Tuesday, August 23, 2016

Function Prgramming


http://www.jianshu.com/p/0379d6a18c2e

Preconditions

绝大多数public的函数对于传递给它们的参数都需要进行限制。例如,索引值不能为负数,对象引用不能为空等等。良好的设计应该保证“发生错误应尽快检测出来”。为此,常常会在函数入口处进行参数的合法性校验。
为了消除大量参数前置校验的重复代码,可以提取公共的工具类库,例如:
public final class Precoditions {
  private Precoditions() {
  }

  public static void checkArgument(boolean exp, String msg = "") {
    if (!exp) {
      throw new IllegalArgumentException(msg);
    }
  }

  public static <T> T requireNonNull(T obj, String msg = "") {
    if (obj == null)
      throw new NullPointerException(msg);
    return obj;
  }

  public static boolean isNull(Object obj) {
    return obj == null;
  }

  public static boolean nonNull(Object obj) {
    return obj != null;
  }
}
使用requireNonNull等工具函数时,常常import static,使其更具表达力。
import static Precoditions.*;
系统中大量存在前置校验的代码,例如:
public BigInteger mod(BigInteger m) {
  if (m.signum() <= 0)
    throw new IllegalArgumentException("must be positive: " + m);
  ...
}
可以被重构得更加整洁、紧凑,且富有表现力。
public BigInteger mod(BigInteger m) {
  checkArgument(m.signum() > 0 , "must be positive: " + m);
  ...
}
一个常见的误区就是:对所有参数都进行限制、约束和检查。我将其称为“缺乏自信”的表现,因为在一些场景下,这样的限制和检查纯属多余。
C++为例,如果public接口传递了指针,对该指针做前置校验无可厚非,但仅仅在此做一次校验,其在内部调用链上的所有private子函数,如果要传递此指针,应该将其变更为pass by reference;特殊地,如果是只读,为了做到编译时的安全,pass by const-reference更是明智之举。
可以得到一个推论,对于private的函数,你对其调用具有完全的控制,自然保证了其传递参数的有效性;如果非得对其private的参数进行前置校验,应该使用assert。例如:
private static void <T> sort(T a[], int offset, int length) {
  assert a != null;
  assert offset >= 0 && offset <= a.length;
  assert length >= 0 && length <= a.length - offset;

  ...
}

Avoid Pass/Return Null

private final List<Product> stock = new ArrayList<>();

public Product[] filter(Predicate<Product> pred) {
  if (stock.isEmpty()) return null;
  ...
}
客户端不得不为此校验返回值,否则将在运行时抛出NullPointerException异常。
Product[] fakes = repo.filter(Product::isFake);
if (fakes != null && Arrays.asList(fakes).contains(Product.STILTON)) {
  ...
}
经过社区的实践总结出,返回null的数组或列表是不明智的,而应该返回零长度的数组或列表。
private final List<Product> stock = new ArrayList<>();

private static final Product[] EMPTY = new Product[0]; 

public Product[] filter(Predicate<Product> pred) {
  if (stock.isEmpty()) return EMPTY;
  ...
}
对于返回值是List的,则应该使用Collections.emptyXXX的静态工厂方法,返回零长度的列表。
private final List<Product> stock = new ArrayList<>();

public Product[] filter(Predicate<Product> pred) {
  if (stock.isEmpty()) return Collections.emptyList();
  ...
}

