è¨ç®éçè« è¨ç®éå ¥éï¼æ¼ç¿åé¡ï¼ ãªã¹ã¹ã¡ã®æ¬ æ²³æå½°æ
è¨ç®éçè« è¨ç®éå ¥éï¼æ¼ç¿åé¡ï¼ ãªã¹ã¹ã¡ã®æ¬ æ²³æå½°æ
General-purpose algorithms and data structures, illustrated in Haskell. Part II Reflection without Remorse: A conceptual sequence as a tangible and efficient data structure Pure functional, mutation-free, efficient double-linked lists Total stream processors and their applications to all infinite streams Sparse Grids: multi-dimensional interpolation, approximation and integration Fast computation
2. è«æç´¹ä» â¢ Marc Sebban, et. al. âBLUE*: a Blue-Fringe Procedure for Learning DFA with Noisy Dataâ ⢠http://labh-curien.univ-st-etienne.fr/~janodet/ pub/tjs04.pdf ⢠ãã¤ãºãå«ãä¿¡å·åããç¶æ é·ç§»å³ãæ¨å® âãããä½ã®å½¹ã«ç«ã¤ã®ï¼ 13å¹´4æ14æ¥æ¥ææ¥ 3. è«æç´¹ä» â¢ Thomas Arts and Simon Thompson, âFrom Test Cases to FSMs: Augmented Test-driven Development and Property Inferenceâ ⢠http://www.cs.kent.ac.uk/pubs/2010/3041/content.pdf ⢠ã¦ããããã¹ãã®çµæ
id:echizen_tm ããã®è¨äºãã¦ã§ã¼ãã¬ããæ¨ã®å¹ççã§ç°¡åãªå®è£ "The Wavelet Matrix"ãããå§ã¾ã£ãã¦ã§ã¼ãã¬ããè¡åãã¼ã ããå年以ä¸ãéãããã§ã«æ¯ããæè¡ã¨ãã¦ç¢ºç«ããã¤ã¤ããæãããã¾ãã â¦åã§ãã æ¥æ¬ä»¥å¤ã§ã¯ããã¾ãæ¥ã¦ãã¾ããã çç±ã¨ãã¦ã¯ããã¯ãã¢ã«ãã¡ãããåã§ã¯åèªå¢çãæ確ã§ããããããã¡ãã®è¨äºã§æ¸ããã¦ãããããªããã¼ã¯ã¼ãåå²ã®é£æ度ãã¨ãã£ããã¨ããã¾ãåé¡ã«ãªããªãã¨ãããã¨ãããããããã¾ããã ã¾ããããããããã§å±æçã«æ¥ã¦ããã¦ã§ã¼ãã¬ããè¡åã§ãããæ¥æ¬èªãã¯ããã¨ããåèªå¢çã®ãªãè¨èªåã«ã¨ã£ã¦ã¯éè¦ãªãã¿ã§ããã¨æãããã解説è¨äºãæ¸ãç´ãã¦*1ã¿ããã¨æãã¾ãã ã¦ã§ã¼ãã¬ããè¡åã§ã§ããã㨠主ã¨ãªãæä½ã¯ãæååã«å¯¾ãã å®æ°æéã® rank() 㨠select()*2 ã§ãã rank() ã¯ããæ
