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Refactor edit strategies and confidence validation in unified diff processing

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- Enhanced the applyContextMatching and applyDMP functions to improve handling of context and edit changes.
- Updated confidence validation logic to ensure stricter checks, now requiring a minimum confidence of 1 for successful edits.
- Refined the way changes are processed, including better tracking of removal and addition changes.
- Improved the validation of edit results by incorporating strategy-specific checks and logging for better debugging.
- Adjusted the applyEdit function to ensure strategies are applied in a more robust manner, with clearer handling of debug mode.
This commit is contained in:
Daniel Riccio
2025-01-08 17:13:46 -05:00
parent 995692c48e
commit 9591ae062a
3 changed files with 136 additions and 105 deletions
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105
src/core/diff/strategies/new-unified/edit-strategies.ts
View File

@@ -36,35 +36,43 @@ export function applyContextMatching(hunk: Hunk, content: string[], matchPositio
const newResult = [...content.slice(0, matchPosition)];
let sourceIndex = matchPosition;
let previousIndent = '';
const hunkChanges = hunk.changes.filter(c => c.type !== 'context');
let lastChangeWasRemove = false; // Track if last change was a remove
for (const change of hunk.changes) {
if (change.type === 'context') {
newResult.push(change.originalLine || (change.indent + change.content));
previousIndent = change.indent;
sourceIndex++;
if (!lastChangeWasRemove) { // Only increment if we didn't just remove a line
sourceIndex++;
}
lastChangeWasRemove = false;
} else if (change.type === 'add') {
const indent = change.indent || inferIndentation(change.content,
hunk.changes.filter(c => c.type === 'context').map(c => c.originalLine || ''),
hunk.changes.filter(c => c.type === 'context' && c.originalLine).map(c => c.originalLine || ''),
previousIndent
);
newResult.push(indent + change.content);
previousIndent = indent;
lastChangeWasRemove = false;
} else if (change.type === 'remove') {
sourceIndex++;
lastChangeWasRemove = true;
}
}
newResult.push(...content.slice(sourceIndex));
// Validate the result
// Calculate the window size based on all changes
const windowSize = hunk.changes.length;
// Validate the result using the full window size
const similarity = getDMPSimilarity(
content.slice(matchPosition, matchPosition + hunk.changes.length).join('\n'),
newResult.slice(matchPosition, matchPosition + hunk.changes.length).join('\n')
content.slice(matchPosition, matchPosition + windowSize).join('\n'),
newResult.slice(matchPosition, matchPosition + windowSize).join('\n')
)
const confidence = validateEditResult(hunk, newResult.slice(matchPosition, matchPosition + hunkChanges.length + 1).join('\n'));
const confidence = validateEditResult(hunk, newResult.slice(matchPosition, matchPosition + windowSize).join('\n'), 'context');
return {
confidence: similarity * confidence,
@@ -80,45 +88,45 @@ export function applyDMP(hunk: Hunk, content: string[], matchPosition: number):
}
const dmp = new diff_match_patch();
const editRegion = content.slice(matchPosition, matchPosition + hunk.changes.length);
const editText = editRegion.join('\n');
// Build the target text sequentially like in applyContextMatching
let targetText = '';
let previousIndent = '';
// Build BEFORE block (context + removals)
const beforeLines = hunk.changes
.filter(change => change.type === 'context' || change.type === 'remove')
.map(change => change.originalLine || (change.indent + change.content));
for (const change of hunk.changes) {
if (change.type === 'context') {
targetText += (change.originalLine || (change.indent + change.content)) + '\n';
previousIndent = change.indent;
} else if (change.type === 'add') {
const indent = change.indent || inferIndentation(change.content,
hunk.changes.filter(c => c.type === 'context').map(c => c.originalLine || ''),
previousIndent
);
targetText += indent + change.content + '\n';
previousIndent = indent;
}
// Skip remove changes as they shouldn't appear in target
}
// Trim the trailing newline
targetText = targetText.replace(/\n$/, '');
const patch = dmp.patch_make(editText, targetText);
const [patchedText] = dmp.patch_apply(patch, editText);
