The Algorithm Design Manual (Texts in Computer Science)
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- Create Date：2022-12-28 09:53:57
- Update Date：2025-09-07
- Status：finish
- Author：Steven S. Skiena
- ISBN：3030542580
- Environment：PC/Android/iPhone/iPad/Kindle
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Summary
This book/CD-ROM package is a handy reference for working professionals who use algorithms on a daily basis。 Practical Algorithm Design takes the "mystery" out of algorithms which readers encounter in the workplace by identifying and explaining them。 A major feature of this book is the inclusion of a complete "catalog" of important algorithmic problems。 By browsing this catalog， readers can quickly identify the name of the problem they have encountered， what is known about it， and how they should proceed if they need to solve it。 Nothing like this catalog currently exists in computing literature for general computer algorithms。
Reviews
MyBookJournal
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Difficult subject。 The second half has a nice set of graph problems to review for quizzes。 Not for beginners。 Start with Introduction to Algorithms by Cormen。 Unless you're an algorist for a living or a masochist the real world will rust your algo skills。 Difficult subject。 The second half has a nice set of graph problems to review for quizzes。 Not for beginners。 Start with Introduction to Algorithms by Cormen。 Unless you're an algorist for a living or a masochist the real world will rust your algo skills。 。。。more
Nick Greenquist
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Long and difficult book to get through。 I did most of the problems but started skipping many towards the final chapters （8 and 9）。 I also skipped all the problems in chapter 10， which dealt with NP hard problems and approximate algos and more proofy ones about reducing problems down to satisfiability。 This was mostly because I already knew going in that I wasnt interested in those sections （did them and school and realized that they're not that useful unless you go into research or academia）。 Bu Long and difficult book to get through。 I did most of the problems but started skipping many towards the final chapters （8 and 9）。 I also skipped all the problems in chapter 10， which dealt with NP hard problems and approximate algos and more proofy ones about reducing problems down to satisfiability。 This was mostly because I already knew going in that I wasnt interested in those sections （did them and school and realized that they're not that useful unless you go into research or academia）。 But regardless， the reason for the 3 stars is that this book tries to straddle the middle of being a practical interview prep book and being a proof heavy， theoretical Algo book。 If I were to go back in time， I'd probably pick either a 100% practical Algo book or something like CLRS for very rigorous understanding。 。。。more
Tech Nossomy
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Comprehensive albeit verbose book on algorithms for computational problems。 Target audience primarily undergraduate computer scientists， but will be helpful to more seasoned software developers and scientists as well。 Written in the first person。 Applicability in a wide range of industry sectors is well argued。 Bibliography spans 40+ pages， giving ample opportunity for further research。Second edition still contains a typo here and there （eg page 43: S（n） =≥ （n/2） × （n/2）） and verbosity could hav Comprehensive albeit verbose book on algorithms for computational problems。 Target audience primarily undergraduate computer scientists， but will be helpful to more seasoned software developers and scientists as well。 Written in the first person。 Applicability in a wide range of industry sectors is well argued。 Bibliography spans 40+ pages， giving ample opportunity for further research。Second edition still contains a typo here and there （eg page 43: S（n） =≥ （n/2） × （n/2）） and verbosity could have been replaced with more rigorous treatment of algorithm runtime analysis， although author discounts for this editorial choice on page 57。 。。。more
祝雅逸
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no！
Jamie CULPON
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A bit too heavy duty for a textbook or quick reference， but the “war stories” are amusing enough。
Michael Burnam-Fink
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Skiena is incredible！I'll be upfront that I'm a pragmatist as a programmer。 I some actual training in data science and machine learning， which is arcane enough on it's own， and a few years experience to call myself Good With Pandas， but the thing about being an autodidact solving a limited set of business problems in Python is that you miss the big picture。 In a mature ecosystem like Python， a lot of the time the right answer is just "pip install magiclib。 from magiclib import incantation。 bar = Skiena is incredible！I'll be upfront that I'm a pragmatist as a programmer。 I some actual training in data science and machine learning， which is arcane enough on it's own， and a few years experience to call myself Good With Pandas， but the thing about being an autodidact solving a limited set of business problems in Python is that you miss the big picture。 In a mature ecosystem like Python， a lot of the time the right answer is just "pip install magiclib。 from magiclib import incantation。 bar = incantation（foo）" Except sometimes magiclib doesn't exist yet。 At the end of the day， computers are all Turing machines， they all solve the same sets of problems， but some approaches are algorithmically tractable， and some will leave you lost in the Swamp of Sadness。Artax has been asked to solve a large NP complete problemFor someone who's never taken CS101， this book an eye-opener into the hows and whys of basic data structures like linked lists， trees， hash tables， and arrays， as well as sorting techniques and more advanced practices like dynamic programming。 Clear explainers are interspersed with practical war stories， where Skiena explains how he applied the technique just discussed to solve a previously intractable problem。Cracking the Coding interview is a series of dog tricks。 The Algorithm Design Manual is actual knowledge。 It's been a great guide to actually thinking like a professional， even if most of the day job is data plumbing。 。。。more