20åã§ããã Purely Functional Data Structures k.inaba (http://www.kmonos.net/) Apr. 4, 2010 ãããã 㤠ã 㥠㼠㿠ã ã« ã ã¼ ã¿ æ§ é 㯠é ã Immutable Object ã ãã§ä½ããã¼ã¿æ§é ãã®æ¬ã® å 容ã å ¨éå㧠å¸æãã ãé¡ï¼ãã¥ã¼ (Queue) ⢠FIFO (First-In First-Out) ⢠pushBack(e) ã§ãã¼ã¿eãå ¥ãã ⢠popFront() ã§åãåºãã â¢ å ¥ããé ã«åºã¦ãã â¢ ä»¥ä¸ ç ´å£çãã¥ã¼ Immutable Object ã§ãªã æåãã¹ãç®æ¨ 代 å ¥ æç¶ãåã§ãããã interface Queue<E> { void pushBack(E e); E popFront(); } ããããå®è£ 1 2 3 ã» 4 ã»
æ¨æ¥ï¼PFI ã»ããã¼ã«ã¦ã大è¦æ¨¡ã°ã©ãã¢ã«ã´ãªãºã ã®æå 端ãã¨ããã¿ã¤ãã«ã§çºè¡¨ãããã¦ãããã¾ããï¼ã¹ã©ã¤ãã¯ä»¥ä¸ã«ãªãã¾ãï¼ å¤§è¦æ¨¡ã°ã©ãã¢ã«ã´ãªãºã ã®æå 端 View more presentations from iwiwi å½æ¥ã¯ Ustream ãããã¦ããï¼é²ç»ãããçºè¡¨ãã覧ã«ãªãã¾ãï¼ http://www.ustream.tv/recorded/19713623 å 容ã®æµãã¨ãã¦ã¯ï¼ä»¥ä¸ã®ããã«ãªã£ã¦ãã¾ãï¼ å°å ¥ ã¢ã«ã´ãªãºã çéã§ã®è©±é¡ ææ°ã®ç 究åå éè·¯ãããã¯ã¼ã¯ã§ã®æçè·¯ã¯ã¨ãªå¦ç åºç¤çãªææ³ï¼åæ¹å Dijkstraï¼A*, ALT ææ°ã®ææ³ï¼Highway Dimension + Hub-Labeling Algorithm DB çéã§ã®è©±é¡ ææ°ã®ç 究åå è¤éãããã¯ã¼ã¯ã§ã®æçè·¯ã¯ã¨ãªå¦ç åºç¤çãªææ³ï¼ã©ã³ããã¼ã¯ãç¨ããæçè·é¢æ¨å® æ
ã¡ãã£ã¨æ©æ¢°å¦ç¿ã®æ¯è¼çæåãªã¢ãã«ãã¢ã«ã´ãªãºã ã®ååºã«ã¤ãã¦å¹´è¡¨ãä½ã£ã¦ã¿ãã ã£ã¦ä»é±æ«ç¨ã®è³æãªãã ãã©ãï½ 1805 Method of Least Squares 1901 PCA (Principal Component Analysis) 1905 Random Walk -1925 Logistic Regression 1936 Fisher's