DOCSLIB.ORG

Geometry in Competitive Programming

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Geometry in Competitive Programming Geometry in competitive programming Dissertation presented by Victor LECOMTE for obtaining the master's degree in Computer Science and Engineering Supervisor Yves DEVILLE Co-supervisor François AUBRY Readers François AUBRY, Yves DEVILLE, Jean-François REMACLE Academic year 2017-2018 Abstract Competitive programming consists in the organization of programming con- tests, which see the world's most talented coders compete to solve problems of an algorithmic nature by implementing efficient programs as quickly as possible. Recently, geometry problems have had an increasing importance in those contests, but many contestants dislike them for being too technical or causing too precision issues linked to the use of floating-point numbers. We believe that those complaints are for the largest part due to a lack of specific training on the basics of computational geometry. We therefore introduce a new handbook of computational geometry, aimed primarily at the competitive programming public. It treats the subject in a practice- oriented way, providing code snippets for every operation, and explaining them in intuitive terms with the help of a large amount of illustrative figures. Its contents focus on the foundations of both 2D and 3D computational geometry, as well as the management of floating-point imprecisions, where we present a model of error propagation based on magnitude conditions and dimensionality of values. In addition, we present an original geometry contest whose problems showcase innovative notions and techniques, especially in 3D geometry. We hope that in the future, problem setters can reuse and adapt those ideas in order to foster variety and expand the scope of geometry as a competitive programming subfield. Contents I Main contents 6 1 Introduction 7 1.1 About competitive programming . .7 1.2 Types of programming contests . .8 1.3 Geometry in competitive programming . .9 1.4 Goals and structure of this thesis . .9 2 Writing a handbook of geometry 11 2.1 Approach and writing style . 11 2.2 Current contents . 12 2.3 Publication and future plans . 13 3 Organizing a geometry contest 14 3.1 Introduction . 14 3.2 Introduction to contest preparation . 14 3.3 Presentation of the problems . 17 3.4 Problem statements . 18 3.5 Editorial . 34 3.5.1 Sledding down the mountain . 34 3.5.2 Pen spinning accident . 36 3.5.3 Polar map . 38 3.5.4 Gold paint optimization . 40 3.6 Results and conclusion . 43 4 Conclusion 45 1 II Handbook of geometry for competitive programmers 47 5 Precision issues and epsilons 48 5.1 Small imprecisions can become big imprecisions . 48 5.1.1 When doing numerically unstable computations . 49 5.1.2 With large values and accumulation . 50 5.2 Small imprecisions can break algorithms . 51 5.2.1 When making binary decisions . 51 5.2.2 By violating basic assumptions . 52 5.3 Modelling precision . 52 5.3.1 The issue with \absolute or relative" error . 52 5.3.2 Precision guarantees from IEEE 754 . 54 5.3.3 Considering the biggest possible magnitude . 54 5.3.4 Incorporating multiplication . 55 5.3.5 Why other operations do not work as well . 56 5.4 Case studies . 57 5.4.1 Problem \Keeping the Dogs Apart" . 57 5.4.2 Quadratic equation . 62 5.4.3 Circle-circle intersection . 64 5.5 Some advice . 67 5.5.1 For problem solvers . 67 5.5.2 For problem setters . 68 6 Basics 69 6.1 Points and vectors . 69 6.1.1 Complex numbers . 69 6.1.2 Point representation . 72 6.2 Transformations . 75 6.2.1 Translation . 75 6.2.2 Scaling . 76 6.2.3 Rotation . 76 6.2.4 General linear transformation . 77 6.3 Products and angles . 78 6.3.1 Dot product . 78 2 6.3.2 Cross product . 80 6.4 Lines . 86 6.4.1 Line representation . 86 6.4.2 Side and distance . 89 6.4.3 Perpendicular through a point . 90 6.4.4 Sorting along a line . 90 6.4.5 Translating a line . 91 6.4.6 Line intersection . 92 6.4.7 Orthogonal projection and reflection . 93 6.4.8 Angle bisectors . 93 6.5 Segments . 95 6.5.1 Point on segment . 95 6.5.2 Segment-segment intersection . 96 6.5.3 Segment-point distance . 98 6.5.4 Segment-segment distance . 98 6.6 Polygons . 99 6.6.1 Polygon area . 99 6.6.2 Cutting-ray test . 101 6.6.3 Winding number . 103 6.7 Circles . 108 6.7.1 Defining a circle . 108 6.7.2 Circumcircle . 108 6.7.3 Circle-line intersection . 109 6.7.4 Circle-circle intersection . 111 6.7.5 Tangent lines . 112 7 3D geometry 116 7.1 Points, products and orientation . 116 7.1.1 Point representation . 116 7.1.2 Dot product . 