Y\u0131\u011f\u0131n s\u0131ralama, verileri yerinde s\u0131ralamak i\u00e7in 'y\u0131\u011f\u0131n' ad\u0131 verilen bir veri yap\u0131s\u0131n\u0131n \u00f6zelliklerini kullanan, kar\u015f\u0131la\u015ft\u0131rmaya dayal\u0131 etkili bir s\u0131ralama algoritmas\u0131d\u0131r. Performans verimlili\u011fiyle tan\u0131nan Heapsort, veri analiti\u011fi, makine \u00f6\u011frenimi ve a\u011f altyap\u0131s\u0131 y\u00f6netimi dahil olmak \u00fczere bilgisayar biliminin \u00e7e\u015fitli alanlar\u0131nda yayg\u0131n olarak kullan\u0131lmaktad\u0131r.<\/p>\n
Heapsort algoritmas\u0131 ilk olarak 1964 y\u0131l\u0131nda JWJ Williams taraf\u0131ndan tan\u0131t\u0131ld\u0131. Heapsort'un ard\u0131ndaki fikir, b\u00fcy\u00fck miktarda veriyi ek bellek alan\u0131 gerektirmeden s\u0131ralayabilen etkili bir algoritmaya olan ihtiya\u00e7tan ortaya \u00e7\u0131kt\u0131. Williams, y\u0131\u011f\u0131n veri yap\u0131s\u0131n\u0131n b\u00f6yle bir g\u00f6rev i\u00e7in potansiyelini belirledi ve bu da Heapsort algoritmas\u0131n\u0131n geli\u015ftirilmesine yol a\u00e7t\u0131.<\/p>\n
1978'de Robert Sedgewick, Heapsort algoritmas\u0131n\u0131 geli\u015ftirerek verimlili\u011fini art\u0131rd\u0131 ve bu da onun bilgisayar bilimi alan\u0131nda geni\u015f \u00e7apta benimsenmesine katk\u0131da bulundu.<\/p>\n
Y\u0131\u011f\u0131n s\u0131ralamas\u0131, \u00f6ncelikle bir giri\u015f dizisini maksimum y\u0131\u011f\u0131na (her ana d\u00fc\u011f\u00fcm\u00fcn de\u011ferinin alt d\u00fc\u011f\u00fcmlerin de\u011ferlerinden b\u00fcy\u00fck veya onlara e\u015fit oldu\u011fu tam bir ikili a\u011fa\u00e7) d\u00f6n\u00fc\u015ft\u00fcrerek \u00e7al\u0131\u015f\u0131r. Algoritma daha sonra y\u0131\u011f\u0131n\u0131n k\u00f6k\u00fcn\u00fc (maksimum de\u011fer) y\u0131\u011f\u0131n\u0131n son \u00f6\u011fesiyle de\u011fi\u015ftirir. Bu i\u015flem y\u0131\u011f\u0131n\u0131 k\u00fc\u00e7\u00fclt\u00fcr ve maksimum de\u011feri do\u011fru s\u0131ralama konumuna yerle\u015ftirir.<\/p>\n
Bu de\u011fi\u015ftirme ve y\u0131\u011f\u0131n azaltma i\u015flemi yinelemeli olarak devam eder ve t\u00fcm girdi dizisinin s\u0131ral\u0131 bir s\u0131raya d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesiyle sonu\u00e7lan\u0131r. Y\u0131\u011f\u0131n S\u0131ralama algoritmas\u0131n\u0131n yerinde s\u0131ralama yapt\u0131\u011f\u0131 g\u00f6z \u00f6n\u00fcne al\u0131nd\u0131\u011f\u0131nda, ek bellek gerektirmez, bu da onu alan a\u00e7\u0131s\u0131ndan olduk\u00e7a verimli k\u0131lar.<\/p>\n
