Algorithms Detailed in the xingshaocheng/architect-awesome Repository: A Complete Backend Catalog

The xingshaocheng/architect-awesome repository catalogs over 15 algorithm categories—including sorting, graph theory, string matching, and distributed consensus protocols—in its README.md "常用算法" section.

The xingshaocheng/architect-awesome repository serves as a curated knowledge map for back-end architects, organizing essential computer science concepts into a navigable Markdown structure. Its comprehensive README.md dedicates a specific "常用算法" (Common Algorithms) section to documenting foundational and distributed systems algorithms critical for architectural decision-making. Understanding the algorithms detailed in the xingshaocheng/architect-awesome repository provides engineers with a centralized reference for both interview preparation and production system design.

Core Algorithm Categories in README.md

The central documentation resides in README.md under the anchor #常用算法, which functions as the primary index for all algorithmic content. Each subcategory uses stable markdown headers that serve as permanent deeplinks to specific algorithm families.

Sorting and Searching Algorithms

The #排序查找算法 section enumerates ten fundamental data structure algorithms. Comparison-based sorts include Quick Sort, Merge Sort, Heap Sort, Shell Sort, Bubble Sort, Selection Sort, and Insertion Sort. Non-comparison sorts cover Counting Sort, Bucket Sort, and Radix Sort. The section also documents Binary Search for O(log n) retrieval in ordered collections.

String Matching and Optimization Strategies

Dedicated headers cover pattern recognition and strategic optimization techniques:

• KMP Algorithm (#kmp-算法): Knuth-Morris-Pratt linear-time string pattern matching
• Greedy Algorithm (#贪心算法): Local optimization heuristics for combinatorial problems
• Backtracking (#回溯算法): Exhaustive search with state restoration for constraint satisfaction
• Pruning (#剪枝算法): Search space reduction via early termination conditions

Graph Theory Algorithms

Two critical anchors address network optimization problems:

• Minimum Spanning Tree (#最小生成树算法): Kruskal and Prim algorithms for connecting weighted graphs with minimal total edge cost
• Shortest Path (#最短路径算法): Dijkstra's algorithm for single-source shortest path computation in graphs with non-negative edge weights

Distributed Systems and Specialized Algorithms

Beyond classical computer science, the repository catalogs algorithms essential for modern distributed architectures and high-scale system design.

Consensus, Hashing, and Cryptography

• Distributed Consistency Algorithms (#分布式一致性算法): Documentation covers Paxos, Raft, and Gossip protocols for achieving consensus across distributed nodes
• Consistent Hashing (#一致性hash算法): Ring-based distribution strategies for load balancing and horizontal scaling
• Hash Functions (#哈希算法): References to common hash functions including MD5, SHA-1, and SHA-2

System Design Operational Algorithms

The README integrates algorithms for operational concerns under system architecture sections:

• Rate Limiting: Sliding Window, Leaky Bucket, and Token Bucket algorithms (referenced under the "限流" section)
• Cache Eviction: FIFO, LRU, and LFU replacement policies for cache management strategies
• Unique ID Generation: Snowflake-style distributed ID generation algorithms for primary key generation in sharded databases

Reference Implementation Patterns

While README.md functions strictly as a knowledge base rather than a code library, the documented algorithms follow standard implementation patterns. The following Java snippets illustrate the core mechanics of the algorithms cataloged in the repository.

Quick Sort Partition Strategy

public static void quickSort(int[] a, int lo, int hi) {
    if (lo < hi) {
        int p = partition(a, lo, hi);
        quickSort(a, lo, p - 1);
        quickSort(a, p + 1, hi);
    }
}

private static int partition(int[] a, int lo, int hi) {
    int pivot = a[hi];
    int i = lo;
    for (int j = lo; j < hi; j++) {
        if (a[j] <= pivot) swap(a, i++, j);
    }
    swap(a, i, hi);
    return i;
}

private static void swap(int[] a, int i, int j) { 
    int tmp = a[i]; a[i] = a[j]; a[j] = tmp; 
}

Binary Search Implementation

public static int binarySearch(int[] a, int target) {
    int lo = 0, hi = a.length - 1;
    while (lo <= hi) {
        int mid = (lo + hi) >>> 1;
        if (a[mid] == target) return mid;
        else if (a[mid] < target) lo = mid + 1;
        else hi = mid - 1;
    }
    return -1;
}