117 7.1.3 Cross product . 118 7.1.4 Mixed product and orientation . 120 7.2 Planes . 122 7.2.1 Defining planes . 122 3 7.2.2 Side and distance . 123 7.2.3 Translating a plane . 124 7.2.4 Orthogonal projection and reflection . 125 7.2.5 Coordinate system based on a plane . 125 7.3 Lines . 127 7.3.1 Line representation . 127 7.3.2 Distance from a line . 129 7.3.3 Sorting along a line . 129 7.3.4 Orthogonal projection and reflection . 129 7.3.5 Plane-line intersection . 130 7.3.6 Plane-plane intersection . 131 7.3.7 Line-line distance and nearest points . 132 7.4 Angles between planes and lines . 134 7.4.1 Between two planes . 134 7.4.2 Between two lines . 135 7.4.3 Between a plane and a line . 136 7.4.4 Perpendicular through a point . 136 7.5 Polyhedrons . 137 7.5.1 Definition . 137 7.5.2 Surface area . 138 7.5.3 Face orientation . 140 7.5.4 Volume . 142 7.6 Spherical geometry . 144 7.6.1 Spherical coordinate system . 144 7.6.2 Sphere-line intersection . 145 7.6.3 Great-circle distance . 146 7.6.4 Spherical segment intersection . 147 7.6.5 Angles on a sphere . 151 7.6.6 Spherical polygons and area . 152 7.6.7 Solid angle . 154 7.6.8 3D winding number . 155 A Solutions to the exercises 157 4 B Omitted proofs 160 B.1 Precision bounds for +; ; ................... 160 − × 5 Part I Main contents 6 Chapter 1 Introduction In this chapter, we give a short introduction to competitive programming and the role of geometry in it, then outline the goals and structure of this thesis. 1.1 About competitive programming Competitive programming is the participation in programming contests, which test the participants' ability to write programs that solve problems of an algorithmic or mathematical nature in an efficient way. A typical problem in a programming contest describes the problem to be solved, specifies how the input data is provided and how the output should be written. The participant then has to write a program that will read the input data (typically in stdin), compute the result, then write the output (typically in stdout). When the participant submits a program, it will be compiled by the judging system then executed on a batch of tests, which is designed to comprehensively test the program in many situations and detect any flaw. If for each test case the program runs successfully within the time and memory limits, and the judging system evaluates the answer as correct, then the solution is Accepted and awarded points. Other verdicts include Wrong answer if the output is incorrect, Time limit exceeded if the program took too much time, or Runtime error if the program crashed. Besides this standard "read input, compute result, write output" scheme, there are also interactive tasks, in which the participant's solution has to interact directly with the judging system, exchanging information back and forth. Also, in most tasks, finding a fast enough solution is the main chal- lenge, there are some tasks in which the memory limit might be quite limit- ing, or some other resource determined by the problem statement (like the 7 number of queries the solution may ask the judging system, in interactive tasks). Contestants are free to implement their solutions in a variety of lan- guages, but C++ is the most popular, because of its execution speed and relatively rich standard library. To succeed in contests, good implementa- tion skills and a mastery of the language used are as important as talent in algorithm design and problem solving. For more details about competitive programming, see [4]. 1.2 Types of programming contests Programming contests can be mostly classified under four categories. The type of problems is generally the same across the board, but the contest formats vary a lot. Olympiads in Informatics Often called OIs, olympiads in informatics are contests for secondary school students. The most famous OI is the IOI (International Olympiad in Informatics), held every year for about a week in the summer. National OIs organized in most countries, usually as part of the selection process for IOI, and there are also many regional OIs, like APIO (Asia-Pacific), Balkan OI, CEOI (Central Europe), etc. OIs are individual contests and are characterized by relatively few tasks (at IOI, 3 tasks for 5 hours), each containing many subtasks that give partial score to partial or suboptimal solutions. ACM-ICPC Composed of the World Finals, dozens of regionals serving as qualifiers, and many subregionals for local practice, the ACM-ICPC con- tests are for teams of 3 university students. Teams have 5 hours to solve usually 9-13 problems.