Linear Discriminant Analysis 1946 Monte Carlo Method 1948 n-gram model 1950 RKHS (Reproducing Kernel Hilbert Space) 1950s Markov Decision Process -1957 Perceptron 1958 Kalman Filter 1960s Hidden Markov Model -1961 N
ããã«ã¡ã¯å²¡éåã§ããããå¹´æ«ã«ãªãã¾ããããç§ã®ä»å¹´ã¯ããããã§ãã wat-arrayã¨ããC++ã©ã¤ãã©ãªãå ¬éãã¾ããã google code:wat-array wat-arrayã¯ããªã¼ã½ããã¦ã§ã¢ã§ãããä¿®æ£BSDã©ã¤ã»ã³ã¹ã«åºã¥ãã¦å©ç¨ã§ãã¾ãï¼ wat-arrayã¯waveletæ¨ã¨å¼ã°ãããã¼ã¿æ§é ãå©ç¨ãããã¨ã«ãããé åä¸ã®æ§ã ãªå¦çãå¹ççã«è¡ããã¨ãã§ããC++ã©ã¤ãã©ãªã§ãã ä¾ãã°ã â ä»»æã®é£ç¶ããç¯å²å ã«ããæå¤§å¤ /æå°å¤ / kçªç®ã«å¤§ããå¤, ã¾ããããã®åºç¾ä½ç½®ãé »åº¦ â ä»»æã®é£ç¶ããç¯å²å ã«ããæå®ããæåcã®åºç¾åæ°ãcæªæº/ãã大ããæåã®åºç¾åæ° â ä»»æã®æåã®içªç®ã®åºç¾ä½ç½® ã¨ãã£ããã®ãæ±ãããã¨ãå ¨ã¦ç¯å²é·ãå ¥åé·ã«å¯¾ãã¦å®æ°æéã§è¡ããã¨ãã§ãã¾ãã ä¾ãã°é·ã10åãå¤ã®ç¯å²ã0ãã1000ä¸ã§ãããããªé åAä¸ã®A[
Lanczosé¢æ°ã使ã£ã¦ç»åãæ¡å¤§ç¸®å°ããã¨ãé«å質ãªç»åãå¾ãããã®ã ããã ã ãã®ä»çµã¿ãç¥ãããã¨æã£ã¦ãã¤ãéãGoogleã®ãä¸è©±ã«ãªã£ãããä»çµã¿ã解説ããæ å ±ãè¦ã¤ãããªãã è¦ã¤ããã®ã¯Lanczosã¨ããååã®ç´¹ä»ããç»åå¦çã½ããã®ç´¹ä»ã°ããã ãã£ã¨ããæ¢ãæ¹ãæªãã®ãããããªããã©ã ãªãé«å質ãªç»åãå¾ãããã®ãï¼ ä»ã®æ¹æ³ã¨ã¯ä½ãéãã®ãï¼ æççãªæ å ±ãã調ã¹ã¦ãã£ã¦ããã®çç±ãç解ã§ããã ã¯ã£ããè¨ã£ã¦ããã解説ããã®ã¯é£ããï¼ Lanczosé¢æ° ã¾ãã¯Lanczosé¢æ°ã«ã¤ãã¦ã ããããLanczosãä½ã¨èªãã®ããçåã ã£ãããã©ã³ãã©ã·ã¥ã¨èªããããã æ°å¦è ã®ååã Lanczos sincé¢æ°ã¨ãLanczosçªé¢æ°ã¨ãLanczosãã£ã«ã¿ã¨ãã人ã«ãã£ã¦è²ã ãªå¼ã³æ¹ããã¦ãã¦ãæ£ããå¼ç§°ãã©ããªã®ãã¯ã£ããããªãããLanczos wi