KMP Pattern Matching

public static int kmpSearch(String txt, String pat) {
    int[] lps = computeLPS(pat);
    int i = 0, j = 0;
    while (i < txt.length()) {
        if (pat.charAt(j) == txt.charAt(i)) { 
            i++; 
            j++; 
        }
        if (j == pat.length()) return i - j;
        else if (i < txt.length() && pat.charAt(j) != txt.charAt(i)) {
            if (j != 0) j = lps[j - 1];
            else i++;
        }
    }
    return -1;
}

private static int[] computeLPS(String pat) {
    int[] lps = new int[pat.length()];
    int len = 0, i = 1;
    while (i < pat.length()) {
        if (pat.charAt(i) == pat.charAt(len)) { 
            len++; 
            lps[i++] = len; 
        }
        else if (len != 0) len = lps[len - 1];
        else lps[i++] = 0;
    }
    return lps;
}

Dijkstra Shortest Path

public static int[] dijkstra(List<int[]>[] graph, int src) {
    int n = graph.length;
    int[] dist = new int[n];
    Arrays.fill(dist, Integer.MAX_VALUE);
    dist[src] = 0;
    PriorityQueue<int[]> pq = new PriorityQueue<>(Comparator.comparingInt(a -> a[1]));
    pq.offer(new int[]{src, 0});
    
    while (!pq.isEmpty()) {
        int[] cur = pq.poll();
        int u = cur[0];
        if (cur[1] != dist[u]) continue;
        
        for (int[] edge : graph[u]) {
            int v = edge[0], w = edge[1];
            if (dist[u] + w < dist[v]) {
                dist[v] = dist[u] + w;
                pq.offer(new int[]{v, dist[v]});
            }
        }
    }
    return dist;
}

Consistent Hash Ring

public class ConsistentHash<T> {
    private final SortedMap<Long, T> ring = new TreeMap<>();
    private final int replicas;
    
    public ConsistentHash(int replicas, Collection<T> nodes) {
        this.replicas = replicas;
        for (T node : nodes) add(node);
    }
    
    public void add(T node) {
        for (int i = 0; i < replicas; i++) {
            long hash = hash(node.toString() + i);
            ring.put(hash, node);
        }
    }
    
    public T get(String key) {
        if (ring.isEmpty()) return null;
        long hash = hash(key);
        SortedMap<Long, T> tail = ring.tailMap(hash);
        return tail.isEmpty() ? ring.get(ring.firstKey()) : tail.get(tail.firstKey());
    }
    
    private long hash(String s) { 
        try {
            return java.security.MessageDigest.getInstance("MD5")
                .digest(s.getBytes())[0];
        } catch (Exception e) { return 0; }
    }
}

Summary

• The xingshaocheng/architect-awesome repository documents 15+ algorithm categories in README.md under the "常用算法" section and specific sub-headers like #排序查找算法 and #分布式一致性算法.
• Classical algorithms include ten sorting varieties (Quick, Merge, Heap, Shell, Bubble, Selection, Insertion, Counting, Bucket, Radix), Binary Search, KMP string matching, and graph algorithms (Dijkstra, Kruskal, Prim).
• Distributed systems coverage spans consensus protocols (Paxos, Raft, Gossip), consistent hashing, cryptographic hashes (MD5, SHA-1/2), and operational algorithms for rate limiting, caching, and unique ID generation.
• Each algorithm entry in the source provides descriptive context and external reference links; the repository serves as a curated index rather than an implementation library.

Frequently Asked Questions

Does the repository contain actual algorithm implementations?

No, the xingshaocheng/architect-awesome repository functions strictly as a curated knowledge base. The README.md file provides descriptive catalogs, categorization, and external reference links for each algorithm, but does not ship executable source code or function implementations for the documented methods.

Which distributed consistency algorithms are detailed in the README?

According to the source code in README.md, the #分布式一致性算法 section documents Paxos, Raft, and Gossip protocols. These entries provide architectural explanations and external references suitable for designing fault-tolerant distributed systems.

How are the sorting algorithms organized in the documentation?

The sorting algorithms reside under the #排序查找算法 anchor in README.md. This section groups Selection Sort, Bubble Sort, Insertion Sort, Quick Sort, Merge Sort, Shell Sort, Heap Sort, Counting Sort, Bucket Sort, and Radix Sort together with Binary Search in a single categorical header dedicated to sorting and searching.

Are consistent hashing and rate-limiting algorithms included?

Yes, the repository documents Consistent Hashing explicitly under the #一致性hash算法 header. Rate-limiting strategies including Sliding Window, Leaky Bucket, and Token Bucket algorithms are implicitly covered within the "限流" (flow control) system design section of the README.

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  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}