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cobraambalaj
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webpack
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lib
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util
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/var/www/cobraambalaj/node_modules/webpack/lib/util
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ArrayHelpers.js
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ArrayQueue.js
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AsyncQueue.js
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binarySearchBounds.js
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cleverMerge.js
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comparators.js
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compileBooleanMatcher.js
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createHash.js
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DataURI.js
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deprecation.js
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deterministicGrouping.js
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extractUrlAndGlobal.js
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findGraphRoots.js
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fs.js
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Hash.js
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identifier.js
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internalSerializables.js
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IterableHelpers.js
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LazyBucketSortedSet.js
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LazySet.js
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makeSerializable.js
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MapHelpers.js
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memoize.js
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numberHash.js
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objectToMap.js
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ParallelismFactorCalculator.js
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processAsyncTree.js
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propertyAccess.js
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Queue.js
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registerExternalSerializer.js
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runtime.js
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Semaphore.js
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semver.js
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serialization.js
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SetHelpers.js
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smartGrouping.js
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SortableSet.js
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source.js
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StackedMap.js
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StackedSetMap.js
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StringXor.js
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TupleQueue.js
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TupleSet.js
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URLAbsoluteSpecifier.js
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Edit:
/var/www/cobraambalaj/node_modules/webpack/lib/util/deterministicGrouping.js
(11413B)
/* MIT License http://www.opensource.org/licenses/mit-license.php Author Tobias Koppers @sokra */ "use strict"; // Simulations show these probabilities for a single change // 93.1% that one group is invalidated // 4.8% that two groups are invalidated // 1.1% that 3 groups are invalidated // 0.1% that 4 or more groups are invalidated // // And these for removing/adding 10 lexically adjacent files // 64.5% that one group is invalidated // 24.8% that two groups are invalidated // 7.8% that 3 groups are invalidated // 2.7% that 4 or more groups are invalidated // // And these for removing/adding 3 random files // 0% that one group is invalidated // 3.7% that two groups are invalidated // 80.8% that 3 groups are invalidated // 12.3% that 4 groups are invalidated // 3.2% that 5 or more groups are invalidated /** * * @param {string} a key * @param {string} b key * @returns {number} the similarity as number */ const similarity = (a, b) => { const l = Math.min(a.length, b.length); let dist = 0; for (let i = 0; i < l; i++) { const ca = a.charCodeAt(i); const cb = b.charCodeAt(i); dist += Math.max(0, 10 - Math.abs(ca - cb)); } return dist; }; /** * @param {string} a key * @param {string} b key * @param {Set<string>} usedNames set of already used names * @returns {string} the common part and a single char for the difference */ const getName = (a, b, usedNames) => { const l = Math.min(a.length, b.length); let i = 0; while (i < l) { if (a.charCodeAt(i) !