Null Object

private final List<Product> stock = new ArrayList<>();

public Product[] filter(Predicate<Product> pred) {
  if (stock.isEmpty()) return Collections.emptyList();
  ...
}
Collections.emptyList()工厂方法返回的就是一个Null Object,它的实现大致是这样的。
public final class Collections {
  private Collections() {
  }

  private static class EmptyList<E> 
    extends AbstractList<E> 
    implements RandomAccess, Serializable {

    private static final long serialVersionUID = 8842843931221139166L;

    public Iterator<E> iterator() {
      return emptyIterator();
    }

    public ListIterator<E> listIterator() {
      return emptyListIterator();
    }

    public int size() {return 0;}
    public boolean isEmpty() {return true;}

    public boolean contains(Object obj) {return false;}
    public boolean containsAll(Collection<?> c) { return c.isEmpty(); }

    public Object[] toArray() { return new Object[0]; }

    public <T> T[] toArray(T[] a) {
      if (a.length > 0)
        a[0] = null;
      return a;
    }

    public E get(int index) {
      throw new IndexOutOfBoundsException("Index: "+index);
    }

    public boolean equals(Object o) {
      return (o instanceof List) && ((List<?>)o).isEmpty();
    }

    public int hashCode() { return 1; }

    private Object readResolve() {
      return EMPTY_LIST;
    }
  }

  @SuppressWarnings("rawtypes")
  public static final List EMPTY_LIST = new EmptyList<>();

  @SuppressWarnings("unchecked")
  public static final <T> List<T> emptyList() {
    return (List<T>) EMPTY_LIST;
  }
}
Null Object代表了一种例外,并且这样的例外具有特殊性,它是一个有效的对象,对于用户来说是透明的,是感觉不出来的。使用Null Object,遵循了"按照接口编程"的良好设计原则,并且让用户处理空和非空的情况得到了统一,使得因缺失null检查的错误拒之门外。

Monadic Option

Null Object虽然很优雅地使得空与非空得到和谐,但也存在一些难以忍受的情况。
  • 接口发生变化(例如新增加一个方法),代表Null Object的类也需要跟着变化;
  • Null Object在不同的场景下重复这一实现方式,其本质是一种模式的重复;
  • 有时候,引入Null Object使得设计变得更加复杂,往往得不偿失;

Option的引入

问题的本质在哪里?null代表的是一种空,与其对立的一面便是非空。如果将其放置在一个容器中,问题便得到了很完美的解决。也就是说,如果为空,则该容器为空容器;如果不为空,则该值包含在容器之中。
Scala语言表示,可以建立一个Option的容器。如果存在,则用Some表示;否则用None表示。
sealed abstract class Option[+A] {
  def isEmpty: Boolean
  def get: A
}

case class Some[+A](x: A) extends Option[A] {
  def isEmpty = false
  def get = x
}

case object None extends Option[Nothing] {
  def isEmpty = true
  def get = throw new NoSuchElementException("None.get")
}
这样的表示有如下几个方面的好处:
  • 对于存在与不存在的值在类型系统中得以表示;
  • 显式地表达了不存在的语义;
  • 编译时保证错误的发生;
问题并没有那么简单,如果如下使用,并没有发挥出Option的威力。
def double(num: Option[Int]) = {
  num match {
    Some(n) => Some(n*2)
    None => None
  }
}
Option视为容器,让其处理Some/None得到统一性和一致性。
def double(num: Option[Int]) = num.map(_*2)
也可以使用for Comprehension,在某些场景下将更加简洁、漂亮。
def double(num: Option[Int]) = for (n <- num) yield(n*2)

Option的本质

通过上例的可以看出来,Option本质上是一个Monad,它是一种函数式的设计模式。用Java8简单地形式化一下,可以如下形式化地描述一个Monad
interface M<A> {
  M<B> flatMap(Function<A, M<B>> f);

  default M<B> map(Function<A, B> f) {
    return flatMap(a -> unit(f(a)));
  }

  static M<A> unit(A a) {
    ...
  }
}
同时满足以下三条规则:
  • 右单位元(identity),既对于任意的Monad m,则m.flatMap(unit) <=> m
  • 左单位元(unit),既对于任意的Monad m,则unit(v).flatMap(f) <=> f(v)
  • 结合律,既对于任意的Monad m, 则m.flatMap(g).flatMap(h) <=> m.flatMap(x => g(x).flatMap(h))
在这里,我们将Monad的数学语义简化,为了更深刻的了解Monad的本质,必须深入理解Cathegory Theory,这好比你要吃披萨的烹饪精髓,得学习意大利的文化。但这对于大部分的程序员要求优点过高,但不排除部分程序员追求极致。

