OpenID 2.0 Quick Note

Feb 28, 2008Download as ppt, pdf

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Toru Yamaguchi

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Bubble sort is an algorithm that sorts a list of numbers by repeatedly swapping adjacent elements that are out of order. It works by comparing adjacent elements and swapping them if they are in the wrong order, "bubbling" the largest values to the end of the list over multiple iterations. The algorithm iterates through the list N-1 times, where N is the number of elements, to fully sort the list. It uses pairwise comparisons and swapping to move the largest remaining value to its correct place with each pass.

Quicksort: illustrated step-by-step walk throughYoshi Watanabe

Bubblesort AlgorithmTobias Straub

Mergesortluzenith_g

The document discusses the merge sort algorithm. It works by recursively dividing an array into two halves, sorting each half, and then merging the sorted halves back together. The key steps are: 1) Divide the array into equal halves recursively until arrays contain a single element. 2) Sort the halves by recursively applying the merge sort algorithm. 3) Merge the sorted halves back into a single sorted array by comparing elements and copying the smaller value into the output array.

Quicksort Presentationirdginfo

Quick Sort is a recursive divide and conquer sorting algorithm that works by partitioning a list around a pivot value and recursively sorting the sublists. It has average case performance of O(n log n) time. The algorithm involves picking a pivot element, partitioning the list based on element values relative to the pivot, and recursively sorting the sublists until the entire list is sorted. An example using Hoare's partition scheme is provided to demonstrate the partitioning and swapping steps.

Algorithm: Quick-SortTareq Hasan

The document describes the quicksort algorithm. Quicksort works by: 1) Partitioning the array around a pivot element into two sub-arrays of less than or equal and greater than elements. 2) Recursively sorting the two sub-arrays. 3) Combining the now sorted sub-arrays. In the average case, quicksort runs in O(n log n) time due to balanced partitions at each recursion level. However, in the worst case of an already sorted input, it runs in O(n^2) time due to highly unbalanced partitions. A randomized version of quicksort chooses pivots randomly to avoid worst case behavior.

Quick Sort , Merge Sort , Heap SortMohammed Hussein

The document discusses various sorting algorithms that use the divide-and-conquer approach, including quicksort, mergesort, and heapsort. It provides examples of how each algorithm works by recursively dividing problems into subproblems until a base case is reached. Code implementations and pseudocode are presented for key steps like partitioning arrays in quicksort, merging sorted subarrays in mergesort, and adding and removing elements from a heap data structure in heapsort. The algorithms are compared in terms of their time and space complexity and best uses.

Merge sortVidushi Pathak

John von Neumann invented the merge sort algorithm in 1945. Merge sort follows the divide and conquer paradigm by dividing the unsorted list into halves, recursively sorting each half through merging, and then merging the sorted halves back into a single sorted list. The time complexity of merge sort is O(n log n) in all cases (best, average, worst) due to its divide and conquer approach, while its space complexity is O(n) to store the temporary merged list.

Bubble Sortgeeortiz

Bubble sort is a simple sorting algorithm that works by repeatedly swapping adjacent elements if they are in the wrong order until the list is fully sorted. It is best for sorting small lists or lists that are nearly sorted already. Though simple, it is not efficient for large data sets as its runtime is quadratic. The example demonstrates bubble sort by visually swapping numbers in the wrong order until the list is sorted.

Quick Sortpriyankanaidu6

Quick sort uses a divide-and-conquer approach to sort a list. It works by selecting a pivot element, partitioning the list into elements less than, equal to, and greater than the pivot, and then recursively sorting the sub-lists. The example shows quick sort being applied to a list of numbers, with the pivot being swapped with other elements to partition the list into sorted sub-lists on each iteration.

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特定のプロジェクトがあり、要件定義をし概要設計をする。それがアーキテクトの仕事だと思われがちですが、大きな視点を持ち様々な課題を自らリードして解決していく立場としても絶好のポジションです。このセッションでは、Mobage オープンプラットフォームの立ち上げから、グローバルプラットフォーム展開、さらには mixi 社との共同プラットフォーム構築、 JavaScript SDK と認証技術の組み合わせによる新しい HTML5 プラットフォーム構築をアーキテクトという立場でリードし続けた立場から、技術選択のみならず実現したい事に対する俯瞰的な捉え方を、これまでの実例と共に紹介し、アーキテクトという役割について、お話します。

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