Heapsort algoritmas\u0131 iki temel ad\u0131mdan olu\u015fur:<\/p>\n
y\u0131\u011f\u0131nla\u015ft\u0131rma<\/strong>: Bu, bir dizi \u00f6\u011feyi bir y\u0131\u011f\u0131na d\u00f6n\u00fc\u015ft\u00fcrme i\u015flemidir. Dizinin ortas\u0131ndan ba\u015f\u0131na do\u011fru yinelenerek ve heap \u00f6zelli\u011fini ihlal eden herhangi bir \u00f6\u011fenin do\u011fru konumuna itilmesiyle ger\u00e7ekle\u015ftirilir.<\/p>\n<\/li>\n Silme<\/strong>: Dizi ge\u00e7erli bir y\u0131\u011f\u0131n haline geldi\u011finde, maksimum \u00f6\u011fe (y\u0131\u011f\u0131n k\u00f6k\u00fc), y\u0131\u011f\u0131n\u0131n son \u00f6\u011fesiyle (dizinin sonu) tekrar tekrar de\u011fi\u015ftirilir ve y\u0131\u011f\u0131n boyutu bir azalt\u0131l\u0131r. Her takastan sonra, y\u0131\u011f\u0131n \u00f6zelli\u011fini geri y\u00fcklemek i\u00e7in k\u00f6k "a\u015fa\u011f\u0131 elenir", b\u00f6ylece maksimum \u00f6\u011fe s\u0131ralanan dizide do\u011fru konumuna yerle\u015ftirilir.<\/p>\n<\/li>\n<\/ol>\n Bu ad\u0131mlar dizinin tamam\u0131 s\u0131ralanana kadar tekrarlan\u0131r.<\/p>\n Y\u0131\u011f\u0131n S\u0131ralama algoritmas\u0131 birka\u00e7 \u00f6nemli \u00f6zellik ile karakterize edilir:<\/p>\n Yerinde S\u0131ralama<\/strong>: Y\u0131\u011f\u0131n s\u0131ralamas\u0131 ek alan gerektirmez ve verilen dizi i\u00e7indeki \u00f6\u011feleri s\u0131ralar.<\/p>\n<\/li>\n Zaman verimlili\u011fi<\/strong>: Y\u0131\u011f\u0131n s\u0131ralaman\u0131n en k\u00f6t\u00fc durum ve ortalama zaman karma\u015f\u0131kl\u0131\u011f\u0131 O(n log n) olup, zaman a\u00e7\u0131s\u0131ndan olduk\u00e7a verimlidir.<\/p>\n<\/li>\n Karars\u0131zl\u0131k<\/strong>: Y\u0131\u011f\u0131n s\u0131ralamas\u0131 kararl\u0131 bir s\u0131ralama algoritmas\u0131 de\u011fildir. Bu, e\u015fit de\u011ferli \u00f6\u011felerin s\u0131ralanan \u00e7\u0131kt\u0131da g\u00f6receli s\u0131ras\u0131n\u0131 koruyamayaca\u011f\u0131 anlam\u0131na gelir.<\/p>\n<\/li>\n Evrensellik<\/strong>: Y\u0131\u011f\u0131n s\u0131ralamas\u0131, ister say\u0131sal ister kategorik olsun, kar\u015f\u0131la\u015ft\u0131r\u0131labilecek her t\u00fcrl\u00fc veriyi s\u0131ralayabilir.<\/p>\n<\/li>\n<\/ul>\n Heapsort'un temel prensibi ayn\u0131 kalsa da farkl\u0131 y\u0131\u011f\u0131n t\u00fcrleri kullan\u0131larak uygulanabilir. En yayg\u0131n t\u00fcrler \u015funlard\u0131r:<\/p>\nY\u0131\u011f\u0131n S\u0131ralaman\u0131n Temel \u00d6zellikleri<\/h2>\n
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Y\u0131\u011f\u0131n S\u0131ralamas\u0131 T\u00fcrleri<\/h2>\n