[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-573426-105":53,"doc-detail-573426-en":125},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":118,"head_meta":120,"extra_data":122,"updated_unix":124},105,"en","data-structure-operations-big-o-complexity-chart-common-algorithms","Data Structure Operations - Big-O Complexity Chart - Common Algorithms","","A compact reference chart covering core data structure operations and fundamental algorithm performance. It summarizes time and space complexity for array sorting and major data structures, including stacks, linked lists, skip lists, hash tables, and multiple tree variants, with best/average/worst access, search, insertion, deletion, and storage costs. It also lists common sorting algorithms such as quicksort, mergesort, timsort, heapsort, and others, plus graph representations and heap operation complexities, presented with an overall Big-O 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time complexities are compared for common data structure operations?","Question",{"text":107,"@type":108},"The chart compares best, average, and worst time complexities for operations such as access/search, insertion, and deletion across multiple structures like arrays, stacks, linked lists, skip lists, and trees.","Answer",{"name":110,"@type":105,"acceptedAnswer":111},"Which sorting algorithms are listed in the document?",{"text":112,"@type":108},"It lists quicksort, mergesort, timsort, heapsort, bubble sort, insertion sort, selection sort, shell sort, bucket sort, and radix sort.",{"name":114,"@type":105,"acceptedAnswer":115},"What graph and heap topics are included?",{"text":116,"@type":108},"The document covers graph representations such as adjacency list/matrix and incidence list/matrix, and it includes heap types and key heap operations like heapify, extract max, increase key, insert, delete, and merge.","https://schema.org",{"og:url":78,"og:type":119,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":121,"canonical":78},"index,follow",{"doc_id":123,"site_id":56},573426,1792016109,{"code":4,"msg":5,"data":126},{"doc_id":123,"user_id":127,"nickname":88,"user_avatar":128,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":129,"file_id":130,"file_url":131,"file_type":132,"file_size":133,"view_count":9,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":9,"language":134,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":135,"faqs":136,"seo_title":137,"seo_description":61,"update_tm":138,"read_time":4},137455077381,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","DATA STRUCTURE OPERATIONS  \nARRAY SORTING ALGORITHMS  \nGRAPH OPERATIONS  \nHEAP OPERATIONS  \nBIG-O COMPLEXITY CHART  \nBIG-O COMPLEXITIES  \nOF COMMON ALGORITHMS USED IN COMPUTER SCIENCE  \nData Structure Time Complexity  \nAverage  \nAccess Search  \nArray  O(1)   O(n)   \nStack  O(n)   O(n)   \nSingly-Linked List  O(n)   O(n)   \nDoubly-Linked List  O(n)   O(n)   \nSkip List  O(log (n))   O(log (n))   \nHash Table –  O(1)   \nBinary Search Tree  O(log (n))   O(log (n))   \nCartesian Tree –  O(log (n))   \nB-Tree  O(log (n))   O(log (n))   \nRed-Black Tree  O(log (n))   O(log (n))   \nSplay Tree –  O(log (n))   \nAVL Tree  O(log (n))   O(log (n))   \nInsertion  \n O(n)   \n O(1)   \n O(1)   \n O(1)   \nO(log (n))  \n O(1)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nDeletion  \n O(n)   \n O(1)   \n O(1)   \n O(1)   \nO(log (n))  \n O(1)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nWorst  \nAccess Search  \n O(1)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n–  \n O(n)   \n–  \nO(log (n))  \nO(log (n))  \n–  \nO(log (n))  \n O(n)   \n O(n)   \n O(n)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nInsertion  \n O(n)   \n O(1)   \n O(1)   \n O(1)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nDeletion  \n O(n)   \n O(1)   \n O(1)   \n O(1)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nO(log (n))  \nSpace Complexity  \nWorst  \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n log (n))   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \n O(n)   \nAlgorithm  \nQuicksort  \nMergesort  \nTimsort  \nHeapsort  \nBubble Sort  \nInsertion Sort  \nSelection Sort  \nShell Sort  \nBucket Sort  \nRadix Sort  \nTime Complexity  \nBest  \n O(n log (n))   \n O(n log (n))   O(n)   \n O(n log (n))   O(n)   \n O(n)   \nO(n^2)  \n O(n)   \nO(n+k)  \nO(nk)  \nAverage  O(n log (n))   \n O(n log (n))   \n O(n log (n))   \n O(n log (n))   \nO(n^2)  \nO(n^2)  \nO(n^2)  \nO((n log (n))^2)  \nO(n+k)  \nO(nk)  \nWorst  \nO(n^2)  \n O(n log (n))   \n O(n log (n))   \n O(n log (n))   \nO(n^2)  \nO(n^2)  \nO(n^2)  \nO((n log (n))^2)  \nO(n^2)  \nO(nk)  \nSpace Complexity  \nWorst  \nO(log (n))  \n O(n)   \n O(n)   \n O(1)   \n O(1)   \n O(1)   \n O(1)   \n O(1)   \n O(n)   \nO(n+k)  \nLEGEND  \nExcellent  \nGood  \nFair  \n\n| Bad |  |\n| --- | --- |\n|  |  |\n| Horrible |  |\n\nNode / Edge Management Adjacency list  \nIncidence list Adjacency matrix  \nIncidence matrix  \nStorage  O(|V|+|E|)   \n O(|V|+|E|)   \n O(|V|^2)   \n O(|V| · |E|)   \nAdd Vertex  \n O(1)   \n O(1)   O(|V|^2)   \n O(|V| · |E|)   \nAdd Edge  \n O(1)   \n O(1)   \n O(1)   \n O(|V| · |E|)   \nRemove Vertex  \n O(|V|+|E|)   \n O(|E|)   \n O(|V|^2)   \n O(|V| · |E|)   \nRemove Edge  O(|E|)   \n O(|E|)   O(1)   \n O(|V| · |E|)   \nQuery  O(|V|)   \n O(|E|)   O(1)   \n O(|E|)   \nHeap Type  \nLinked List (sorted)  \nLinked List (unsorted) Binary Heap  \nBinomial Heap Fibonacci Heap  \nTime Complexity  \nHeapify Find Max  \n–  O(1)   \n–  O(n)   \n O(n)   O(1)   \n–  \n–  \n O(1)   \n O(1)   \nExtract Max  \n O(1)   \n O(n)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nIncrease Key  \n O(n)   \n O(1)   \nO(log (n))  \nO(log (n))  \n O(1)   \nInsert  \n O(n)   \n O(1)   \nO(log (n))  \n O(1)   \n O(1)   \nDelete  \n O(1)   \n O(1)   \nO(log (n))  \nO(log (n))  \nO(log (n))  \nMerge  \nO(m+n)  \n O(1)   \nO(m+n)  \nO(log (n))  \n O(1)   \nOperations  \n1000  \n900  \n800  \n700  \n600  \n500  \n400  \n300  \n200  \n100  \n0  \nO(1)  \n O(logn)  \n O(n)  \n O(nlogn)  \n O(n^2)  \n O(2^n)  \n O(n!)  \nWWW. BIGOPOSTER.COM © 2016 Roman Pushkin","cbCaiczoIfbydxss","https://ap.wps.com/l/cbCaiczoIfbydxss","pdf",100197,"English","# Data Structure Operations\n## Array Sorting Algorithms\n## Graph Operations\n## Heap Operations\n## Big-O Complexity Chart\n## Common Algorithms Time and Space Complexity\n## Graph Representations\n## Heap Operations","[{\"question\":\"Which time complexities are compared for common data structure operations?\",\"answer\":\"The chart compares best, average, and worst time complexities for operations such as access/search, insertion, and deletion across multiple structures like arrays, stacks, linked lists, skip lists, and trees.\"},{\"question\":\"Which sorting algorithms are listed in the document?\",\"answer\":\"It lists quicksort, mergesort, timsort, heapsort, bubble sort, insertion sort, selection sort, shell sort, bucket sort, and radix sort.\"},{\"question\":\"What graph and heap topics are included?\",\"answer\":\"The document covers graph representations such as adjacency list/matrix and incidence list/matrix, and it includes heap types and key heap operations like heapify, extract max, increase key, insert, delete, and merge.\"}]","Data Structure Operations - Big-O Complexity Chart - Common Algorithms | PDF",1791939570]