ãã¼ã¿æ§é Javaã使ããªãå¿ ãè¦ãã¦ãããããã¼ã¿æ§é - é åã»ãªã¹ãã»ããã PHPãªãè¦ããã¹ããã¼ã¿æ§é ã¯ã²ã¨ã¤ã ãï¼ - é å Perlã§è¦ããããã¼ã¿æ§é - é åã»ããã·ã¥ VBAã§è¦ãã¦ãããã¼ã¿æ§é - éçé åã»åçé åã»ãã£ã¯ã·ã§ã㪠JavaScriptã§è¦ãã¦ããã¨ãããã¼ã¿æ§é - é åã»ãªãã¸ã§ã¯ã Bashã§è¦ãã¦ããã¨ãããã¼ã¿æ§é - é å - ä½ãããã®è¨èªã«ããè¨è¿°ã解æããæ¥è¨ ã¢ã«ã´ãªãºã Javaã使ããªãç解ãã¦ããããã¢ã«ã´ãªãºã - æ½åºã»ã½ã¼ãã»çµåã»éè¨ (ãªã¹ãï¼ãããç·¨) Javaã使ããªãç解ãã¦ããããã¢ã«ã´ãªãºã - æ½åºã»ã½ã¼ãã»çµåã»éè¨ (ãªã¹ãï¼ãã¼ã³ç·¨) PHPã使ããªãç解ãã¦ããããã¢ã«ã´ãªãºã - æ½åºã»ã½ã¼ãã»çµåã»éè¨ VBAã使ããªãç解ãã¦ããããã¢ã«ã´ãªãºã - æ½åºã»çµåã»éè¨ Javascr
gcbook, gcai, GCGCLoverã®ã¿ãªããããå¾ ãããã¾ããããã¬ãã¼ã¸ã³ã¬ã¯ã·ã§ã³ã®ã¢ã«ã´ãªãºã ã¨å®è£ ãã®æ å ±å ¬éã§ãã æ¸åï¼ã¬ãã¼ã¸ã³ã¬ã¯ã·ã§ã³ã®ã¢ã«ã´ãªãºã ã¨å®è£ èè ï¼ä¸æãææ´ï¼ç¸å·ãå ç£ä¿®ï¼ç«¹å ãéé ãã¼ã¸æ°ï¼472ãã¼ã¸ æ¬ä½ä¾¡æ ¼ï¼3,200å çºå£²éå§æ¥ï¼2010å¹´3æ17æ¥ï¼æ°´ï¼ â»å°åã»æ¸åºã«ãã£ã¦é ãããã¨ãããã¾ã ISBNï¼978-4-7980-2562-9 C3055 èªã¿æ æ¬æ¸ã¯æ¬¡ã®2ã¤ã®ãã¼ããæ±ãã¾ãã 1.GCã®ã¢ã«ã´ãªãºã ï¼ã¢ã«ã´ãªãºã ç·¨ï¼ 2.GCã®å®è£ ï¼å®è£ ç·¨ï¼ ã¢ã«ã´ãªãºã ç·¨ã§ã¯ãããã¾ã§ã«èæ¡ããã¦ããæ°å¤ãã®GCã¢ã«ã´ãªãºã ã®ä¸ ãããéè¦ãªãã®ãå³é¸ãã¦ç´¹ä»ãã¾ããä¼çµ±çãã¤åºæ¬çãªãã®ããããã é«åº¦ãªã¢ã«ã´ãªãºã ãé¸å®ãã¦ãã¾ããGCç¬ç¹ã®èãæ¹ãåã¢ã«ã´ãªãºã ã®ç¹ æ§ãªã©ãç解ãã¦ããã ãã®ãã¢ã«ã´ãªãºã ç·¨ã®æ大
