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<h1 id="01-about-this-book">0.1 &nbsp; About This Book<a class="headerlink" href="#01-about-this-book" title="Permanent link">&para;</a></h1>
<p>This project aims to create an open-source, free, beginner-friendly introductory tutorial on data structures and algorithms.</p>
<ul>
<li>The entire book uses animated illustrations, with clear and easy-to-understand content and a smooth learning curve, guiding beginners to explore the knowledge map of data structures and algorithms.</li>
<li>The source code can be run with one click, helping readers improve their programming skills through practice and understand how algorithms work and the underlying implementation of data structures.</li>
<li>We encourage readers to learn from each other, and everyone is welcome to ask questions and share insights in the comments section, making progress together through discussion and exchange.</li>
</ul>
<h2 id="011-target-audience">0.1.1 &nbsp; Target Audience<a class="headerlink" href="#011-target-audience" title="Permanent link">&para;</a></h2>
<p>If you are an algorithm beginner who has never been exposed to algorithms, or if you already have some problem-solving experience and have a vague understanding of data structures and algorithms, oscillating between knowing and not knowing, then this book is tailor-made for you!</p>
<p>If you have already accumulated a certain amount of problem-solving experience and are familiar with most question types, this book can help you review and organize your algorithm knowledge system, and the repository's source code can be used as a "problem-solving toolkit" or "algorithm dictionary."</p>
<p>If you are an algorithm "expert," we look forward to receiving your valuable suggestions, or <a href="https://www.hello-algo.com/chapter_appendix/contribution/">participating in creation together</a>.</p>
<div class="admonition success">
<p class="admonition-title">Prerequisites</p>
<p>You need to have at least a programming foundation in any language, and be able to read and write simple code.</p>
</div>
<h2 id="012-content-structure">0.1.2 &nbsp; Content Structure<a class="headerlink" href="#012-content-structure" title="Permanent link">&para;</a></h2>
<p>The main content of this book is shown in Figure 0-1.</p>
<ul>
<li><strong>Complexity analysis</strong>: Evaluation dimensions and methods for data structures and algorithms. Methods for calculating time complexity and space complexity, common types, examples, etc.</li>
<li><strong>Data structures</strong>: Classification methods for basic data types and data structures. The definition, advantages and disadvantages, common operations, common types, typical applications, implementation methods, etc. of data structures such as arrays, linked lists, stacks, queues, hash tables, trees, heaps, and graphs.</li>
<li><strong>Algorithms</strong>: The definition, advantages and disadvantages, efficiency, application scenarios, problem-solving steps, and example problems of algorithms such as searching, sorting, divide and conquer, backtracking, dynamic programming, and greedy algorithms.</li>
</ul>
<p><a class="glightbox" href="../about_the_book.assets/hello_algo_mindmap.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="Main content of this book" class="animation-figure" src="../about_the_book.assets/hello_algo_mindmap.png" /></a></p>
<p align="center"> Figure 0-1 &nbsp; Main content of this book </p>
<h2 id="013-acknowledgements">0.1.3 &nbsp; Acknowledgements<a class="headerlink" href="#013-acknowledgements" title="Permanent link">&para;</a></h2>
<p>This book has been continuously improved through the joint efforts of many contributors in the open-source community. Thanks to every contributor who invested time and effort, they are (in the order automatically generated by