Benjamin Smith
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A must read for budding computer scientists and software engineers。 War stories are an excellent complement to the technical details
Ivan Koma
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（FR） Я бы мог начать выпендриваться и восторгаться книгой， но для людей с моим интеллектом могут возникнуть проблемы。。。 Я вообще не понял вторую главу дальше началаМне всегда казалось что если ты пишешь книгу， ты должен написать ее на таком языке， чтобы даже самый тупой человек （я） мог немного понять её， тут же у меня было ощущение， что кто-то решил поиграться "нейронными мускулами"， это конечно не претензия， просто когда я читал становилось скучно， и это при том что я люблю формулы и прочее， но （FR） Я бы мог начать выпендриваться и восторгаться книгой， но для людей с моим интеллектом могут возникнуть проблемы。。。 Я вообще не понял вторую главу дальше началаМне всегда казалось что если ты пишешь книгу， ты должен написать ее на таком языке， чтобы даже самый тупой человек （я） мог немного понять её， тут же у меня было ощущение， что кто-то решил поиграться "нейронными мускулами"， это конечно не претензия， просто когда я читал становилось скучно， и это при том что я люблю формулы и прочее， но примеры просто что-то， чем ты не проникаешься， а порой и вообще не понимаешь что это за ерунда （ясновиденью привет）Сразу говорю что читал в русском переводе， может быть это сказалось， но иногда хочется что-то читнуть на своем языке， возможно это не лучшая идея， распространять такую хотелку на технические книгиИ еще в книге 60% упражнений， решил ли кто-нибудь их все， останется загадкой навсегда。。。 。。。more
Weston
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An excellent resource， the section in the back is great for a reference or just to read。 I love the idea of the war stories， although some of them are difficult to follow or slightly dated。The only real complaint I have about the book is a number of mistakes littered about。 Some of them are small grammatical mistakes， but some are actually missing lines in algorithms， which can be super confusing。
Manish Khokhar
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4。9Book is simple （a good thing） and very much fun to read。 Beginners， who want to read only 1 book should pick it up and see if it is suits their taste。 Readers looking for more formal/mathematical material can supplement it with additional books like CLRS or Knuth later。
Mi Lia
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One can never say that he's done reading this book。 As it's one of the books that you return all the time to。 Very practical as a handbook as half of it is like a dictionary of algorithms and the problem each one of them solves。 The author gives lots of code samples in-text in C。 Very well written， humorous， and practical。 If you need a first book for your Algorithms and Data Structures class， start with this one。 Then go to the bible （CLRS）。 Great job prof。 Skiena。 One can never say that he's done reading this book。 As it's one of the books that you return all the time to。 Very practical as a handbook as half of it is like a dictionary of algorithms and the problem each one of them solves。 The author gives lots of code samples in-text in C。 Very well written， humorous， and practical。 If you need a first book for your Algorithms and Data Structures class， start with this one。 Then go to the bible （CLRS）。 Great job prof。 Skiena。 。。。more
Harry Harman
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Indispensable reading for any computer scientist。An algorithm is a procedure that takes any of the possible input instances and transforms it to the desired output。In industrial settings， any program that seems to give good enough answers without slowing the application down is often acceptable， regardless of whether a better algorithm exists。 The issue of finding the best possible answer or achieving maximum efficiency usually arises in industry only after serious performance or legal troubles
Sophie
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Though this is a 1998 edition， it explains essential algorithms concisely。Notespp。 28-32Fundamental Data Types1。 Containers: • Fundamental Operations: Put（C，x）: Insert a new data item x into the container C。Get（C）: Retrieve the next item from the container C。 Different types of containers support different retrieval orders， based on insertion order or position。• Popular Types of Containers: （1） Stacks - Last in， first out （LIFO）。 The put and get operations for stacks are usually called push and Though this is a 1998 edition， it explains essential algorithms concisely。Notespp。 28-32Fundamental Data Types1。 Containers: • Fundamental Operations: Put（C，x）: Insert a new data item x into the container C。Get（C）: Retrieve the next item from the container C。 Different types of containers support different retrieval orders， based on insertion order or position。• Popular Types of Containers: （1） Stacks - Last in， first out （LIFO）。 