== b.charCodeAt(i)) { i++; break; } i++; } while (i < l) { const name = a.slice(0, i); const lowerName = name.toLowerCase(); if (!usedNames.has(lowerName)) { usedNames.add(lowerName); return name; } i++; } // names always contain a hash, so this is always unique // we don't need to check usedNames nor add it return a; }; /** * @param {Record<string, number>} total total size * @param {Record<string, number>} size single size * @returns {void} */ const addSizeTo = (total, size) => { for (const key of Object.keys(size)) { total[key] = (total[key] || 0) + size[key]; } }; /** * @param {Iterable<Node>} nodes some nodes * @returns {Record<string, number>} total size */ const sumSize = nodes => { const sum = Object.create(null); for (const node of nodes) { addSizeTo(sum, node.size); } return sum; }; const isTooBig = (size, maxSize) => { for (const key of Object.keys(size)) { const maxSizeValue = maxSize[key]; if (typeof maxSizeValue === "number") { if (size[key] > maxSizeValue) return true; } } return false; }; const isTooSmall = (size, minSize) => { for (const key of Object.keys(size)) { const minSizeValue = minSize[key]; if (typeof minSizeValue === "number") { if (size[key] < minSizeValue) return true; } } return false; }; const getToSmallTypes = (size, minSize) => { const types = new Set(); for (const key of Object.keys(size)) { const minSizeValue = minSize[key]; if (typeof minSizeValue === "number") { if (size[key] < minSizeValue) types.add(key); } } return types; }; const getNumberOfMatchingSizeTypes = (size, types) => { let i = 0; for (const key of Object.keys(size)) { if (types.has(key)) i++; } return i; }; const selectiveSizeSum = (size, types) => { let sum = 0; for (const key of Object.keys(size)) { if (types.has(key)) sum += size[key]; } return sum; }; /** * @template T */ class Node { /** * @param {T} item item * @param {string} key key * @param {Record<string, number>} size size */ constructor(item, key, size) { this.item = item; this.key = key; this.size = size; } } /** * @template T */ class Group { /** * @param {Node<T>[]} nodes nodes * @param {number[]} similarities similarities between the nodes (length = nodes.length - 1) * @param {Record<string, number>=} size size of the group */ constructor(nodes, similarities, size) { this.nodes = nodes; this.similarities = similarities; this.size = size || sumSize(nodes); /** @type {string} */ this.key = undefined; } /** * @param {function(Node): boolean} filter filter function * @returns {Node[]} removed nodes */ popNodes(filter) { const newNodes = []; const newSimilarities = []; const resultNodes = []; let lastNode; for (let i = 0; i < this.nodes.length; i++) { const node = this.nodes[i]; if (filter(node)) { resultNodes.push(node); } else { if (newNodes.length > 0) { newSimilarities.push( lastNode === this.nodes[i - 1] ? this.similarities[i - 1] : similarity(lastNode.key, node.key) ); } newNodes.push(node); lastNode = node; } } this.nodes = newNodes; this.similarities = newSimilarities; this.size = sumSize(newNodes); return resultNodes; } } /** * @param {Iterable<Node>} nodes nodes * @returns {number[]} similarities */ const getSimilarities = nodes => { // calculate similarities between lexically adjacent nodes /** @type {number[]} */ const similarities = []; let last = undefined; for (const node of nodes) { if (last !== undefined) { similarities.push(similarity(last.key, node.key)); } last = node; } return similarities; }; /** * @template T * @typedef {Object} GroupedItems<T> * @property {string} key * @property {T[]} items * @property {Record<string, number>} size */ /** * @template T * @typedef {Object} Options * @property {Record<string, number>} maxSize maximum size of a group * @property {Record<string, number>} minSize minimum size of a group (preferred over maximum size) * @property {Iterable<T>} items a list of items * @property {function(T): Record<string, number>} getSize function to get size of an item * @property {function(T): string} getKey function to get the key of an item */ /** * @template T * @param {Options<T>} options options object * @returns {GroupedItems<T>[]} grouped items */ module.exports = ({ maxSize, minSize, items, getSize, getKey }) => { /** @type {Group<T>[]} */ const result = []; const nodes = Array.from( items, item => new Node(item, getKey(item), getSize(item)) ); /** @type {Node<T>[]} */ const initialNodes = []; // lexically ordering