Option的实现

Option的设计与List相似,有如下几个方面需要注意:
  • Option是一个Immutablity Container,或者是一个函数式的数据结构;
  • sealed保证其类型系统的封闭性;
  • Option[+A]类型参数是协变的,使得None可以成为任意Option[+A]的子对象;
  • 可以被for Comprehension调用;
sealed abstract class Option[+A] { self =>
  def isEmpty: Boolean
  def get: A

  final def map[B](f: A => B): Option[B] =
    if (isEmpty) None else Some(f(this.get))

  final def flatMap[B](f: A => Option[B]): Option[B] =
    if (isEmpty) None else f(this.get)

  ......
}

case class Some[+A](x: A) extends Option[A] {
  def isEmpty = false
  def get = x
}

case object None extends Option[Nothing] {
  def isEmpty = true
  def get = throw new NoSuchElementException("None.get")
}

for Comprehension的本质

for Comprehension其实是对具有foreach, map, flatMap, withFilter访问方法的容器的一个语法糖。
首先,pat <- expr的生成器被解释为:
// pat <- expr
pat <- expr.withFilter { case pat => true; case _ => false }
如果存在一个生成器和yield语句,则解释为:
// for (pat <- expr1) yield expr2
expr1.map{ case pat => expr2 }
如果存在多个生成器,则解释为:
// for (pat1 <- expr1; pat2 <- expr2) yield exprN
expr.flatMap { case pat1 => for (pat2 <- expr2) yield exprN }
expr.flatMap { case pat1 => expr2.map { case pat2 =>  exprN }}
对于for loop,可解释为:
// for (pat1 <- expr1; pat2 <- expr2;...) exprN
expr.foreach { case pat1 => for (pat2 <- expr2; ...) yield exprN }
对于包含guard的生成器,可解释为:
// pat1 <- expr1 if guard
pat1 <- expr1.withFilter((arg1, arg2, ...) => guard)

JDK8 Optional
public final class Optional<T> {
    private static final Optional<?> EMPTY = new Optional<>();
    private final T value;
    private Optional() {
        this.value = null;
    }
    public static<T> Optional<T> empty() {
        @SuppressWarnings("unchecked")
        Optional<T> t = (Optional<T>) EMPTY;
        return t;
    }
    private Optional(T value) {
        this.value = Objects.requireNonNull(value);
    }
    public static <T> Optional<T> of(T value) {
        return new Optional<>(value);
    }
    public static <T> Optional<T> ofNullable(T value) {
        return value == null ? empty() : of(value);
    }
    public T get() {
        if (value == null) {
            throw new NoSuchElementException("No value present");
        }
        return value;
    }
    public boolean isPresent() {
        return value != null;
    }
    public void ifPresent(Consumer<? super T> consumer) {
        if (value != null)
            consumer.accept(value);
    }
    public Optional<T> filter(Predicate<? super T> predicate) {
        Objects.requireNonNull(predicate);
        if (!isPresent())
            return this;
        else
            return predicate.test(value) ? this : empty();
    }
    public<U> Optional<U> map(Function<? super T, ? extends U> mapper) {
        Objects.requireNonNull(mapper);
        if (!isPresent())
            return empty();
        else {
            return Optional.ofNullable(mapper.apply(value));
        }
    }
    public<U> Optional<U> flatMap(Function<? super T, Optional<U>> mapper) {
        Objects.requireNonNull(mapper);
        if (!isPresent())
            return empty();
        else {
            return Objects.requireNonNull(mapper.apply(value));
        }
    }
    public T orElse(T other) {
        return value != null ? value : other;
    }
    public T orElseGet(Supplier<? extends T> other) {
        return value != null ? value : other.get();
    }
    public <X extends Throwable> T orElseThrow(Supplier<? extends X> exceptionSupplier) throws X {
        if (value != null) {
            return value;
        } else {
            throw exceptionSupplier.get();
        }
    }
    @Override
    public boolean equals(Object obj) {
        if (this == obj) {
            return true;
        }