The put and get operations for stacks are usually called push and pop。（2） Queues - First in， first out （FIFO）。 The put and get operations for stacks are usually called enqueue and dequeue。（3） Tables: Supports retrieval by position， so that put and get each accept an index as an argument。 Tables are naturally implemented using arrays。2。 Dictionaries: • Primary Operations:Search（D， k）: Given a search key k， return a pointer to the element in dictionary D whose key value is k， if one exists。Insert（D， x）: Given a data item x， add it to the set of items in the dictionary D。Delete（D， x）: Given a pointer to a given data item x in the dictionary D， remove it from D。• Certain dictionary data structures support the following operations:Max（D） or Min（D）Predecessor（D， k） or Successor（D， k）3。 Binary Search Trees4。 Priority Queuespp。 36-38Approaches to Sorting1。 Data Structures: Repeatedly extracts the smallest remaining element from the unsorted part of the set but will take a total of O（n^2）time aka heapsort。 SelectionSort（A） For i = 1 to n doSort[i] = Find-Minimum from A Delete-Minimum from A Return（Sort） 2。 Incremental Insertion: Select an arbitrary element from the unsorted set， and put it in the proper position in the sorted set。 Though it takes O（n^2） in the worst scenario， it will perform much better if the data is sorted。 InsertionSort（A）A[0] = -∞ for i = 1 to n - 1 doj = i while （A[j] > A[j-1]） do swap（A[j]， A[j-1]） 3。 Divide and Conquer: Suppose we take n elements to sort and split them into piles S and T， each with half the elements。 After sorting both piles， it is easy to combine the two sorted piles and takes O（n log n） in the worst scenario。 MergeSort（A[1， n]） Merge（ MergeSort（A[1， [n/2]]）， MergeSort（A[[n/2] + 1， n]）） 4。 Randomization5。 Bucketing Techniques 。。。more
Andrew
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As recommended by Jaana Dogan 。 As recommended by Jaana Dogan 。 。。。more
Samvid Mistry
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Fundamental Computer Science algorithms with applications to modern problems。 Worth it even if you read only war stories。
Bookich Store
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The ebook The Algorithm Design Manual （Texts in Computer Science） covers all the basic algorithms that any and every programmer and data scientist is expected to know。for anybody with a CS degree， this is just a review。 –– but I like only having to look in a single book for all the basic algorithms。Buy the ebook now:The Algorithm Design Manual （Texts in Computer Science） 3rd ed。 2020 Edition The ebook The Algorithm Design Manual （Texts in Computer Science） covers all the basic algorithms that any and every programmer and data scientist is expected to know。for anybody with a CS degree， this is just a review。 –– but I like only having to look in a single book for all the basic algorithms。Buy the ebook now:The Algorithm Design Manual （Texts in Computer Science） 3rd ed。 2020 Edition 。。。more
Christina
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If you are a self taught software engineer like myself this book is an amazing resource for not only preparing for technical interviews but getting into a rhythm of thinking like a computer scientist and breaking from being just a programmer
Vibhor Rawal
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When I picked it up， I instantly became a fan of Skiena。 Some of the writings span beyond algorithm design and it was a delight reading those。 Especially the war stories helped as a reader to get a clearer picture of an algorist's job。 Though in my opinion the book deteriorates in writing quality （not knowledge imparted per chapter）， it still is a good design manual， don't get me wrong the worst pages of this book felt superior to some other books out their。====================================== When I picked it up， I instantly became a fan of Skiena。 Some of the writings span beyond algorithm design and it was a delight reading those。 Especially the war stories helped as a reader to get a clearer picture of an algorist's job。 Though in my opinion the book deteriorates in writing quality （not knowledge imparted per chapter）， it still is a good design manual， don't get me wrong the worst pages of this book felt superior to some other books out their。===========================================Here are some of the wordings that were a sugar candy to read-Proofs are useful only when they are honest。Pseudocode is perhaps the most mysterious of the bunch， but it is best defined as a programming language that never complains about syntax errors。recursion is mathematical induction。a computer scientist is a mathematician who only knows how to prove things by induction。algorist as “one skillful in reckonings or figuring。”The moral of logarithmic growth is clear: “If you are gonna do the crime， make it worth the time！”An Ω（n log n） lower bound can be shown by observing that any sorting algorithm must behave differently during execution on each of the distinct n！ permutations of n keys。 The outcome of each pairwise comparison governs the run-time behavior of any comparison-based sorting algorithm。 We can think of the set of all possible executions of such an algorithm as a tree with n！ leaves。 The minimum height tree corresponds to the fastest possible algorithm， and it happens that lg（n！） = Θ（n log n）。Strategy represents the quest for the big picture—the framework around which we construct our path to the goal。 Tactics are used to win the minor battles we must fight along the way。 In problem-solving， it is important to check repeatedly whether you are thinking on the right level。 If you do not have a global strategy of how you are going to attack your problem， it is pointless to worry about the tactics。===========================================This book definitely helps solidify some ideas， but the second half didn't sell for me （where it's all here's some algos， these are the places you will find them， ask these questions to yourself for finding how and if to use these） 。 It did not feel thorough in the sense that most of the algos given are briefly discussed and their implementation is out of the bounds of the book， maybe it suffices it's purpose and for some it will be a blessing to find the references material and latch onto it for more information。 But for me it distinguished this book from a 5 star to a 4。 。。。more