as詳解 ActionScript 3.0ã¢ãã¡ã¼ã·ã§ã³ âè¡çªå¤å®ã»AIã»3Dãããã¯ã»ã«ã·ã§ã¼ãã¾ã§Flashä¸ç´ãã¯ãã㯠ãèªãã§ãã¦ãçµè·¯æ¢ç´¢ã®ã¢ã«ã´ãªãºã 㧠A* ãåãä¸ãããã¦ãã¾ãããA* ã«ã¤ãã¦ã¯ãããããæ¤ç´¢ãã¦èª¿ã¹ãããããã®ã§ããããã£ã±ãæ¬ã«æ¸ãã¦ããã¨ç解ããããã§ããããã£ãããªã®ã§èªåæµã«å®è£ ãã¦ãã¸ã¥ã¢ã©ã¤ãºãã¦ã¿ã¾ããããã¤ã¯ã¹ãã©æ³ã¾ã㯠A* ã®ç¹å¥ãªã±ã¼ã¹ã§ããããã¤ã¯ã¹ãã©æ³ããè¦ã¦ããã¾ããã¯ãªãã¯ããã¨æ¢ç´¢ã®ã·ãã¥ã¬ã¼ã·ã§ã³ãéå§ãã¾ããã¹ã¿ã¼ãå°ç¹(S)ããã´ã¼ã«(G)ã¸ã®æ¢ç´¢ãå§ã¾ãã¾ããè²ãã¤ããã¨ããããæççµè·¯ã決å®ããå ´æãã§ããã¹ã¿ã¼ãå°ç¹ããå°ããã¤æ¢ç´¢ãå®äºãã¦ããã¾ããååãããå®äºãã¾ãããã¾ã ã¾ã é²ã¿ã¾ããæå¾ã¾ã§çµããã¾ãããæççµè·¯ãé»è²ç¢å°ã§è¡¨ç¤ºãã¦ãã¾ãããã¤ã¯ã¹ãã©æ³ã¯ãã¹ã¿ã¼ãå°ç¹ããè¿ããã¼ã(=ãã¹
æå¼·æéã¢ã«ã´ãªãºãã¼é¤æè¬åº§ï¼ ãã®ã¢ã«ã´ãªãºã ã貪欲ã«ã¤ãââ貪欲æ³ã®ã¹ã¹ã¡ ã¢ã«ã´ãªãºã ã®ä¸çã«ããã¦ã欲張ãã§ãããã¨ã¯ã¨ãã«æå©ã«åããã¨ãããã¾ããä»åã¯ã貪欲æ³ã¨å¼ã°ããã¢ã«ã´ãªãºã ãç´¹ä»ããªããããã¼ããªåé¡ã«ææ¦ãã¦ã¿ã¾ãããããã®ã¢ã«ã´ãªãºã ã使ãããã©ããã®è¦æ¥µããã§ããããã«ãªãã°ãããªãã®è«ççæèåã¯ããªãã®ã¬ãã«ãªã®ã§ããï¼2010/9/4ï¼ æå¼·æéã¢ã«ã´ãªãºãã¼é¤æè¬åº§ï¼ ç ã¿ã¤ãã«ãªããåçè¨ç»æ³ãããã®æ·±æ·µã«è¿«ã æ°åã«ããã£ã¦åçè¨ç»æ³ã»ã¡ã¢åå帰ã«ã¤ãã¦è§£èª¬ãã¦ãã¾ããããä»åã¯å®è·µç·¨ã¨ãã¦ãããããµãã¯åé¡ã¸ã®ææ¦ã足ãããã«ããã®é·æã¨çæã®ç´¹ä»ãç解度ãã§ãã¯ã·ã¼ããªã©ãç¨æãã¾ãããç¹ã«ãåçè¨ç»æ³ã«ã¤ãã¦æ·±ãæãä¸ããçãããåçè¨ç»æ³ãã¹ã¿ã¼ã®éã«ãæ¡å ãã¾ããï¼2010/5/15ï¼ æå¼·æéã¢ã«ã´ãªãºãã¼é¤æè¬åº§ï¼ ã¢ã«ã´ãªãºãã¼ã®ç»
9. æ¢ç´¢ ãã®æç« ã§ã¯ãæ¢ç´¢åé¡ãéãã¦ããªã List ã« Monad ãããã®ãã説æãã¾ãã 1. æ¢ç´¢ã®ãããã ããã§ãæ¢ç´¢ (search) ã¨ã¯ æåã°ã©ãã®ããç¹ï¼å§ç¹ï¼ããããç¹ï¼çµç¹ï¼ã¾ã§ã®çµè·¯ãï¼ããããã°ï¼æ±ããã㨠ãæãã¾ãã æ¢ç´¢ã®ã¢ã«ã´ãªãºã ã«ã¯å¤§ããåãã¦ãæ·±ãåªå æ¢ç´¢ (depth first search) ã¨ å¹ åªå æ¢ç´¢ (breadth first search) ã®ï¼ã¤ãããã¾ãã æ·±ãåªå