Chapter 3: Searching describes several classic symbol-table implementations, including binary search trees, red—black trees, and hash tables.
Chapter 4: Graphs surveys the most important graph-processing problems, including depth-first search, breadth-first search, minimum spanning trees, and shortest paths. Chapter 5: Strings investigates specialized algorithms for string processing, including radix sorting, substring search, tries, regular expressions, and data compression.
Chapter 6: Context highlights connections to systems programming, scientific computing, commercial applications, operations research, and intractability. Reading a book and surfing the web are two different activities: This booksite is intended for your use while online for example, while programming and while browsing the web ; the textbook is for your use when initially learning new material and when reinforcing your understanding of that material for example, when reviewing for an exam.
For teachers: This online content. Everything on these pages is freely available. We ask only that you adhere to normal academic traditions of attribution if you adapt this content in your own course. One best practice is to just provide links to our pages. To use the lecture videos. Please go to the Lectures tab at left for links to all the online videos and suggestions on how to use them. To adopt the textbook. Finally, we consider various applications of stacks and queues ranging from parsing arithmetic expressions to simulating queueing systems.
Elementary Sorts We introduce the sorting problem and Java's Comparable interface. We study two elementary sorting methods selection sort and insertion sort and a variation of one of them shellsort. We also consider two algorithms for uniformly shuffling an array. We conclude with an application of sorting to computing the convex hull via the Graham scan algorithm. Mergesort We study the mergesort algorithm and show that it guarantees to sort any array of n items with at most n lg n compares.
We also consider a nonrecursive, bottom-up version. We prove that any compare-based sorting algorithm must make at least n lg n compares in the worst case. We discuss using different orderings for the objects that we are sorting and the related concept of stability. Quicksort We introduce and implement the randomized quicksort algorithm and analyze its performance. We also consider randomized quickselect, a quicksort variant which finds the kth smallest item in linear time. Finally, we consider 3-way quicksort, a variant of quicksort that works especially well in the presence of duplicate keys.
Priority Queues We introduce the priority queue data type and an efficient implementation using the binary heap data structure. This implementation also leads to an efficient sorting algorithm known as heapsort. We conclude with an applications of priority queues where we simulate the motion of n particles subject to the laws of elastic collision. Elementary Symbol Tables We define an API for symbol tables also known as associative arrays and describe two elementary implementations using a sorted array binary search and an unordered list sequential search.
When the keys are Comparable, we define an extended API that includes the additional methods min, max floor, ceiling, rank, and select. To develop an efficient implementation of this API, we study the binary search tree data structure and analyze its performance. Free course or paid. Tutorials for beginners or advanced learners. Algorithms and Data structures are the building blocks …. Category : Training Courses Show more.
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