Load more

Recommended publications
  • Lecture Notes, CSE 232, Fall 2014 Semester
    Lecture Notes, CSE 232, Fall 2014 Semester Dr. Brett Olsen Week 1 - Introduction to Competitive Programming Syllabus First, I've handed out along with the syllabus a short pre-questionnaire intended to give us some idea of where you're coming from and what you're hoping to get out of this class. Please fill it out and turn it in at the end of the class. Let me briefly cover the material in the syllabus. This class is CSE 232, Programming Skills Workshop, and we're going to focus on practical programming skills and preparation for programming competitions and similar events. We'll particularly be paying attention to the 2014 Midwest Regional ICPC, which will be November 1st, and I encourage anyone interested to participate. I've been working closely with the local chapter of the ACM, and you should talk to them if you're interesting in joining an ICPC team. My name is Dr. Brett Olsen, and I'm a computational biologist on the Medical School campus. I was invited to teach this course after being contacted by the ACM due to my performance in the Google Code Jam, where I've been consistently performing in the top 5-10%, so I do have some practical experience in these types of contests that I hope can help you improve your performance as well. Assisting me will be TA Joey Woodson, who is also affiliated with the ACM, and would be a good person to contact about the ICPC this fall. Our weekly hour and a half meetings will be split into roughly half lecture and half practical lab work, where I'll provide some sample problems to work on under our guidance.
    [Show full text]
  • Declaratively Solving Tricky Google Code Jam Problems with Prolog-Based Eclipse CLP System
    Declaratively solving tricky Google Code Jam problems with Prolog-based ECLiPSe CLP system Sergii Dymchenko Mariia Mykhailova Independent Researcher Independent Researcher [email protected] [email protected] ABSTRACT produces correct answers for all given test cases within a In this paper we demonstrate several examples of solving certain time limit (4 minutes for the \small" input and 8 challenging algorithmic problems from the Google Code Jam minutes for the \large" one). programming contest with the Prolog-based ECLiPSe sys- tem using declarative techniques: constraint logic program- GCJ competitors can use any freely available programming ming and linear (integer) programming. These problems language or system (including the ECLiPSe2 system de- were designed to be solved by inventing clever algorithms scribed in this paper). Most other competitions restrict par- and efficiently implementing them in a conventional imper- ticipants to a limited set of popular programming languages ative programming language, but we present relatively sim- (typically C++, Java, C#, Python). Many contestants par- ple declarative programs in ECLiPSe that are fast enough ticipate not only in GCJ, but also in other contests, and to find answers within the time limit imposed by the con- use the same language across all competitions. When the test rules. We claim that declarative programming with GCJ problem setters design the problems and evaluate their ECLiPSe is better suited for solving certain common kinds complexity, they keep in mind mostly this crowd of seasoned of programming problems offered in Google Code Jam than algorithmists. imperative programming. We show this by comparing the mental steps required to come up with both kinds of solu- We show that some GCJ problems that should be challeng- tions.
