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Algorithms

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All my notes on Algorithms

Problems. 4.5 Discussion and Exercises. Java Algorithms and Clients. Top 10 Algorithms for Coding Interview. PDF: Update History, Latest version (8/1/2016) The following are the common subjects in coding interviews. As understanding those concepts requires much more effort, this tutorial only serves as an introduction. The subjects that are covered include: 1) String/Array/Matrix, 2) Linked List, 3) Tree, 4) Heap, 5) Graph, 6) Sorting, 7) Dynamic Programming, 8) Bit Manipulation, 9) Combinations and Permutations, and 10) Math Problems. I highly recommend you to read "Simple Java" first, if you need a brief review of Java basics. If you want to see code examples that show how to use a popular API, you can use JavaSED.com. 1. An algorithm problem's input is often a string or array. 2. Common methods to solve matrix related problem include DFS, BFS, dynamic programming, etc. 3.

The implementation of a linked list is pretty simple in Java. Two popular applications of linked list are stack and queue. Stack Queue The Java standard library contains a class called "Stack". 4. 4.1 Tree 4.2 Heap 4.3 Trie 5. 6. Data Structure Visualization. Linked List Queue Visualization. Gödel's Lost Letter and P=NP | a personal view of the theory of computation. Jeff Erickson's Algorithms. Sadly, this page has become embarrassingly stale. Updated revisions of most notes, along with unedited video captures of several lectures, are indeed available on the web sites of my most recent courses: (You might notice that some of the updated notes look more like book chapters.) Check back this summer for a major update to this page, complete with three more years of homeworks, exams, and lab problems. This page contains lecture notes and other course materials for various algorithms classes I have taught at the University of Illinois, Urbana-Champaign.

The notes are numbered in the order I cover the material in a typical undergraduate class, wtih notes on more advanced material (indicated by the symbol ♥) intersprsed appropriately. Each lecture note includes several exercises, and a near-complete archive of my old homeworks, exams, and discussion problems also follows the lecture notes on this page. Please do not ask me for solutions to the exercises. Everything Algorithms Notes. Neopythonic. Lectures 1 and 2: Analysis of Algorithms. I just finished watching the last lecture of MIT's "Introduction to Algorithms" course. Having a great passion for all aspects of computing, I decided to share everything I learned with you, my dear readers! This is the first post in an article series about this course. As I wrote earlier, I am very serious about watching video lectures. If they are math-intensive, I usually take notes as if I were in the classroom.

Lectures in this course were exactly like that -- logarithms, big-o's, thetas, expectations, and all the other math guys fighting with each other on the blackboards. There are totally 23 video lectures, each around 1 hour 20 minutes long. I will be posting about 2 - 3 lectures at a time which will result in approximately 10 blog posts. Understanding and designing effective algorithms is a very important skill for a top-notch programmer.

Let's start with Lecture 1 of this course. Lecture 1: Analysis of Algorithms The first lecture is given by the famous professor Charles E. Ps. Calculate the sum of long numbers - James Chen's C/C++ Home. Reverse a linked list in java « Think ! If you search for it you will get millions of solutions but sadly (like many things in internet) the first few solutions seem unintuitive and unnecessarily complex for such a simple problem, not sure why, anyway putting mine out there for somebody to point out why I should go for a more complex solution. [in java for a change] Idea : Use two references and reverse their links and proceed till we reach the end public void reverse_iterative { if(isEmpty()) { return;} //curr == null Node currNode,nextNode , loopNode; currNode = head; nextNode = head.next; head.next = null; while(nextNode !

= null) { loopNode = nextNode.next; nextNode.next = currNode; currNode = nextNode; nextNode = loopNode; } head = currNode; } Recursive Idea : Reverse the sublist starting from second node and point the second node to first, apply this recursively. Share This. Vkostyukov/finagle-fibonacci. Sorting Algorithm Animations. Algorithms in Java, Parts 1-4, 3rd edition by Robert Sedgewick. Addison Wesley, 2003. Quicksort is Optimal by Robert Sedgewick and Jon Bentley, Knuthfest, Stanford University, January, 2002.