// Build AFTER block (context + additions)
const afterLines = hunk.changes
.filter(change => change.type === 'context' || change.type === 'add')
.map(change => change.originalLine || (change.indent + change.content));
// Construct result with edited portion
// Convert to text
const beforeText = beforeLines.join('\n');
const afterText = afterLines.join('\n');
// Create the patch
const patch = dmp.patch_make(beforeText, afterText);
// Get the target text from content
const targetText = content.slice(matchPosition, matchPosition + beforeLines.length).join('\n');
// Apply the patch
const [patchedText] = dmp.patch_apply(patch, targetText);
// Split patched text back into lines
const patchedLines = patchedText.split('\n');
// Construct the final result
const newResult = [
...content.slice(0, matchPosition),
...patchedText.split('\n'),
...content.slice(matchPosition + hunk.changes.length)
...patchedLines,
...content.slice(matchPosition + beforeLines.length)
];
const similarity = getDMPSimilarity(editText, patchedText)
const confidence = validateEditResult(hunk, patchedText);
return {
// Calculate confidence
const similarity = getDMPSimilarity(beforeText, targetText);
const confidence = validateEditResult(hunk, patchedText, 'dmp');
return {
confidence: similarity * confidence,
result: newResult,
strategy: 'dmp'
@@ -228,7 +236,7 @@ async function applyGit(hunk: Hunk, content: string[], matchPosition: number): P
const osrResult = (await memfs.promises.readFile('/file.txt')).toString();
const osrSimilarity = getDMPSimilarity(editText, osrResult)
const confidence = validateEditResult(hunk, osrResult);
const confidence = validateEditResult(hunk, osrResult, 'git-osr');
if (osrSimilarity * confidence > 0.9) {
// Construct result with edited portion
@@ -273,7 +281,7 @@ async function applyGit(hunk: Hunk, content: string[], matchPosition: number): P
const srsoResult = (await memfs.promises.readFile('/file.txt')).toString();
const srsoSimilarity = getDMPSimilarity(editText, srsoResult)
const confidence = validateEditResult(hunk, srsoResult);
const confidence = validateEditResult(hunk, srsoResult, 'git-srso');
// Construct result with edited portion
const newResult = [
@@ -299,7 +307,7 @@ async function applyGit(hunk: Hunk, content: string[], matchPosition: number): P
}
// Main edit function that tries strategies sequentially
export async function applyEdit(hunk: Hunk, content: string[], matchPosition: number, confidence: number, debug: boolean = false): Promise<EditResult> {
export async function applyEdit(hunk: Hunk, content: string[], matchPosition: number, confidence: number, debug: string = 'false'): Promise<EditResult> {
// Don't attempt any edits if confidence is too low and not in debug mode
const MIN_CONFIDENCE = 0.9;
@@ -310,12 +318,12 @@ export async function applyEdit(hunk: Hunk, content: string[], matchPosition: nu
// Try each strategy in sequence until one succeeds
const strategies = [
{ name: 'context', apply: () => applyContextMatching(hunk, content, matchPosition) },
{ name: 'dmp', apply: () => applyDMP(hunk, content, matchPosition) },
{ name: 'context', apply: () => applyContextMatching(hunk, content, matchPosition) },
{ name: 'git', apply: () => applyGit(hunk, content, matchPosition) }
];
if (debug) {
if (debug !== '') {
// In debug mode, try all strategies and return the first success
const results = await Promise.all(strategies.map(async strategy => {
console.log(`Attempting edit with ${strategy.name} strategy...`);
@@ -324,18 +332,19 @@ export async function applyEdit(hunk: Hunk, content: string[], matchPosition: nu
return result;
}));
const successfulResults = results.filter(result => result.confidence > MIN_CONFIDENCE);
/*const successfulResults = results.filter(result => result.confidence > MIN_CONFIDENCE);
if (successfulResults.length > 0) {
const bestResult = successfulResults.reduce((best, current) =>
current.confidence > best.confidence ? current : best
);
return bestResult;
}
}*/
return results.find(result => result.strategy === debug) || { confidence: 0, result: content, strategy: 'none' };
} else {
// Normal mode - try strategies sequentially until one succeeds
for (const strategy of strategies) {
const result = await strategy.apply();
if (result.confidence > MIN_CONFIDENCE) {