of keys nodes.sort((a, b) => { if (a.key < b.key) return -1; if (a.key > b.key) return 1; return 0; }); // return nodes bigger than maxSize directly as group // But make sure that minSize is not violated for (const node of nodes) { if (isTooBig(node.size, maxSize) && !isTooSmall(node.size, minSize)) { result.push(new Group([node], [])); } else { initialNodes.push(node); } } if (initialNodes.length > 0) { const initialGroup = new Group(initialNodes, getSimilarities(initialNodes)); const problemTypes = getToSmallTypes(initialGroup.size, minSize); if (problemTypes.size > 0) { // We hit an edge case where the working set is already smaller than minSize // We merge problematic nodes with the smallest result node to keep minSize intact const problemNodes = initialGroup.popNodes( n => getNumberOfMatchingSizeTypes(n.size, problemTypes) > 0 ); // Only merge it with result nodes that have the problematic size type const possibleResultGroups = result.filter( n => getNumberOfMatchingSizeTypes(n.size, problemTypes) > 0 ); if (possibleResultGroups.length > 0) { const bestGroup = possibleResultGroups.reduce((min, group) => { const minMatches = getNumberOfMatchingSizeTypes(min, problemTypes); const groupMatches = getNumberOfMatchingSizeTypes( group, problemTypes ); if (minMatches !== groupMatches) return minMatches < groupMatches ? group : min; if ( selectiveSizeSum(min.size, problemTypes) > selectiveSizeSum(group.size, problemTypes) ) return group; return min; }); for (const node of problemNodes) bestGroup.nodes.push(node); bestGroup.nodes.sort((a, b) => { if (a.key < b.key) return -1; if (a.key > b.key) return 1; return 0; }); } else { // There are no other nodes with the same size types // We create a new group and have to accept that it's smaller than minSize result.push(new Group(problemNodes, null)); } } if (initialGroup.nodes.length > 0) { const queue = [initialGroup]; while (queue.length) { const group = queue.pop(); // only groups bigger than maxSize need to be splitted if (!isTooBig(group.size, maxSize)) { result.push(group); continue; } // find unsplittable area from left and right // going minSize from left and right // at least one node need to be included otherwise we get stuck let left = 1; let leftSize = Object.create(null); addSizeTo(leftSize, group.nodes[0].size); while (isTooSmall(leftSize, minSize)) { addSizeTo(leftSize, group.nodes[left].size); left++; } let right = group.nodes.length - 2; let rightSize = Object.create(null); addSizeTo(rightSize, group.nodes[group.nodes.length - 1].size); while (isTooSmall(rightSize, minSize)) { addSizeTo(rightSize, group.nodes[right].size); right--; } if (left - 1 > right) { // can't split group while holding minSize // because minSize is preferred of maxSize we return // the problematic nodes as result here even while it's too big // To avoid this make sure maxSize > minSize * 3 result.push(group); continue; } if (left <= right) { // when there is a area between left and right // we look for best split point // we split at the minimum similarity // here key space is separated the most let best = left - 1; let bestSimilarity = group.similarities[best]; for (let i = left; i <= right; i++) { const similarity = group.similarities[i]; if (similarity < bestSimilarity) { best = i; bestSimilarity = similarity; } } left = best + 1; right = best; } // create two new groups for left and right area // and queue them up const rightNodes = [group.nodes[right + 1]]; /** @type {number[]} */ const rightSimilarities = []; for (let i = right + 2; i < group.nodes.length; i++) { rightSimilarities.push(group.similarities[i - 1]); rightNodes.push(group.nodes[i]); } queue.push(new Group(rightNodes, rightSimilarities)); const leftNodes = [group.nodes[0]]; /** @type {number[]} */ const leftSimilarities = []; for (let i = 1; i < left; i++) { leftSimilarities.push(group.similarities[i - 1]); leftNodes.push(group.nodes[i]); } queue.push(new Group(leftNodes, leftSimilarities)); } } } // lexically ordering result.sort((a, b) => { if (a.nodes[0].key < b.nodes[0].key) return -1; if (a.nodes[0].key > b.nodes[0].key) return 1; return 0; }); // give every group a name const usedNames = new Set(); for (let i = 0; i < result.length; i++) { const group = result[i]; if (group.nodes.length === 1) { group.key = group.nodes[0].key; } else { const first = group.nodes[0]; const last = group.nodes[group.nodes.length - 1]; const name = getName(first.key, last.key, usedNames); group.key = name; } } // return the results return result.map(group => { /** @type {GroupedItems} */ return { key: group.key, items: group.nodes.map(node => node.item), size: group.size }; }); };
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