æ¢ç´¢ã¨ã¯ãçµç¹ã«ãã©ãçãããè¡ãæ¢ã¾ãã«ãªãã¾ã§ï¼ã¤ã®çµè·¯ãæ¢ç´¢ãã¦ããã 次ã®çµè·¯ãæ¢ç´¢ããæ¹æ³ã§ããããã°ã©ã ãç°¡åãªã®ã¨ãã¡ã¢ãªã¼éãè¨ç®æéãæ¯è¼ççãã¦æ¸ãã¨ãã ç¹å¾´ãããã¾ãããã ããæåã«è¦ã¤ãã£ãçµè·¯ãæççµè·¯ã ã¨ããä¿éã¯ããã¾ããã è¡ãæ¢ã¾ãã«ãªã£ããå ã®å°ç¹ã«æ»ã£ã¦ä»ã®å¯è½æ§ãæ¢ããã¨ãããã¯ãã©ãã¯ã¨ããã¾ãã ããã«å¯¾ããå¹ åª
ä»åã¯A*ã¢ã«ã´ãªãºã ãPythonã§ãã£ã¦ã¿ã¾ãã ã²ã¼ã ããã°ã©ãã®éã§ã¯ããã¯ã常èã¨ãªãã¤ã¤ããæççµè·¯åé¡è§£æ±ºã¢ã«ã´ãªãºã ã§ãã A*ã¯ãå¤å ¸çææ³ã§ããããã¤ã¯ã¹ãã©æ³ããæ¹è¯ãããã®ã§ãã ã¹ã¿ã¼ãå°ç¹ãããã¼ãnãéã£ã¦ã´ã¼ã«ã«è¾¿ãä»ãã¨ããæçè·é¢ãf(n)ã¨ããã¨ã f(n) = g(n) + h(n) ã¨ãããã¨ãã§ãã¾ããg(n)ã¯ãã¹ã¿ã¼ããããã¼ãnã¾ã§ã®æçè·é¢ããh(n)ã¯ããã¼ãnããã´ã¼ã«ã¾ã§ã®æçè·é¢ãã§ãã ã§ããæåããé©åãªg(n)ã¨h(n)ãå¤ã£ã¦ããªãè¦å´ãã¾ããããã ã ããããããã¼ãªäºæ¸¬å¤ã使ã£ã¦ãæççµè·¯ãããç¨åº¦äºæ¸¬ãã¦å¹ççã«çµè·¯æ¢ç´¢ããã¦ã¿ããã¨ããäºã§ãã ãããã¼ãªäºæ¸¬å¤ã使ã£ãæççµè·¯è·é¢ãf*(n)ã¨ãã㨠f*(n) = g*(n) + h*(n) ã¨ãªãã¾ããf*(n)ãæ±ããããã«ãããã¼ãªg*(n)ã¨h*(n)ã
id:smoking186 ããã®ææãåã, First Authorã®ååãªã©ãä»å ãã¾ãã. ã©ããã§ã. è¨äºå ã®codeã¯æé©åãªã©ãæ½ãã¦ããã, åé·ã«, å®ç¾©ã©ããã«æ¸ãã¦ãã¾ã. ifãã¾ã¨ãããããã¨ããã¾ãã, ãã®ãããã¯ã容赦ã... Rubyã§levenshteinè·é¢ãè¦ã¦ä»¥æ¥, å人çã«diffãã¼ã ãæ¥ã¦ãã. è¨ç®éO(ND) / O(NP)ã®algorithmãªã©ãããã®ã¯ç¥ã£ã¦ããã, è«æ(è±èª)ããã³, 解説ã®ã¿, ã¾ãã¯ã½ã¼ã¹ã³ã¼ãã®ã¿ãªã©åããã¦ãããã®ãå¤ã, algorithmã«çãèªåã«ã¯ç解ããã®ã«å¤§å¤æéãããã£ã¦ãã¾ã£ã. ããããã£ã¨ããã£ãã®ã§, 解説+JSå®è£ ãã¦ã¿ã. 解説ã¨ã½ã¼ã¹ã³ã¼ããã»ããã ã¨, å¤å°ã¯ãããããããªããã¨... èªåã¯æ£ç´ãããããç´°ããè¨ãããªãã¨ããã«ã¯ããããªã人ãªã®ã§(the O(ND)ã ã
