Lecture

Computation & Algorithms II: Binary Search and Merge Sort

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture covers the concepts of binary search and merge sort algorithms. It starts by explaining binary search, its application in scenarios like inspecting exam results, and the recursive nature of the algorithm. The lecture then delves into merge sort, detailing the process of splitting a list, sorting each half, and merging them. It also discusses the idea of recursion in algorithms, using Fibonacci numbers as an example. The lecture concludes with an introduction to dynamic programming, focusing on the Floyd algorithm for finding the shortest path between multiple points in a graph.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Official source

Ontological neighbourhood

Theoretical computer science

Algorithms and data structures: Analysis of algorithms

Related concepts (32)

Sorting algorithm

In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output.

External sorting

External sorting is a class of sorting algorithms that can handle massive amounts of data. External sorting is required when the data being sorted do not fit into the main memory of a computing device (usually RAM) and instead they must reside in the slower external memory, usually a disk drive. Thus, external sorting algorithms are external memory algorithms and thus applicable in the external memory model of computation. External sorting algorithms generally fall into two types, distribution sorting, which resembles quicksort, and external merge sort, which resembles merge sort.

Merge sort

In computer science, merge sort (also commonly spelled as mergesort) is an efficient, general-purpose, and comparison-based sorting algorithm. Most implementations produce a stable sort, which means that the relative order of equal elements is the same in the input and output. Merge sort is a divide-and-conquer algorithm that was invented by John von Neumann in 1945. A detailed description and analysis of bottom-up merge sort appeared in a report by Goldstine and von Neumann as early as 1948.

Bucket sort

Bucket sort, or bin sort, is a sorting algorithm that works by distributing the elements of an array into a number of buckets. Each bucket is then sorted individually, either using a different sorting algorithm, or by recursively applying the bucket sorting algorithm. It is a distribution sort, a generalization of pigeonhole sort that allows multiple keys per bucket, and is a cousin of radix sort in the most-to-least significant digit flavor. Bucket sort can be implemented with comparisons and therefore can also be considered a comparison sort algorithm.

Sorting

Sorting refers to ordering data in an increasing or decreasing manner according to some linear relationship among the data items. ordering: arranging items in a sequence ordered by some criterion; categorizing: grouping items with similar properties. Ordering items is the combination of categorizing them based on equivalent order, and ordering the categories themselves. In , arranging in an ordered sequence is called "sorting". Sorting is a common operation in many applications, and efficient algorithms have been developed to perform it.

Related lectures (64)

Algorithms in Computer Science: Search and Sort Techniques

Provides an overview of essential search and sort algorithms in computer science.

Algorithms: Summary of the week

Covers algorithms for searching, sorting, optimization, and the Halting Problem.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Algorithm Design: Divide and Conquer

Covers recursion, dynamic programming, and algorithm design using divide and conquer strategies.

Optimization Algorithms: Greedy Approach