    [Show full text]
  • Competitive Programming
    Competitive Programming Frank Takes LIACS, Leiden University https://liacs.leidenuniv.nl/~takesfw/CP Lecture 1 | Introduction to Competitive Programming Frank Takes | CP | Lecture 1 | Introduction to Competitive Programming 1 / 30 : problem solving, algorithm selection, algorithm design, data structure optimization, complexity analysis, . in a competitive context, i.e., with limited CPU time limited memory consumption a fixed amount of problem solving time (optional) others competing with you (more optional) This is not software engineering, but algorithmic problem solving. About this course Competitive Programming Frank Takes | CP | Lecture 1 | Introduction to Competitive Programming 2 / 30 . in a competitive context, i.e., with limited CPU time limited memory consumption a fixed amount of problem solving time (optional) others competing with you (more optional) This is not software engineering, but algorithmic problem solving. About this course Competitive Programming: problem solving, algorithm selection, algorithm design, data structure optimization, complexity analysis, . Frank Takes | CP | Lecture 1 | Introduction to Competitive Programming 2 / 30 , i.e., with limited CPU time limited memory consumption a fixed amount of problem solving time (optional) others competing with you (more optional) This is not software engineering, but algorithmic problem solving. About this course Competitive Programming: problem solving, algorithm selection, algorithm design, data structure optimization, complexity analysis, . in a competitive context
    [Show full text]
  • Model Answer
    Competitive Programming and Big-O Notation Anson Ho Flow 1. Introduction to competitive programming 2. Skills and advices for competitive programming 3. Big-O Notation Programming • Algorithm – idea, outline – flowchart • Program – codes in specific programming languages • Target – problem solving Competitive Programming • Usually for competitions • More limits on – runtime – memory – resources • time • software • hardware – available programming languages Online judge • HKOI online judge • Codeforces • Codechef • TopCoder • POJ • HDU online judge • AtCoder • May have contests regularly Contest • Annual contest – IOI – NOI – APIO – ACM ICPC – CCC • Open contest – Facebook Hacker Cup – Google Code Jam Contest structure • Individual/ team • Length • Full feedback? • Pretest? • Partial score (subtask)? • Batch score/ score per test • Time penalty? • Hack? Programming languages • Common – C, C++, Java, Pascal, Python, … • HKOI (16/17) – C, C++, Pascal Programming languages • IOI 16 – C++, Pascal, Java – C and Pascal will be removed – Python will be added • NOI 16 – C, C++, Pascal – C and Pascal will be removed in 2020 Environment • Onsite/ online • Operating system • Compiler • IDE/ text editor • Beware of the differences between the computer for coding and the computer for judging Topics • Basic Problem type • Input and output • Interactive • Output only • (Other) Common verdict (HKOI) Verdict (HKOI) • Accepted • Compilation Error • Wrong Answer • Time Limit Exceeded • Runtime Error • Partial Score Verdict (other) • Wrong Output Format •
    [Show full text]
  • Early Introduction of Competitive Programming
    Olympiads in Informatics, 2008, Vol. 2, 149–162 149 © 2008 Institute of Mathematics and Informatics, Vilnius Early Introduction of Competitive Programming Pedro RIBEIRO Departamento de Ciência de Computadores, Faculdade de Ciências, Universidade do Porto Rua do Campo Alegre, 1021/1055, 4169-007 PORTO, Portugal e-mail: [email protected] Pedro GUERREIRO Universidade do Algarve Gambelas, 8005-139 FARO, Portugal e-mail: [email protected] Abstract. Those who enjoy programming enjoy programming competitions, either as contestants or as coaches. Often coaches are teachers, who, aiming at better results in the future, would like to have more and more students participating, from earlier stages. Learning all the basic algorithms takes some time, of course; on the other hand, competition environments can be introduced right from the beginning as a pedagogical tool. If handled correctly, this can be very effective in helping to reach the goals of the course and, as a side-effect, in bringing larger crowds of students into the programming competition arena. Key words: programming contests, computer science education, automatic evaluation systems, competitive programming, introductory programming, IOI, International Olympiads in Informatics. 1. Introduction The most popular programming competitions are geared to imperative languages and to input-output problems. The automatics judges that handle submissions have been custom- arily designed for that environment. In our own programming courses, at our universities, we are using one such judge as a learning tool. Students submit their programming as- signments to the judge, with the benefit of immediate feedback, more reliable than what could be provided by a teaching assistant. Moreover, the automatic judge publishes a ranking of the students by number of accepted submissions, and this induces a healthy competitive attitude that many students enjoy and that makes them work harder and in a more disciplined way than they would otherwise.