        if (!(obj instanceof Optional)) {
            return false;
        }

        Optional<?> other = (Optional<?>) obj;
        return Objects.equals(value, other.value);
    }
    @Override
    public int hashCode() {
        return Objects.hashCode(value);
    }
}

http://www.jianshu.com/p/ea41fad02851
从原生的Java API创建线程谈起,讲述Scala对「控制结构」抽象的设计与实现.

创建线程

Java8之前,创建一个线程的典型方法如下。
Thread t = new Thread(new Runnable() {
  @Override
  public void run() {
    ...
  }
});

t.start();

使用Java8

使用Java8,可以除去一部分冗余的语法噪声,表达力得到了提升。
Thread t = new Thread(() -> {
  ...
});

t.start();

使用Scala

尝试使用Scala,对Java的接口进行包装处理,可以得到更加人性化的接口。首先定义runnable的控制结构:
def runnable(callback: => Unit) = new Runnable {
  override def run() = callback
}
然后,定义thread的关键字,实现Thread的创建。
def thread(callback: Unit) = new Thread(runnable(callback))
用户API也变得更加简洁,其感觉形如if, while等内置的控制结构,表达力非常强。
thread {
  ...
}

多样化

上例创建的是匿名的线程,如果想创建有名线程,并将其设置为Daemon线程,可以如下设计。
daemon("daemon-service-1") {
  ...
}
可以如下实现:
def daemon(name: String)(callback: => Unit): Thread = {
  val t = new Thread(runnable(callback), name)
  t.setDaemon(true)
  t.setUncaughtExceptionHandler(new Thread.UncaughtExceptionHandler {
    override def uncaughtException(t: Thread, e: Throwable) = 
      error(s"Uncaught exception in ${t.getName}:${e.toString}")
  })
  t
}
t.setUncaughtExceptionHandler的入参有点复杂,可以通过「提取函数」改善表达力。
def daemon(name: String)(callback: => Unit): Thread = {
  val t = new Thread(runnable(callback), name)
  t.setDaemon(true)
  t.setUncaughtExceptionHandler(handler)
  t
}

private def handler = new Thread.UncaughtExceptionHandler {
  override def uncaughtException(t: Thread, e: Throwable) = 
    error(s"Uncaught exception in ${thread.getName}:${e.toString}")
}
接下来,以此类推,可以提取「抽象结构」,改善程序的表现力。
private def handler = onException { (thread, except) =>
  error(s"Uncaught exception in ${thread.getName}:${except.toString}")
}

private def onException(h: (Thread, Throwable) => Unit) =
  new Thread.UncaughtExceptionHandler {
    override def uncaughtException(t: Thread, e: Throwable): Unit = h(t, e)
  }
也就是说,onExceptionrunnable, thread, daemon一样,是对Java接口的修饰或隐藏。

总结

Scala是设计DSL的利器。
借助于柯里化,及其漂亮的大括号语法,使得Scala创建自定义的「控制结构」变得非常容易;同时可以有效地除去冗余的语法噪声,提升代码的可读性。




    No comments:

    Post a Comment

    Labels

    GeeksforGeeks (976) Algorithm (811) LeetCode (654) to-do (599) Review (362) Classic Algorithm (334) Classic Interview (298) Dynamic Programming (263) Google Interview (233) LeetCode - Review (233) Tree (146) POJ (137) Difficult Algorithm (136) EPI (127) Different Solutions (119) Bit Algorithms (110) Cracking Coding Interview (110) Smart Algorithm (109) Math (91) HackerRank (85) Lintcode (83) Binary Search (73) Graph Algorithm (73) Greedy Algorithm (61) Interview Corner (61) Binary Tree (58) List (58) DFS (56) Algorithm Interview (53) Advanced Data Structure (52) Codility (52) ComProGuide (52) LeetCode - Extended (47) USACO (46) Geometry Algorithm (45) BFS (43) Data Structure (42) Mathematical Algorithm (42) ACM-ICPC (41) Jobdu (39) Interval (38) Recursive Algorithm (38) Stack (38) String Algorithm (38) Binary Search Tree (37) Knapsack (37) Codeforces (36) Introduction to Algorithms (36) Matrix (36) Must Known (36) Beauty of Programming (35) Sort (35) Space Optimization (34) Array (33) Trie (33) prismoskills (33) Backtracking (32) Segment Tree (32) Union-Find (32) HDU (31) Google Code Jam (30) Permutation (30) Puzzles (30) Array O(N) (29) Data Structure Design (29) Company-Zenefits (28) Microsoft 100 - July (28) to-do-must (28) Random (27) Sliding Window (27) GeeksQuiz (25) Logic Thinking (25) hihocoder (25) High Frequency (23) Palindrome (23) Algorithm Game (22) Company - LinkedIn (22) Graph (22) Hash (22) Queue (22) DFS + Review (21) TopCoder (21) Binary Indexed Trees (20) Brain Teaser (20) CareerCup (20) Company - Twitter (20) Pre-Sort (20) Company-Facebook (19) UVA (19) Probabilities (18) Follow Up (17) Codercareer (16) Company-Uber (16) Game Theory (16) Heap (16) Shortest Path (16) String Search (16) Topological Sort (16) Tree Traversal (16) itint5 (16) Iterator (15) Merge Sort (15) O(N) (15) Bisection Method (14) Difficult (14) Number (14) Number Theory (14) Post-Order Traverse (14) Priority Quieue (14) Amazon Interview (13) BST (13) Basic Algorithm (13) Codechef (13) Majority (13) mitbbs (13) Combination (12) Computational Geometry (12) KMP (12) Long Increasing Sequence(LIS) (12) Modify Tree (12) Reconstruct Tree (12) Reservoir Sampling (12) 尺取法 (12) AOJ (11) DFS+Backtracking (11) Fast Power Algorithm (11) Graph DFS (11) LCA (11) LeetCode - DFS (11) Ordered Stack (11) Princeton (11) Tree DP (11) 挑战程序设计竞赛 (11) Binary Search - Bisection (10) Company - Microsoft (10) Company-Airbnb (10) Euclidean GCD (10) Facebook Hacker Cup (10) HackerRank Easy (10) Reverse Thinking (10) Rolling Hash (10) SPOJ (10) Theory (10) Tutorialhorizon (10) X Sum (10) Coin Change (9) Divide and Conquer (9) Lintcode - Review (9) Mathblog (9) Max-Min Flow (9) Stack Overflow (9) Stock (9) Two Pointers (9) Book Notes (8) Bottom-Up (8) DP-Space Optimization (8) Graph BFS (8) LeetCode - DP (8) LeetCode Hard (8) Prefix Sum (8) Prime (8) Suffix Tree (8) System Design (8) Tech-Queries (8) Time Complexity (8) Use XOR (8) 穷竭搜索 (8) Algorithm Problem List (7) DFS+BFS (7) Facebook