Dual Pivot Quicksort: Code by Discussion. Bubble-sort with Hungarian (“Csángó”) folk dance YouTube video, created at Sapientia University, Tirgu Mures (Marosvásárhely), Romania. Select-sort with Gypsy folk dance YouTube video, created at Sapientia University, Tirgu Mures (Marosvásárhely), Romania. Sorting Out Sorting, Ronald M. Baecker with the assistance of David Sherman, 30 minute color sound film, Dynamic Graphics Project, University of Toronto, 1981.

CS 240 Computer Science II Syllabus. Spring 2008 SYLLABUS This page last changed 6/19/08 Objectives: To develop skills in the design and development of computer software continuing to utilize an object-oriented language, packages, modules and libraries. To develop understanding and build skills in the implementation and use of common data structures used in software development through data abstraction. To further study the Java language and learn to use UNIX as a software design environment. To build a basic background in algorithm analysis and verification techniques. To further understand various aspects of the field of computer science. This course's prerequisite is CS 110. Build program solutions using control structures of selection (if-then, switch), iteration (while, for) and functions understand the use of objects, methods, and classes understand the basic use of vectors (arrays) understand the design, implementation and testing of small problem solutions (25-50 lines of code) Grading: Assignments and programs:

Open Data Structures (in Java) Dictionary of Algorithms and Data Structures. CPSC490 - Problem Solving in Computer Science. Sphere Online Judge (SPOJ) - Problems. Algorithm Tutorials. Big-O Algorithm Complexity Cheat Sheet. Adnan Aziz. Elements of Programming Interviews We're excited to release a free soft copy sampler of EPI. Specifically, this PDF shows the organization, content, style, topics, and quality of our book.

Amit, Tsung-Hsien and I have completed "Elements of Programming Interviews"! Buy it at Amazon.com - it's the best investment you as a software professional can make in your future. Have you ever... Wanted to work at a hot futuristic company? If so, you need to read Elements of Programming Interviews (EPI). The code of EPI is a collection of 300 problems with detailed solutions, including over 100 figures and 200 tested programs. The book begins with a summary of patterns for data structure, algorithms, and problem solving that will help you solve the most challenging interview problems. EPI concludes with a summary of the nontechnical aspects of interviewing, including common mistakes, strategies for a great interview, perspectives from across the table, negotiating the best offer, and much more.

Classes. Maratona/Facebook at master · arthurguima/maratona. / - elements-of-programming-interviews - Solutions to Elements of Programming Interviews: 300 Questions and Solutions. Markov Chains – Explained | Tech Effigy. Markov Chains is a probabilistic process, that relies on the current state to predict the next state. For Markov chains to be effective the current state has to be dependent on the previous state in some way; For instance, from experience we know that if it looks cloudy outside, the next state we expect is rain. We can also say that when the rain starts to subside into cloudiness, the next state will most likely be sunny. Not every process has the Markov Property, such as the Lottery, this weeks winning numbers have no dependence to the previous weeks winning numbers. Usually when we have data, we calculate the probability of a state by counting the amount of times it occurs within a total of all states, we then end up with 0.5(50%) cloudy, 0.3(30%) rain, 0.2(20%) Sunny days of a year; Containing no information about when they occur relating to each other.

The Transition Matrix transitions from Row to Column as in the Markov Table. No surprise, most likely rain. Like this: Scalgorithms - Algorithms and Data-Structures in Scala. Efficient binary tree traversal with two pointers without using a stack - debforit. In this article, we will be discussing about space complexity optimized binary tree traversal techniques. Four modes of traversals are used quite often in a binary tree. They are pre-order walk, in-order walk, post-order walk and level first walk. Except the level first traversal, all the others are recursive and hence require a stack for traversal. We would talk here about in-order traversal. Our analysis can be applied to the other two traversal procedures as well. Let us first talk about the simplest method for traversal involving recursion. The method actually is a representation of the way we actually visualize the procedure in our mind. Inline Node* Node::left(Node* father) { // Given the father node's address, calculate // left son's address by XORing with our fLeft field return reinterpret_cast<Node*>(this->fLeft ^ father->addressValue());} Now, let s turn our attention to the coding of the actual traversal routine with this data structure.

