// Copyright 2022 The Go Authors. All rights reserved. // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package diff import ( "bytes" "fmt" "sort" "strings" ) // A pair is a pair of values tracked for both the x and y side of a diff. // It is typically a pair of line indexes. type pair struct{ x, y int } // Diff returns an anchored diff of the two texts old and new // in the “unified diff” format. If old and new are identical, // Diff returns a nil slice (no output). // // Unix diff implementations typically look for a diff with // the smallest number of lines inserted and removed, // which can in the worst case take time quadratic in the // number of lines in the texts. As a result, many implementations // either can be made to run for a long time or cut off the search // after a predetermined amount of work. // // In contrast, this implementation looks for a diff with the // smallest number of “unique” lines inserted and removed, // where unique means a line that appears just once in both old and new. // We call this an “anchored diff” because the unique lines anchor // the chosen matching regions. An anchored diff is usually clearer // than a standard diff, because the algorithm does not try to // reuse unrelated blank lines or closing braces. // The algorithm also guarantees to run in O(n log n) time // instead of the standard O(n²) time. // // Some systems call this approach a “patience diff,” named for // the “patience sorting” algorithm, itself named for a solitaire card game. // We avoid that name for two reasons. First, the name has been used // for a few different variants of the algorithm, so it is imprecise. // Second, the name is frequently interpreted as meaning that you have // to wait longer (to be patient) for the diff, meaning that it is a slower algorithm, // when in fact the algorithm is faster than the standard one. func Diff(oldName, old, newName, new string) []byte { if old == new { return nil } // Print diff header. var out bytes.Buffer fmt.Fprintf(&out, "diff %s %s\n", oldName, newName) fmt.Fprintf(&out, "--- %s\n", oldName) fmt.Fprintf(&out, "+++ %s\n", newName) out.Write(DiffNoHeader(old, new)) return out.Bytes() } func DiffNoHeader(old, new string) []byte { x := lines(old) y := lines(new) var out bytes.Buffer // Loop over matches to consider, // expanding each match to include surrounding lines, // and then printing diff chunks. // To avoid setup/teardown cases outside the loop, // tgs returns a leading {0,0} and trailing {len(x), len(y)} pair // in the sequence of matches. var ( done pair // printed up to x[:done.x] and y[:done.y] chunk pair // start lines of current chunk count pair // number of lines from each side in current chunk ctext []string // lines for current chunk ) for _, m := range tgs(x, y) { if m.x < done.x { // Already handled scanning forward from earlier match. continue } // Expand matching lines as far possible, // establishing that x[start.x:end.x] == y[start.y:end.y]. // Note that on the first (or last) iteration we may (or definitey do) // have an empty match: start.x==end.x and start.y==end.y. start := m for start.x > done.x && start.y > done.y && x[start.x-1] == y[start.y-1] { start.x-- start.y-- } end := m for end.x < len(x) && end.y < len(y) && x[end.x] == y[end.y] { end.x++ end.y++ } // Emit the mismatched lines before start into this chunk. // (No effect on first sentinel iteration, when start = {0,0}.) for _, s := range x[done.x:start.x] { ctext = append(ctext, "-"+s) count.x++ } for _, s := range y[done.y:start.y] { ctext = append(ctext, "+"+s) count.y++ } // If we're not at EOF and have too few common lines, // the chunk includes all the common lines and continues. const C = 3 // number of context lines if (end.x < len(x) || end.y < len(y)) && (end.x-start.x < C || (len(ctext) > 0 && end.x-start.x < 2*C)) { for _, s := range x[start.x:end.x] { ctext = append(ctext, " "+s) count.x++ count.y++ } done = end continue } // End chunk with common lines for context. if len(ctext) > 0 { n := end.x - start.x if n > C { n = C } for _, s := range x[start.x : start.x+n] { ctext = append(ctext, " "+s) count.x++ count.y++ } done = pair{start.x + n, start.y + n} // Format and emit chunk. // Convert line numbers to 1-indexed. // Special case: empty file shows up as 0,0 not 1,0. if count.x > 0 { chunk.x++ } if count.y > 0 { chunk.y++ } fmt.Fprintf(&out, "@@ -%d,%d +%d,%d @@\n", chunk.x, count.x, chunk.y, count.y) for _, s := range ctext { out.WriteString(s) } count.x = 0 count.y = 0 ctext = ctext[:0] } // If we reached EOF, we're done. if end.x >= len(x) && end.y >= len(y) { break } // Otherwise start a new chunk. chunk = pair{end.x - C, end.y - C} for _, s := range x[chunk.x:end.x] { ctext = append(ctext, " "+s) count.x++ count.y++ } done = end } return out.Bytes() } // lines returns the lines in the file x, including newlines. // If the file does not end in a newline, one is supplied // along with a warning about the missing newline. func lines(x string) []string { l := strings.SplitAfter(x, "\n") if l[len(l)-1] == "" { l = l[:len(l)-1] } else { // Treat last line as having a message about the missing newline attached, // using the same text as BSD/GNU diff (including the leading backslash). l[len(l)-1] += "\n\\ No newline at end of file\n" } return l } // tgs returns the pairs of indexes of the longest common subsequence // of unique lines in x and y, where a unique line is one that appears // once in x and once in y. // // The longest common subsequence algorithm is as described in // Thomas G. Szymanski, “A Special Case of the Maximal Common // Subsequence Problem,” Princeton TR #170 (January 1975), // available at https://research.swtch.com/tgs170.pdf. func tgs(x, y []string) []pair { // Count the number of times each string appears in a and b. // We only care about 0, 1, many, counted as 0, -1, -2 // for the x side and 0, -4, -8 for the y side. // Using negative numbers now lets us distinguish positive line numbers later. m := make(map[string]int) for _, s := range x { if c := m[s]; c > -2 { m[s] = c - 1 } } for _, s := range y { if c := m[s]; c > -8 { m[s] = c - 4 } } // Now unique strings can be identified by m[s] = -1+-4. // // Gather the indexes of those strings in x and y, building: // xi[i] = increasing indexes of unique strings in x. // yi[i] = increasing indexes of unique strings in y. // inv[i] = index j such that x[xi[i]] = y[yi[j]]. var xi, yi, inv []int for i, s := range y { if m[s] == -1+-4 { m[s] = len(yi) yi = append(yi, i) } } for i, s := range x { if j, ok := m[s]; ok && j >= 0 { xi = append(xi, i) inv = append(inv, j) } } // Apply Algorithm A from Szymanski's paper. // In those terms, A = J = inv and B = [0, n). // We add sentinel pairs {0,0}, and {len(x),len(y)} // to the returned sequence, to help the processing loop. J := inv n := len(xi) T := make([]int, n) L := make([]int, n) for i := range T { T[i] = n + 1 } for i := 0; i < n; i++ { k := sort.Search(n, func(k int) bool { return T[k] >= J[i] }) T[k] = J[i] L[i] = k + 1 } k := 0 for _, v := range L { if k < v { k = v } } seq := make([]pair, 2+k) seq[1+k] = pair{len(x), len(y)} // sentinel at end lastj := n for i := n - 1; i >= 0; i-- { if L[i] == k && J[i] < lastj { seq[k] = pair{xi[i], yi[J[i]]} k-- } } seq[0] = pair{0, 0} // sentinel at start return seq }