    [Show full text]
  • If I Am Not Good at Solving the Problems on the Competitive Programming Sites Like Codechef Or Hackerrank, Where Am I Lagging? - Quora
    9/28/2014 If I am not good at solving the problems on the competitive programming sites like CodeChef or Hackerrank, where am I lagging? - Quora QUESTION TOPICS If I am not good at solving the problems on the RELATED QUESTIONS competitive programming sites like CodeChef or HackerRank CodeChef: I am in my third year of Hackerrank, where am I lagging? university now. What should be my Codeforces strategy so that I am comfortable with I am a second year undergrad at one of the IITs and very decent with my CPI Sphere Online Judge solving problems of gene... (continue) (SPOJ) as of now. I have tried quite a few times to start with the likes of above mentioned sites but even the basic level questions take a long time for me to Computer Programming: Why am I CodeChef unable to concentrate in problem solving, get completed? If I know the programming language, if I understand the coding, reading, poor at math? TopCoder questions, where is the fallacy on my part that is preventing me from getting Competitive over them(solving questions) quickly and efficiently? I am quite motivated towards Programming programming, but there is a phase when I am unable to solve most of the problems. Software Follow Question 190 Comment Share 2 Downvote How do I ge... (continue) Programming Languages I am new to competitive programming, just joined CodeChef 10 days back. I am Indian Institutes of Sumit Saurabh finding the easy level questions very Technology (IITs) Edit Bio • Make Anonymous difficu... (continue) Computer Science Write your answer, or answer later.
    [Show full text]
  • Understanding Unsolvable Problem
    Olympiads in Informatics, 2016, Vol. 10, 87–98 87 © 2016 IOI, Vilnius University DOI: 10.15388/ioi.2016.06 Understanding Unsolvable Problem Jonathan Irvin GUNAWAN Undergraduate Student School of Computing, National University of Singapore Computing 1, 13 Computing Drive, Singapore 117417 e-mail: [email protected] Abstract. In recent IOIs, there are several problems that seem unsolvable, until we realise that there is a special case to the problem that makes it tractable. In IOI 2014, the problem ‘Friend’ appears to be a standard NP-hard Maximum Independent Set problem. However, the graph is gen- erated in a very special way, hence there is a way to solve the problem in polynomial time. There were several contestants who didn’t identify the special case in this problem, and hence were stuck at the problem. In this paper, we will study a well-known technique called reduction to show that a problem we are currently tackling is intractable. In addition, we introduce techniques to identify special cases such that contestants will be prepared to tackle these problems. Keywords: special case, unsolvable, NP-hard. 1. Introduction The problem ‘Friend’ in IOI 2014 required contestants to find a set of vertices with maxi- mum total weight, such that no two vertices in the set are sharing a common edge. This is a classical Weighted Maximum Independent Set problem. We can show that Weight- ed Maximum Independent Set problem is NP-hard by reduction from 3-SAT (Cormen et al., 2009). Since the formulation of NP-completeness 4 decades ago, no one has been able to propose a solution to any NP-hard problem in polynomial time.