52233 Algorithms and Data Structures. Csclab.murraystate.edu/bob.pilgrim/445/index.html. Introduction to Programming in Java: An Interdisciplinary Approach. A textbook for a first course in computer sciencefor the next generationof scientists and engineers Textbook. Our textbooks Introduction to Programming in Java [Amazon · Pearson · InformIT ] and Computer Science [Amazon · Pearson · InformIT ] are an interdisciplinary approach to the traditional CS1 curriculum with Java. We teach the classic elements of programming, using an "objects-in-the-middle" approach that emphasizes data abstraction.

We motivate each concept by examining its impact on specific applications, taken from fields ranging from materials science to genomics to astrophysics to internet commerce. The first half of the book is organized around four stages of learning to program: Chapter 1: Elements of Programming introduces variables; assignment statements; built-in types of data; conditionals and loops; arrays; and input/output, including graphics and sound.

Booksite. For students: Java programming environment. For instructors: Python. Copyright © 2000–2016 and . Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne. Lecture Slides for An Introduction to the Analysis of Algorithms. These slides are for the first half of an undergraduate course taught at Princeton, developed to provide an overview of An Introduction to the Analysis of Algorithms and Analytic Combinatorics. The course format is "introduce-read-discuss". We introduce a set of topics in lecture; students read about the topics and work selected exercises between lectures, and we discuss any questions about the reading and the exercises at the beginning of the next lecture. Each lecture ends with a slide or two giving assignments to be completed before the next lecture and to be discussed at the beginning of the next lecture.

In addition, a portion of each lecture is devoted to in-class exercises, to make sure that all students understand the introductory material. While some of the reading material may be difficult for a typical undergraduate to master on such a quick pass through, a substantial fraction of the coverage is elementary. Lecture 1, slide 33. What not to do during an interview | Dan Dreams of Coding. Whenever you find yourself doing one of the following things during an interview, just don’t. OK? Don’t suck at something you say you’re an expert at Seriously, how often do I talk to Java experts who don’t know how to use the most basic java.util classes?

Or bash experts who don’t know how to grep? Don’t make excuses for why you failed Sometimes you get caught flat-footed, or your brain seizes up, or you have a bad day, or you go down the wrong path and get stuck. Don’t be arrogant, don’t act superior, don’t be a dick Should be a no-brainer, right? Don’t badmouth an old employer Even if you worked for Satan in the helpdesk department of the third circle of hell, it’s unprofessional to trashtalk an old employer.

Don’t swear Some interviewers won’t care about your language during the interview, but others will – a lot. Don’t chatter on and on You don’t want to be labeled a “talker”. Don’t waste the interviewer’s (and your own) time Don’t ask questions you can look up trivially. Don’t go in cold. CSE101. Stanford / Computer Science III: Programming Paradigms , Academic Earth. Algorithms. Data Structures and Algorithm. GeeksforGeeks | A computer science portal for geeks. Sorting Applications. Sorting algorithms and priority queues are widely used in a broad variety of applications. Our purpose in this section is to briefly survey some of these applications. Sorting various types of data. Our implementations sort arrays of Comparable objects. This Java convention allows us to use Java's callback mechanism to sort arrays of objects of any type that implements the Comparable interface.

Transaction example. Which sorting algorithm should I use? Knowing which algorithm is best possible depends heavily on details of the application and implementation, but we have studied some general-purpose methods that can be nearly as effective as the best possible for a wide variety of applications. Property. In most practical situations, quicksort is the method of choice. Sorting primitive types. Reductions. The idea that we can use sorting algorithms to solve other problems is an example of a basic technique in algorithm design known as reduction. A brief survey of sorting applications. Jdk8/jdk8/jdk: 687fd7c7986d src/share/classes/java/util/DualPivotQuicksort.java.