if (result.confidence === 1) {
return result;
}
}

4
src/core/diff/strategies/new-unified/index.ts
View File

@@ -160,7 +160,7 @@ Your diff here
startLine?: number,
endLine?: number
): Promise<DiffResult> {
const MIN_CONFIDENCE = 0.9
const MIN_CONFIDENCE = 1
const parsedDiff = this.parseUnifiedDiff(diffContent)
const originalLines = originalContent.split("\n")
let result = [...originalLines]
@@ -170,7 +170,7 @@ Your diff here
const { index: matchPosition, confidence } = findBestMatch(contextStr, result)
const editResult = await applyEdit(hunk, result, matchPosition, confidence)
if (editResult.confidence > MIN_CONFIDENCE) {
if (editResult.confidence >= MIN_CONFIDENCE) {
result = editResult.result
} else {
return { success: false, error: `Failed to apply edit using ${editResult.strategy} strategy` }

132
src/core/diff/strategies/new-unified/search-strategies.ts
View File

@@ -15,8 +15,8 @@ const MIN_CONFIDENCE = 0.95;
// Helper function to prepare search string from context
export function prepareSearchString(changes: Change[]): string {
const lines = changes
.filter(c => c.type === 'context' || c.type === 'remove')
.map(c => c.content);
.filter((c) => c.type === 'context' || c.type === 'remove')
.map((c) => c.content);
return lines.join('\n');
}
@@ -42,43 +42,42 @@ export function getDMPSimilarity(original: string, modified: string): number {
// Example: If similarity is 0.8 and MIN_CONFIDENCE is 0.95,
// returns 0.1 (0.5 * (1 - 0.8)) to reduce confidence proportionally but with less impact.
// If similarity >= MIN_CONFIDENCE, returns 0 (no reduction).
export function validateEditResult(hunk: Hunk, result: string): number {
export function validateEditResult(hunk: Hunk, result: string, strategy: string): number {
const hunkDeepCopy: Hunk = JSON.parse(JSON.stringify(hunk));
// Create skeleton of original content (context + removed lines)
const originalSkeleton = hunkDeepCopy.changes
.filter(change => change.type === 'context' || change.type === 'remove')
.map(change => change.content)
.filter((change) => change.type === 'context' || change.type === 'remove')
.map((change) => change.content)
.join('\n');
// Create skeleton of expected result (context + added lines)
const expectedSkeleton = hunkDeepCopy.changes
.filter(change => change.type === 'context' || change.type === 'add')
.map(change => change.content)
.filter((change) => change.type === 'context' || change.type === 'add')
.map((change) => change.content)
.join('\n');
// Compare with original content
const originalSimilarity = evaluateSimilarity(originalSkeleton, result);
// If result is too similar to original, it means changes weren't applied
if (originalSimilarity > 0.9) {
console.log('Result too similar to original content:', originalSimilarity);
return 0.5; // Significant confidence reduction
console.log('originalSimilarity ', strategy, originalSimilarity);
// If original similarity is 1, it means changes weren't applied
if (originalSimilarity > 0.97) {
if (originalSimilarity === 1) {
return 0.5; // Significant confidence reduction
} else {
return 0.8;
}
}
// Compare with expected result
const expectedSimilarity = evaluateSimilarity(expectedSkeleton, result);
console.log('Original similarity:', originalSimilarity);
console.log('Expected similarity:', expectedSimilarity);
console.log('originalSkeleton:', originalSkeleton);
console.log('expectedSkeleton:', expectedSkeleton);
console.log('result:', result);
console.log('expectedSimilarity', strategy, expectedSimilarity);
// Scale between 0.98 and 1.0 (4% impact) based on expected similarity
const multiplier = expectedSimilarity < MIN_CONFIDENCE
? 0.96 + (0.04 * expectedSimilarity)
: 1;
const multiplier =
expectedSimilarity < MIN_CONFIDENCE ? 0.96 + 0.04 * expectedSimilarity : 1;
return multiplier;
}
@@ -86,44 +85,59 @@ export function validateEditResult(hunk: Hunk, result: string): number {
// Helper function to validate context lines against original content
function validateContextLines(searchStr: string, content: string): number {
// Extract just the context lines from the search string
const contextLines = searchStr.split('\n')
.filter(line => !line.startsWith('-')); // Exclude removed lines
const contextLines = searchStr
.split('\n')
.filter((line) => !line.startsWith('-')); // Exclude removed lines
// Compare context lines with content
