lev_distance(a: &str, b: &str, limit: usize) -> Option<usize> {
 ///
 /// Besides Levenshtein, we use case insensitive comparison to improve accuracy
 /// on an edge case with a lower(upper)case letters mismatch.
-#[cold]
 pub fn find_best_match_for_name(
     candidates: &[Symbol],
     lookup: Symbol,
     dist: Option<usize>,
+) -> Option<Symbol> {
+    find_best_match_for_name_impl(false, candidates, lookup, dist)
+}
+
+#[cold]
+fn find_best_match_for_name_impl(
+    use_substring_score: bool,
+    candidates: &[Symbol],
+    lookup: Symbol,
+    dist: Option<usize>,
 ) -> Option<Symbol> {
     let lookup = lookup.as_str();
     let lookup_uppercase = lookup.to_uppercase();
@@ -74,7 +139,11 @@ pub fn find_best_match_for_name(
     let mut dist = dist.unwrap_or_else(|| cmp::max(lookup.len(), 3) / 3);
     let mut best = None;
     for c in candidates {
-        match lev_distance(lookup, c.as_str(), dist) {
+        match if use_substring_score {
+            lev_distance_with_substrings(lookup, c.as_str(), dist)
+        } else {
+            lev_distance(lookup, c.as_str(), dist)
+        } {
             Some(0) => return Some(*c),
             Some(d) => {
                 dist = d - 1;

compiler/rustc_span/src/lev_distance/tests.rs

@@ -27,6 +27,17 @@ fn test_lev_distance_limit() {
     assert_eq!(lev_distance("abc", "xyz", 2), None);
 }
 
+#[test]
+fn test_method_name_similarity_score() {
+    assert_eq!(lev_distance_with_substrings("empty", "is_empty", 1), Some(1));
+    assert_eq!(lev_distance_with_substrings("shrunk", "rchunks", 2), None);
+    assert_eq!(lev_distance_with_substrings("abc", "abcd", 1), Some(1));
+    assert_eq!(lev_distance_with_substrings("a", "abcd", 1), None);
+    assert_eq!(lev_distance_with_substrings("edf", "eq", 1), None);
+    assert_eq!(lev_distance_with_substrings("abc", "xyz", 3), Some(3));
+    assert_eq!(lev_distance_with_substrings("abcdef", "abcdef", 2), Some(0));
+}
+
 #[test]
 fn test_find_best_match_for_name() {
     use crate::create_default_session_globals_then;