Interview (7) Fibonacci Numbers (7) Game Nim (7) HackerRank Difficult (7) Hackerearth (7) Interval Tree (7) Linked List (7) Longest Common Subsequence(LCS) (7) Math-Divisible (7) Miscs (7) O(1) Space (7) Probability DP (7) Radix Sort (7) Simulation (7) Xpost (7) n00tc0d3r (7) 蓝桥杯 (7) Bucket Sort (6) Catalan Number (6) Classic Data Structure Impl (6) DFS+DP (6) DP - Tree (6) How To (6) Interviewstreet (6) Kadane’s Algorithm (6) Knapsack - MultiplePack (6) Level Order Traversal (6) Manacher (6) Minimum Spanning Tree (6) One Pass (6) Programming Pearls (6) Quick Select (6) Rabin-Karp (6) Randomized Algorithms (6) Sampling (6) Schedule (6) Suffix Array (6) Threaded (6) reddit (6) AI (5) Art Of Programming-July (5) Big Data (5) Brute Force (5) Code Kata (5) Codility-lessons (5) Coding (5) Company - WMware (5) Crazyforcode (5) DFS+Cache (5) DP-Multiple Relation (5) DP-Print Solution (5) Dutch Flag (5) Fast Slow Pointers (5) Graph Cycle (5) Hash Strategy (5) Immutability (5) Inversion (5) Java (5) Kadane - Extended (5) Matrix Chain Multiplication (5) Microsoft Interview (5) Morris Traversal (5) Pruning (5) Quadtrees (5) Quick Partition (5) Quora (5) SPFA(Shortest Path Faster Algorithm) (5) Subarray Sum (5) Sweep Line (5) Traversal Once (5) TreeMap (5) jiuzhang (5) to-do-2 (5) 单调栈 (5) 树形DP (5) 1point3acres (4) Anagram (4) Approximate Algorithm (4) Backtracking-Include vs Exclude (4) Brute Force - Enumeration (4) Chess Game (4) Company-Amazon (4) Consistent Hash (4) Convex Hull (4) Cycle (4) DP-Include vs Exclude (4) Dijkstra (4) Distributed (4) Eulerian Cycle (4) Flood fill (4) Graph-Classic (4) HackerRank AI (4) Histogram (4) Kadane Max Sum (4) Knapsack - Mixed (4) Knapsack - Unbounded (4) Left and Right Array (4) MinMax (4) Multiple Data Structures (4) N Queens (4) Nerd Paradise (4) Parallel Algorithm (4) Practical Algorithm (4) Pre-Sum (4) Probability (4) Programcreek (4) Quick Sort (4) Spell Checker (4) Stock Maximize (4) Subsets (4) Sudoku (4) Symbol Table (4) TreeSet (4) Triangle (4) Water Jug (4) Word Ladder (4) algnotes (4) fgdsb (4) 最大化最小值 (4) A Star (3) Abbreviation (3) Algorithm - Brain Teaser (3) Algorithm Design (3) Anagrams (3) B Tree (3) Big Data Algorithm (3) Binary Search - Smart (3) Caterpillar Method (3) Coins (3) Company - Groupon (3) Company - Indeed (3) Cumulative Sum (3) DP-Fill by Length (3) DP-Two Variables (3) Dedup (3) Dequeue (3) Dropbox (3) Easy (3) Edit Distance (3) Expression (3) Finite Automata (3) Forward && Backward Scan (3) Github (3) GoLang (3) Include vs Exclude (3) Joseph (3) Jump Game (3) Knapsack-多重背包 (3) LeetCode - Bit (3) LeetCode - TODO (3) Linked List Merge Sort (3) LogN (3) Master Theorem (3) Maze (3) Min Cost Flow (3) Minesweeper (3) Missing Numbers (3) NP Hard (3) Online Algorithm (3) Pascal's Triangle (3) Pattern Match (3) Project Euler (3) Rectangle (3) Scala (3) SegmentFault (3) Stack - Smart (3) State Machine (3) Streaming Algorithm (3) Subset Sum (3) Subtree (3) Transform Tree (3) Two Pointers Window (3) Warshall Floyd (3) With