GitHub): krahets, coderonion, Gonglja, nuomi1, Reanon, justin-tse, hpstory, danielsss, curtishd, night-cruise, S-N-O-R-L-A-X, rongyi, msk397, gvenusleo, khoaxuantu, rivertwilight, K3v123, gyt95, zhuoqinyue, yuelinxin, Zuoxun, mingXta, Phoenix0415, FangYuan33, GN-Yu, longsizhuo, IsChristina, xBLACKICEx, guowei-gong, Cathay-Chen, pengchzn, QiLOL, magentaqin, hello-ikun, JoseHung, qualifier1024, thomasq0, sunshinesDL, L-Super, Guanngxu, Transmigration-zhou, WSL0809, Slone123c, lhxsm, yuan0221, what-is-me, Shyam-Chen, theNefelibatas, longranger2, codeberg-user, xiongsp, JeffersonHuang, prinpal, seven1240, Wonderdch, malone6, xiaomiusa87, gaofer, bluebean-cloud, a16su, SamJin98, hongyun-robot, nanlei, XiaChuerwu, yd-j, iron-irax, mgisr, steventimes, junminhong, heshuyue, danny900714, MolDuM, Nigh, Dr-XYZ, XC-Zero, reeswell, PXG-XPG, NI-SW, Horbin-Magician, Enlightenus, YangXuanyi, beatrix-chan, DullSword, xjr7670, jiaxianhua, qq909244296, iStig, boloboloda, hts0000, gledfish, wenjianmin, keshida, kilikilikid, lclc6, lwbaptx, linyejoe2, liuxjerry, llql1211, fbigm, echo1937, szu17dmy, dshlstarr, Yucao-cy, coderlef, czruby, bongbongbakudan, beintentional, ZongYangL, ZhongYuuu, ZhongGuanbin, hezhizhen, linzeyan, ZJKung, luluxia, xb534, ztkuaikuai, yw-1021, ElaBosak233, baagod, zhouLion, yishangzhang, yi427, yanedie, yabo083, weibk, wangwang105, th1nk3r-ing, tao363, 4yDX3906, syd168, sslmj2020, smilelsb, siqyka, selear, sdshaoda, Xi-Row, popozhu, nuquist19, noobcodemaker, XiaoK29, chadyi, lyl625760, lucaswangdev, 0130w, shanghai-Jerry, EJackYang, Javesun99, eltociear, lipusheng, KNChiu, BlindTerran, ShiMaRing, lovelock, FreddieLi, FloranceYeh, fanchenggang, gltianwen, goerll, nedchu, curly210102, CuB3y0nd, KraHsu, CarrotDLaw, youshaoXG, bubble9um, Asashishi, Asa0oo0o0o, fanenr, eagleanurag, akshiterate, 52coder, foursevenlove, KorsChen, GaochaoZhu, hopkings2008, yang-le, realwujing, Evilrabbit520, Umer-Jahangir, Turing-1024-Lee, Suremotoo, paoxiaomooo, Chieko-Seren, Allen-Scai, ymmmas, Risuntsy, Richard-Zhang1019, RafaelCaso, qingpeng9802, primexiao, Urbaner3, zhongfq, nidhoggfgg, MwumLi, CreatorMetaSky, martinx, ZnYang2018, hugtyftg, logan-qiu, psychelzh, Keynman, KeiichiKasai, and KawaiiAsh.</p>
<p>The code review work for this book was completed by coderonion, curtishd, Gonglja, gvenusleo, hpstory, justin-tse, khoaxuantu, krahets, night-cruise, nuomi1, Reanon and rongyi (in alphabetical order). Thanks to them for the time and effort they put in, it is they who ensure the standardization and unity of code in various languages.</p>
<p>The Traditional Chinese version of this book was reviewed by Shyam-Chen and Dr-XYZ, the English version was reviewed by yuelinxin, K3v123, QiLOL, Phoenix0415, SamJin98, yanedie, RafaelCaso, pengchzn, thomasq0 and magentaqin, and the Japanese edition was reviewed by eltociear. It is because of their continuous contributions that this book can serve a wider readership, and we thank them.</p>
<p>The ePub ebook generation tool for this book was developed by zhongfq. We thank him for his contribution, which provides readers with a more flexible way to read.</p>
<p>During the creation of this book, I received help from many people.</p>
<ul>
<li>Thanks to my mentor at the company, Dr. Li Xi, who encouraged me to "take action quickly" during a conversation, strengthening my determination to write this book;</li>
<li>Thanks to my girlfriend Bubble as the first reader of this book, who provided many valuable suggestions from the perspective of an algorithm beginner, making this book more suitable for novices to read;</li>
<li>Thanks to Tengbao, Qibao, and Feibao for coming up with a creative name for this book, evoking everyone's fond memories of writing their first line of code "Hello World!";</li>
<li>Thanks to Xiaoquan for providing professional help in intellectual property rights, which played an important role in the improvement of this open-source book;</li>
<li>Thanks to Sutong for designing the beautiful cover and logo for this book, and for patiently making revisions multiple times driven by my obsessive-compulsive disorder;</li>
<li>Thanks to @squidfunk for the typesetting suggestions, as well as for developing the open-source documentation theme <a href="https://github.com/squidfunk/mkdocs-material/tree/master">Material-for-MkDocs</a>.</li>
</ul>
<p>During the writing process, I read many textbooks and articles on data structures and algorithms. These works provided excellent examples for this book and ensured the accuracy and quality of the book's content. I would like to thank all the teachers and predecessors for their outstanding contributions!</p>
<p>This book advocates a learning method that combines hands and brain, and in this regard I was deeply inspired by <a href="https://github.com/d2l-ai/d2l-zh">Dive into Deep Learning</a>. I highly recommend this excellent work to all readers.</p>
<p><strong>Heartfelt thanks to my parents, it is your support and encouragement that has given me the opportunity to do this interesting thing</strong>.</p>
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