    [Show full text]
  • A Competitive Programming Approach to a University Introductory Algorithms Course
    Olympiads in Informatics, 2017, Vol. 11, 87–92 87 © 2017 IOI, Vilnius University DOI: 10.15388/ioi.2017.07 A Competitive Programming Approach to a University Introductory Algorithms Course Antti LAAKSONEN Department of Computer Science University of Helsinki e-mail: [email protected] Abstract. This paper is based on our experiences on teaching a university introductory algorithms course using ideas from competitive programming. The problems are solved using a real program- ming language and automatically tested using a set of test cases. Like in programming contests, there are no hints and well-known problems are not used. The purpose of such problems, com- pared to traditional problems, is to better improve the problem solving skills of the students. Keywords: algorithms course, competitive programming. 1. Introduction This paper summarizes our experiences on teaching the Data Structures and Algorithms course at the University of Helsinki using ideas from competitive programming. The course deals with basic data structures and algorithms, such as trees, graphs and sorting. The course is a compulsory course for computer science students, and it is usually taken during the first year of studies. The course book is Introduction to Algorithms (Cormen et al., 2009), though the course covers only a part of the book. For some years ago, the course was purely theoretic and algorithm design problems were solved using pen and paper and discussed in exercise sessions. However, it was observed that the learning results were not good and many students had difficulties in de- signing even very simple algorithms. After this, some ideas from competitive program- ming have been used on the course to improve the student’s problem solving skills.
    [Show full text]
  • A Survey on Online Judge Systems and Their Applications
    1 A Survey on Online Judge Systems and Their Applications SZYMON WASIK∗†, Poznan University of Technology and Polish Academy of Sciences MACIEJ ANTCZAK, Poznan University of Technology JAN BADURA, Poznan University of Technology ARTUR LASKOWSKI, Poznan University of Technology TOMASZ STERNAL, Poznan University of Technology Online judges are systems designed for the reliable evaluation of algorithm source code submitted by users, which is next compiled and tested in a homogeneous environment. Online judges are becoming popular in various applications. Thus, we would like to review the state of the art for these systems. We classify them according to their principal objectives into systems supporting organization of competitive programming contests, enhancing education and recruitment processes, facilitating the solving of data mining challenges, online compilers and development platforms integrated as components of other custom systems. Moreover, we introduce a formal definition of an online judge system and summarize the common evaluation methodology supported by such systems. Finally, we briefly discuss an Optil.io platform as an example of an online judge system, which has been proposed for the solving of complex optimization problems. We also analyze the competition results conducted using this platform. The competition proved that online judge systems, strengthened by crowdsourcing concepts, can be successfully applied to accurately and efficiently solve complex industrial- and science-driven challenges. CCS Concepts: •General and reference ! Evaluation; •Mathematics of computing ! Combinatorics; Discrete optimization; •Theory of computation ! Design and analysis of algorithms; •Networks ! Cloud computing; Additional Key Words and Phrases: online judge, crowdsourcing, evaluation as a service, challenge, contest ACM Reference format: Szymon Wasik, Maciej Antczak, Jan Badura, Artur Laskowski, and Tomasz Sternal.