Random Pointer (3) Word Search (3) bookkeeping (3) codebytes (3) Activity Selection Problem (2) Advanced Algorithm (2) AnAlgorithmADay (2) Application of Algorithm (2) Array Merge (2) BOJ (2) BT - Path Sum (2) Balanced Binary Search Tree (2) Bellman Ford (2) Binomial Coefficient (2) Bit Mask (2) Bit-Difficult (2) Bloom Filter (2) Book Coding Interview (2) Branch and Bound Method (2) Clock (2) Codesays (2) Company - Baidu (2) Complete Binary Tree (2) DFS+BFS, Flood Fill (2) DP - DFS (2) DP-3D Table (2) DP-Classical (2) DP-Output Solution (2) DP-Slide Window Gap (2) DP-i-k-j (2) DP-树形 (2) Distributed Algorithms (2) Divide and Conqure (2) Doubly Linked List (2) GoHired (2) Graham Scan (2) Graph - Bipartite (2) Graph BFS+DFS (2) Graph Coloring (2) Graph-Cut Vertices (2) Hamiltonian Cycle (2) Huffman Tree (2) In-order Traverse (2) Include or Exclude Last Element (2) Information Retrieval (2) Interview - Linkedin (2) Invariant (2) Islands (2) Knuth Shuffle (2) LeetCode - Recursive (2) Linked Interview (2) Linked List Sort (2) Longest SubArray (2) Lucene-Solr (2) MST (2) MST-Kruskal (2) Math-Remainder Queue (2) Matrix Power (2) Minimum Vertex Cover (2) Negative All Values (2) Number Each Digit (2) Numerical Method (2) Object Design (2) Order Statistic Tree (2) Palindromic (2) Parentheses (2) Parser (2) Peak (2) Programming (2) Range Minimum Query (2) Reuse Forward Backward (2) Robot (2) Rosettacode (2) Scan from right (2) Search (2) Shuffle (2) Sieve of Eratosthenes (2) SimHash (2) Simple Algorithm (2) Skyline (2) Spatial Index (2) Stream (2) Strongly Connected Components (2) Summary (2) TV (2) Tile (2) Traversal From End (2) Tree Sum (2) Tree Traversal Return Multiple Values (2) Word Break (2) Word Graph (2) Word Trie (2) Young Tableau (2) 剑指Offer (2) 数位DP (2) 1-X (1) 51Nod (1) Akka (1) Algorithm - How To (1) Algorithm - New (1) Algorithm Series (1) Algorithms Part I (1) Analysis of Algorithm (1) Array-Element Index Negative (1) Array-Rearrange (1) Auxiliary Array (1) Auxiliary Array: Inc&Dec (1) BACK (1) BK-Tree (1) BZOJ (1) Basic (1) Bayes (1) Beauty of Math (1) Big Integer (1) Big Number (1) Binary (1) Binary Tree Variant (1) Bipartite (1) Bit-Missing Number (1) BitMap (1) BitMap index (1) BitSet (1) Bug Free Code (1) BuildIt (1) C/C++ (1) CC Interview (1) Cache (1) Calculate Height at Same Recusrion (1) Cartesian tree (1) Check Tree Property (1) Chinese (1) Circular Buffer (1) Code Quality (1) Codesolutiony (1) Company - Alibaba (1) Company - Palantir (1) Company - WalmartLabs (1) Company-Apple (1) Company-Epic (1) Company-Salesforce (1) Company-Snapchat (1) Company-Yelp (1) Compression Algorithm (1) Concurrency (1) Convert BST to DLL (1) Convert DLL to BST (1) Custom Sort (1) Cyclic Replacement (1) DFS-Matrix (1) DP - Probability (1) DP Fill Diagonal First (1) DP-Difficult (1) DP-End with 0 or 1 (1) DP-Fill Diagonal First (1) DP-Graph (1) DP-Left and Right Array (1) DP-MaxMin (1) DP-Memoization (1) DP-Node All Possibilities (1) DP-Optimization (1) DP-Preserve Previous Value (1) DP-Print All Solution (1) Database (1) Detect Negative Cycle (1) Directed Graph (1) Do Two Things at Same Recusrion (1) Domino (1) Dr Dobb's (1) Duplicate (1) Equal probability (1) External Sort (1) FST (1) Failure Function (1) Fraction (1) Front End Pointers (1) Funny (1) Fuzzy String Search (1) Game (1) Generating Function (1) Generation (1) Genetic algorithm (1) GeoHash (1) Geometry - Orientation (1) Google APAC (1) Graph But No Graph (1) Graph Transpose (1) Graph Traversal (1) Graph-Coloring (1) Graph-Longest Path (1) Gray Code (1) HOJ (1) Hanoi (1) Hard Algorithm (1) How Hash (1) How to Test (1) Improve It (1) In Place (1) Inorder-Reverse Inorder Traverse Simultaneously (1) Interpolation search (1) Interview (1) Interview - Easy (1) Interview - Facebook (1) Isomorphic (1) JDK8 (1) K Dimensional Tree (1) Knapsack - Fractional (1) Knapsack - ZeroOnePack (1) Knight (1) Kosaraju’s algorithm (1) Kruskal (1) Kruskal MST (1) Kth Element (1) Least Common Ancestor (1) LeetCode - Binary Tree (1) LeetCode - Coding (1) LeetCode - Detail (1) LeetCode - Related (1) LeetCode Diffcult (1) Linked List Reverse (1) Linkedin (1) Linkedin Interview (1) Local MinMax (1) Logic Pattern (1) Longest Common Subsequence (1) Longest Common Substring (1) Longest Prefix Suffix(LPS) (1) Manhattan Distance (1) Map && Reverse Map (1) Math - Induction (1) Math-Multiply (1) Math-Sum Of Digits (1) Matrix - O(N+M) (1) Matrix BFS (1) Matrix Graph (1) Matrix Search (1) Matrix+DP (1) Matrix-Rotate (1) Max Min So Far (1) Median (1) Memory-Efficient (1) MinHash (1) MinMax Heap (1) Monotone Queue (1) Monto Carlo (1) Multi-Reverse (1) Multiple DFS (1) Multiple Tasks (1) Next Successor (1) Offline Algorithm (1) PAT (1) Parent-Only Tree (1) Partition (1) Path Finding (1) Patience Sort (1) Persistent (1) Pigeon Hole Principle (1) Power Set (1) Pratical Algorithm (1) Probabilistic Data Structure (1) Proof (1) Python (1) Queue & Stack (1) RSA (1) Ranking (1) Rddles (1) ReHash (1) Realtime (1) Recurrence Relation (1) Recursive DFS (1) Recursive to Iterative (1) Red-Black Tree (1) Region (1) Regular Expression (1) Resources (1) Reverse Inorder Traversal (1) Robin (1) Selection (1) Self Balancing BST (1) Similarity (1) Sort && Binary Search (1) String Algorithm. Symbol Table (1) String DP (1) String Distance (1) SubMatrix (1) Subsequence (1) System of Difference Constraints(差分约束系统) (1) TSP (1) Ternary Search Tree (1) Test (1) Thread (1) TimSort (1) Top-Down (1) Tournament (1) Tournament Tree (1) Transform Tree in Place (1) Tree Diameter (1) Tree Rotate (1) Trie + DFS (1) Trie and Heap (1) Trie vs Hash (1) Trie vs HashMap (1) Triplet (1) Two Data Structures (1) Two Stacks (1) USACO - Classical (1) USACO - Problems (1) UyHiP (1) Valid Tree (1) Vector (1) Wiggle Sort (1) Wikipedia (1) Yahoo Interview (1) ZOJ (1) baozitraining (1) codevs (1) cos126 (1) javabeat (1) jum (1) namic Programming (1) sqrt(N) (1) 两次dijkstra (1) 九度 (1) 二进制枚举 (1) 夹逼法 (1) 归一化 (1) 折半枚举 (1) 枚举 (1) 状态压缩DP (1) 男人八题 (1) 英雄会 (1) 逆向思维 (1)

    Popular Posts