ã²ã¼ã ã®ä½ãæ¹ã¨ã¢ã«ã´ãªãºã ãã¸ã£ã³ã«å¥ã«ã¾ã¨ãã¦ã¿ã¾ãããã²ã¼ã å¶ä½ããããã°ã©ãã³ã°ã®åå¼·ç¨ã«ãæ´»ç¨ãã ãããè¨èªå¥ã²ã¼ã ããã°ã©ãã³ã°å¶ä½è¬åº§ä¸è¦§ããããã¦ãèªã¿ãã ããã ãªã³ã¯åããããã¦ãããã®ã¯ãURLã表示ãã¦ããã®ã§ãInternet Archiveãªã©ã§ãã£ãã·ã¥ã表示ããã¦ã¿ã¦ãã ããã RPG ã²ã¼ã ã®ä¹±æ°è§£æ ä¹±æ°ãå©ç¨ããæµåºç¾ã¢ã«ã´ãªãºã ã®è§£èª¬ å種ã²ã¼ã ããã°ã©ã 解æ FFããã©ã¯ã¨ããããµã¬ã®ããã°ã©ã ã®è§£æãä¹±æ°ã®è¨ç®ãªã© ãã¡ã¼ã¸è¨ç®ããããï¼http://ysfactory.nobody.jp/ys/prg/calculation_public.htmlï¼ ãã¡ã¼ã¸ã®è¨ç®å¼ ã¨ã³ã«ã¦ã³ãã«ã¤ãã¦èãã¦ã¿ã ã¨ã³ã«ã¦ã³ãï¼ãããã§ã®æµã¨ã®ééï¼ã®å¦çæ¹æ³ãããã RPGã®ä½ãæ¹ - ã²ã¼ã ãã«2000 RPGã®ã¢ã«ã´ãªãºã ãã«ã¢ã¼ã¬ã®å¡ ä¹±æ°ã®å·¥å¤«ã®
ã¯ããã« CãC++ã§ããç¨åº¦å¤§ããªããã°ã©ã ãæ¸ãå ´åï¼æ大ã®åé¡ç¹ã¯ ã¡ã¢ãªç®¡çã§ããï¼è¤éãªããã°ã©ã ã®å ´åï¼å¿ è¦ãªã¡ã¢ãªã®éã ãããããè¦ç©ã£ã¦ããã®ãé£ããããï¼ã¡ã¢ãªãå¿ è¦ã«ãªã£ã æç¹ã§ã¡ã¢ãªã確ä¿ãï¼ä¸è¦ã«ãªã£ããããã解æ¾ããã¨ãã ããã°ã©ãã³ã°ã¹ã¿ã¤ã«ãä¸è¬çã ï¼Cã§è¨ãã°ãããªæãã ï¼ char *x; ... x = (char*)malloc(n*sizeof(char)); ... x ã使ã£ã¦ä»äºããã ... free(x); ãã®ããã°ã©ãã³ã°ã¹ã¿ã¤ã«ã®åé¡ç¹ã¯ï¼ããã¾ãã«è¨ã£ã¦ ãããªã¨ããã ããï¼ free(x) ãå¿ããã¨ï¼ããã»ã¹ãã©ãã©ã大ãããªã£ã¦ãã¾ãï¼ free() ãã¦ã¯ãããªããã®ãééã£ã¦free()ãã(ãã¨ãã°ï¼åã ã¡ã¢ãªã2å free() ãã¦ãã¾ãã¨ã)ã¨ï¼ãã® free() ã®ä¸ã§ãªãï¼ å ¨ç¶éãå ´æã§ã¨ã©ã¼ãçºçã
ãªãªã¼ã¹ãé害æ å ±ãªã©ã®ãµã¼ãã¹ã®ãç¥ãã
ææ°ã®äººæ°ã¨ã³ããªã¼ã®é ä¿¡
å¦çãå®è¡ä¸ã§ã
j次ã®ããã¯ãã¼ã¯
kåã®ããã¯ãã¼ã¯
lãã¨ã§èªã
eã³ã¡ã³ãä¸è¦§ãéã
oãã¼ã¸ãéã
{{#tags}}- {{label}}
{{/tags}}