    [Show full text]
  • Competitive Programmer's Handbook
    Competitive Programmer’s Handbook Antti Laaksonen Draft August 19, 2019 ii Contents Preface ix I Basic techniques 1 1 Introduction 3 1.1 Programming languages . .3 1.2 Input and output . .4 1.3 Working with numbers . .6 1.4 Shortening code . .8 1.5 Mathematics . 10 1.6 Contests and resources . 15 2 Time complexity 17 2.1 Calculation rules . 17 2.2 Complexity classes . 20 2.3 Estimating efficiency . 21 2.4 Maximum subarray sum . 21 3 Sorting 25 3.1 Sorting theory . 25 3.2 Sorting in C++ . 29 3.3 Binary search . 31 4 Data structures 35 4.1 Dynamic arrays . 35 4.2 Set structures . 37 4.3 Map structures . 38 4.4 Iterators and ranges . 39 4.5 Other structures . 41 4.6 Comparison to sorting . 44 5 Complete search 47 5.1 Generating subsets . 47 5.2 Generating permutations . 49 5.3 Backtracking . 50 5.4 Pruning the search . 51 5.5 Meet in the middle . 54 iii 6 Greedy algorithms 57 6.1 Coin problem . 57 6.2 Scheduling . 58 6.3 Tasks and deadlines . 60 6.4 Minimizing sums . 61 6.5 Data compression . 62 7 Dynamic programming 65 7.1 Coin problem . 65 7.2 Longest increasing subsequence . 70 7.3 Paths in a grid . 71 7.4 Knapsack problems . 72 7.5 Edit distance . 74 7.6 Counting tilings . 75 8 Amortized analysis 77 8.1 Two pointers method . 77 8.2 Nearest smaller elements . 79 8.3 Sliding window minimum . 81 9 Range queries 83 9.1 Static array queries .
    [Show full text]
  • Interactive Coding Platform for Students
    International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-7 Issue-4S, November 2018 Interactive Coding Platform for Students T.K. Chandru, M. Dinesh Kumar, S. Karthikeyan, K. Saranya Abstract: Programming has become one of the most demanded There will always be a need for developers, because our skill of a working professional in almost every industry. Even need for apps and software is steadily growing. Regardless though we have a lot of platform to work on and learn from, we of what background you have, the ability to contribute to are not properly trained in this domain . This has increased the need for a platform that is targeted only for the colleges students software means that you are always employable, always able to develop a coding culture among them , right from the start. to create and advance technology and always able to be on The project that we aim to develop solves this particular issue and the cutting edge of innovation. The pace to solve and code a will also enhance the skills of the students by continuous program will considerably increase only upon continuous feedback learning. The end-product will be a web application practice and here is a platform for it. Whether it is for which the teachers can use to set problems and give assignments personal growth and development, career advancement, while the students will use the application to solve the assignments. The application will be developed using: VueJS in career change, or just a desire to improve digital literacy, the front-end, the database will be MongoDB and the back-end knowledge of how software works and the ability to will be composed of ExpressJS and NodeJS entities.
    [Show full text]
  • A New Book on Competitive Programming (167-170)
    Olympiads in Informatics, 2017, Vol. 11, 167–170 167 © 2017 IOI, Vilnius University DOI: 10.15388/ioi.2017.14 REVIEWS, COMMENTS A New Book on Competitive Programming Antti LAAKSONEN Department of Computer Science University of Helsinki e-mail: [email protected] Abstract: This paper presents a new book on competitive programming: Competitive Program- mer’s Handbook. The purpose of the book is to provide a modern introduction to competitive programming, and the book is especially intended for future IOI and ICPC participants. Keywords: competitive programming, book 1 Introduction While the popularity of competitive programming is growing every year, there are not many books devoted to the topic. Thus, in 2013, I started the project of writing a new book on competitive programming. The purpose of the book is to give a thorough in- troduction to modern competitive programming and to be accessible to readers without background in programming contests. Initially I wrote the book in Finnish, and I had to rewrote the entire book several times before the result was satisfactory. Then, in 2016, I decided to translate the book into English, because most people in the competitive programming community can’t read Finnish. The title of the book became Competitive Programmer’s Handbook (in Finnish: Kisakoodarin käsikirja). Of course, before writing the book, I carefully studied the existing books on competi- tive programming. In 2003, Skiena and Revilla wrote the pioneering book in the field, Programming Challenges. Then, between 2010 and 2013, the Halim brothers published three books called Competitive Programming 1–3. My book would resemble those 168 A.
    [Show full text]