Rydzyn
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Certainly worth a read。 I give it 5 stars because it certainly deserves 4， and I'd love more software developers to read it :）。I liked that algorithms were not presented in vacuum。 Quite the opposite。 A lot of attention is placed on practical applications of algorithms。 Author talks a lot about ways to recognize that many popular problems can be solved using popular algorithms。In my opinion， this book has a very pragmatic approach。 It doesn't go into details of flavors of algorithms that most de Certainly worth a read。 I give it 5 stars because it certainly deserves 4， and I'd love more software developers to read it :）。I liked that algorithms were not presented in vacuum。 Quite the opposite。 A lot of attention is placed on practical applications of algorithms。 Author talks a lot about ways to recognize that many popular problems can be solved using popular algorithms。In my opinion， this book has a very pragmatic approach。 It doesn't go into details of flavors of algorithms that most developers won't need in their daily work。 At the same time， it offers a broad overview of many topics， so you know what is there。Consequently， implementation is usually shown for the basic algorithms， and half of the book is a catalog of problems with references to existing libraries implementing solutions。I liked how the book teaches techniques more than algorithms itself。 For example， when it gets to graphs， it features implementations of depth-first-search and breadth-first-search as customizable templates。 Then several other algorithms are presented as a simple variations on DFS or BFS。 In the chapter about dynamic programming， instead of discussing just one specific implementation of the classic edit distance algorithm， it describes a lot of variations where slight modifications to the "edit distance" can be used to solve different problems。 When presenting NP problems， author teaches you how to recognize if your problem is NP or not， so you know if you should look for an efficient algorithm or settle for a heuristic。Because of that focus on design and techniques， the book misses many popular algorithms that other books usually include。 In this book， you will not find: A*， details of various flavors of hash tables， details of splay trees， red-black trees， KMP pattern searching， and so on。 On the other hand， you may have to research some topics like that yourself when doing exercises。If you have time to do exercises， I strongly encourage that。 They'll give you insights， let you practice what you've just learned or show where techniques discussed in the chapter fail to work。 Exercises are divided into sections so you can quickly pick one that you like。 E。g。 interview problems are listed separately， and in my career I have actually been asked some of these questions on job interviews。 Exercises are also graded by difficulty。 I saw reviews that compare this book with Cormen's "Introduction To Algorithms"。 There is overlap， but also the style and focus of these two books are very different。 Depending on your needs， you may like one more than the other。 。。。more
Kirill
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Most of the books in this category provide a rigorous catalog of different algorithmic problems and their solutions， and this one is not an exception。 At least its second part。 What makes this books stand out is its first half。 There， author provides a practical view on solving algorithmic problems， providing intuitive explanations of the major problems in each category。 Each of the first 10 chapters also contain war stories， where the algorithms are brought to real practical applications based Most of the books in this category provide a rigorous catalog of different algorithmic problems and their solutions， and this one is not an exception。 At least its second part。 What makes this books stand out is its first half。 There， author provides a practical view on solving algorithmic problems， providing intuitive explanations of the major problems in each category。 Each of the first 10 chapters also contain war stories， where the algorithms are brought to real practical applications based on the author’s experience。And if you’ll need a more complete reference， the second part of the book contains a more traditional collection of various algorithms with topics ranging from sorting to black box optimization。 。。。more
Priyavasanthan Pandiyan
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Best of the algorithms book read among a lot of others。 Real time challenges with progressive optimization。 The best of it how the Data structure themself are built and why they are built the way that it is。 Worth keeping as a companion for CS career。
Matt McCormick
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A very thorough book but I found that the explanations for most algorithms could have been better。 I found it to be more of a reference book for looking up how to write an algorithm if you need one rather than learning well about a variety of algorithms。