const similarity = evaluateSimilarity(contextLines.join('\n'), content);
// Context lines must match very closely, or confidence drops significantly
return similarity < MIN_CONFIDENCE ? similarity * 0.3 : similarity;
}
// Exact match strategy
export function findExactMatch(searchStr: string, content: string[], startIndex: number = 0): SearchResult {
export function findExactMatch(
searchStr: string,
content: string[],
startIndex: number = 0
): SearchResult {
const contentStr = content.slice(startIndex).join('\n');
const searchLines = searchStr.split('\n');
const exactMatch = contentStr.indexOf(searchStr);
if (exactMatch !== -1) {
const matchedContent = content.slice(
startIndex + contentStr.slice(0, exactMatch).split('\n').length - 1,
startIndex + contentStr.slice(0, exactMatch).split('\n').length - 1 + searchLines.length
).join('\n');
const matchedContent = content
.slice(
startIndex + contentStr.slice(0, exactMatch).split('\n').length - 1,
startIndex +
contentStr.slice(0, exactMatch).split('\n').length -
1 +
searchLines.length
)
.join('\n');
const similarity = getDMPSimilarity(searchStr, matchedContent);
const contextSimilarity = validateContextLines(searchStr, matchedContent);
const confidence = Math.min(similarity, contextSimilarity);
return {
index: startIndex + contentStr.slice(0, exactMatch).split('\n').length - 1,
index:
startIndex + contentStr.slice(0, exactMatch).split('\n').length - 1,
confidence,
strategy: 'exact'
strategy: 'exact',
};
}
return { index: -1, confidence: 0, strategy: 'exact' };
}
// String similarity strategy
export function findSimilarityMatch(searchStr: string, content: string[], startIndex: number = 0): SearchResult {
export function findSimilarityMatch(
searchStr: string,
content: string[],
startIndex: number = 0
): SearchResult {
const searchLines = searchStr.split('\n');
let bestScore = 0;
let bestIndex = -1;
@@ -136,7 +150,7 @@ export function findSimilarityMatch(searchStr: string, content: string[], startI
const similarity = getDMPSimilarity(searchStr, windowStr);
const contextSimilarity = validateContextLines(searchStr, windowStr);
const adjustedScore = Math.min(similarity, contextSimilarity) * score;
if (adjustedScore > bestScore) {
bestScore = adjustedScore;
bestIndex = i;
@@ -144,33 +158,37 @@ export function findSimilarityMatch(searchStr: string, content: string[], startI
}
}
return {
index: bestIndex,
return {
index: bestIndex,
confidence: bestIndex !== -1 ? bestScore : 0,
strategy: 'similarity'
strategy: 'similarity',
};
}
// Levenshtein strategy
export function findLevenshteinMatch(searchStr: string, content: string[], startIndex: number = 0): SearchResult {
export function findLevenshteinMatch(
searchStr: string,
content: string[],
startIndex: number = 0
): SearchResult {
const searchLines = searchStr.split('\n');
const candidates = [];
for (let i = startIndex; i < content.length - searchLines.length + 1; i++) {
candidates.push(content.slice(i, i + searchLines.length).join('\n'));
}
if (candidates.length > 0) {
const closestMatch = closest(searchStr, candidates);
const index = startIndex + candidates.indexOf(closestMatch);
const similarity = getDMPSimilarity(searchStr, closestMatch);
const contextSimilarity = validateContextLines(searchStr, closestMatch);
const confidence = Math.min(similarity, contextSimilarity) * 0.7; // Still apply Levenshtein penalty
return {
index,
const confidence = Math.min(similarity, contextSimilarity) * 0.7; // Still apply Levenshtein penalty
return {
index,
confidence,
strategy: 'levenshtein'
strategy: 'levenshtein',
};
}
@@ -178,21 +196,25 @@ export function findLevenshteinMatch(searchStr: string, content: string[], start
}
// Main search function that tries all strategies
export function findBestMatch(searchStr: string, content: string[], startIndex: number = 0): SearchResult {
export function findBestMatch(
searchStr: string,
content: string[],
startIndex: number = 0
): SearchResult {
const strategies = [
findExactMatch,
findSimilarityMatch,
findLevenshteinMatch
findLevenshteinMatch,
];
let bestResult: SearchResult = { index: -1, confidence: 0, strategy: 'none' };
for (const strategy of strategies) {
const result = strategy(searchStr, content, startIndex);
if (result.confidence > bestResult.confidence) {
bestResult = result;
}
}
return bestResult;
}
}