Philippe Fanaro
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A work of art and mastery of many fields。 Decades and decades of research in addition to the much more valuable big picture of their integration。 This is *the* book to bridge the gap between theory and practice。I don't know if this book could be read with someone with zero knowledge of the topics involved。 I am a graduate student of electrical engineering who knew a reasonable lot before trying this book out and， still， couldn't read more than 40-60 pages a day （I separated 2 weeks off for this A work of art and mastery of many fields。 Decades and decades of research in addition to the much more valuable big picture of their integration。 This is *the* book to bridge the gap between theory and practice。I don't know if this book could be read with someone with zero knowledge of the topics involved。 I am a graduate student of electrical engineering who knew a reasonable lot before trying this book out and， still， couldn't read more than 40-60 pages a day （I separated 2 weeks off for this book）。 。。。more
Priyanka Shah
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Amazing and informative book for anyone interested in knowing how algorithms shape the world we live and power almost all the electronic machines we interact with on day to day basis。 Most importantly gives you a zoom out version to analyze and breakdown big problems into small informative chunks which can then be processed to get a value。
Edmund
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One of the best introductory texts to Algorithms， and introduces many of the topics in an easy to understand way。
Scott Holstad
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A pretty good resource and one of the better books on the subject， in my opinion。 However， many describe it as "introductory" algorithms， and I'm not sure I totally agree。 Unless you already posses a solid foundation in related areas， a newbie will often find it hard to walk into this and immediately understand it。 And maybe some will say that would be unrealistic， and I would be one of those。 However， I actually have heard and seen others say exactly that， and again， I don't agree。 Nonetheless， A pretty good resource and one of the better books on the subject， in my opinion。 However， many describe it as "introductory" algorithms， and I'm not sure I totally agree。 Unless you already posses a solid foundation in related areas， a newbie will often find it hard to walk into this and immediately understand it。 And maybe some will say that would be unrealistic， and I would be one of those。 However， I actually have heard and seen others say exactly that， and again， I don't agree。 Nonetheless， a pretty good book and solid resource。 Recommended。 。。。more
Danial Kalbasi
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A useful read for anyone who likes to have a deeper understanding of algorithm design。 The book covers many aspects such as time/space complexity， NP-completeness， and many other concepts。 The part that I personally really appreciate was the first few chapters about how to set our mindset to design an algorithm。This book， like most academic books， is hard to read and comprehend and needs the reader to do more research about the subjects。 I wish people who write these books， they come out of thei A useful read for anyone who likes to have a deeper understanding of algorithm design。 The book covers many aspects such as time/space complexity， NP-completeness， and many other concepts。 The part that I personally really appreciate was the first few chapters about how to set our mindset to design an algorithm。This book， like most academic books， is hard to read and comprehend and needs the reader to do more research about the subjects。 I wish people who write these books， they come out of their academic cave。 It doesn't need to use complex writing structures or tough vocabularies to explain a simple idea。This book， of course， is not something you read from A to Z。 It's probably good as a reference。 。。。more
Alexey Zorin
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This book is just a bit less academic and a bit more casual than the famous "Introduction to Algorithms" however it's all about applications。Every chapter starts off with a problem statement， then questions are asked to help identify hidden nuances of the problem， followed by a "War story" showing where exactly that particular algorithm found it's application and tricky exercises of course。Author provides dozens of references to each topic so the reader could study the particular subject in deta This book is just a bit less academic and a bit more casual than the famous "Introduction to Algorithms" however it's all about applications。Every chapter starts off with a problem statement， then questions are asked to help identify hidden nuances of the problem， followed by a "War story" showing where exactly that particular algorithm found it's application and tricky exercises of course。Author provides dozens of references to each topic so the reader could study the particular subject in details。As well as "Introduction to Algorithms" it requires a strong background in Math （geometry， calculus） and CS。 。。。more
Vikas Srivastava
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An excellent book taking a hands approach on solving algorithmic problems。 A brief introduction to the algorithms followed by specific implementations of everyday problems makes it truly a ‘Hitchhiker’s Guide to Algorithms’
Sebastian Baker
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