Best Algorithms Books (Part 1)

At any rate, should you wish to navigate to a (much) more detailed overview, elsewhere, on the stuff of algorithmic magic, you’ll find a nice commentary there on—among other algorithms—these ones:

• • Google Search (There was a time not too long ago when search engines battled it out for Internet supremacy) 📌 

• • Facebook’s News Feed (As much as we may be loathe to admit it, the Facebook News Feed is where many of us love to waste our time) ⛱ 

• • NSA Data Collection, Interpretation, and Encryption (We are increasingly being watched not by people, but by algorithms) 🔐 

• • High Frequency Stock Trading (The financial sector has long used algorithms to predict market fluctuations, but they’re also being used in the burgeoning practice of high-frequency stock trading) 📈 

• • MP3 Compression (Algorithms that squeeze data are an indelible and crucial aspect of the digital world) 🔬 
  • And the list goes on and on and…. 🔭

Indeed, as J.R.R. Tolkien memorably observed in the classic book The Fellowship of the Ring

The Road goes ever on and on.

Is Software Really Eating the World?

The question is: Will algorithms remain our servants, or will they overrun as like an out-of-control juggernaut? And should you need further convincing of the juggernaut that algorithms have become, I invite you to check out the superb article Why Software Is Eating the World by Marc Andreessen—yep, the same guy who co-created the highly influential Mosaic Internet browser and cofounded Netscape. The article was originally published in The Wall Street Journal on August 20, 2011. Andreessen was spot on when he presciently noted that 📣

Today’s leading real-world retailer, Wal-Mart, uses software to power its logistics and distribution capabilities, which it has used to crush its competition. Likewise for FedEx, which is best thought of as a software network that happens to have trucks, planes and distribution hubs attached. And the success or failure of airlines today and in the future hinges on their ability to price tickets and optimize routes and yields correctly—with software.

And there is no subject in computer science—at least from a pragmatic and practitioner’s point of view—more central than that of algorithms. My fascination with algorithms, and in particular their applicability to distributed programming, would have us travel back through the mists of time; OK, just kidding, so I’m not that old 😂

Pitstops In Our Journey In The Land Of Algorithms 🚂

I will, though, be casting a glance back at my ongoing and happily endless journey through the landscape of algorithms. As I do so, I’ll be taking an opinionated look at the following books, in turn. With that, I present to you the books which have proved most helpful to me in grokking algorithms:

1. Algorithms 4th Edition (Addison-Wesley) by Robert Sedgewick and Kevin Wayne 🏆
2. Data Structures and Algorithms in Java 6th Edition (Wiley) by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser 🔔
3. The Nature of Computation (Oxford University Press) by Cristopher Moore and Stephan Mertens 🔦
4. Essential Algorithms: A Practical Approach to Computer Algorithms (Wiley) by Rod Stephens 📫
5. Algorithms to Live By: The Computer Science of Human Decisions (Henry Holt and Co.) by Brian Christian and Tom Griffiths 🔐

For those impatiently trying to tell me, Hey Akram, give us the algorithms, and please make it snappy, I will oblige, and herewith submit an opinionated look at the outstanding books in the list above 📘 You have to remember, though, that I might at times be compelled to digress—may I gently remind the reader that this eponymous blog boldly proclaims the byname Programming Digressions somewhere in its title. Rest assured, thought, that those digressions won’t appear until after we’re done taking an up-close-and-personal look at these outstanding books 😇

I mean, we got to have ourselves some fun along the ride, don’t we? 🎈

Oh, and the careful reader will have noted the “(Part 1)”, um, part in the title of this essay: “Best Algorithms Books (Part 1)“. So it is that I plan on writing at least one more essay to do some justice to the finest of the abundant resources available on the subject of algorithms 🍒

1. Algorithms 4th Edition (Addison-Wesley) by Robert Sedgewick and Kevin Wayne 🏆

If you’re looking to read only a single algorithms book, look no farther than the extraordinarily well done volume that is simply entitled Algorithms 4th Edition (Addison-Wesley) by Robert Sedgewick and Kevin Wayne. I’ve gone through a ton of book on the subject of algorithms, over many years, and this gem has emerged as the clear winner 📣

Algorithms by Sedgewick and Wayne has so much that is so good, that I’ll need to break down my assessment into easily digestible chunks 🍔

This book simply can’t be beat for comprehensiveness. Yes, there is CLRS out there—it’s hoary with age and its dryness is right up there with a desiccated Saharan sand dune on an unbearably hot day—but you need to have the gumption of an archeologist to trudge across the pages of CLRS 🐫 I tossed the acronym (CLRS) out there blithely, but I might as well introduce it for newcomers to the field of algorithms: It just so happens that CLRS are the initials of this formidable book’s authors (Cormen, Leiserson, Rivest, and Stein). The book is entitled Introduction to Algorithms 3rd Edition (MIT Press) by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. It does make for a good research book, for finding citations and that sort of thing—for that it’s probably unbeatable—since it happens to be replete, to overflowing, with copious cross-references to the vast literature on algorithms. Given its intimidating style, though, I’m not convinced that it’s a good introductory book on the subject.

But I hear you quizzically ask, Aren’t we supposed to be talking about the Algorithms book by Sedgewick and Wayne? And right you are, except that I had to get CLRS—along with all its desiccated Saharan sand dune heft—off of my chest. So there 😇

In my mind, Algorithms is to the world of algorithms what the Gang Of Four (GoF) book is to the world of software design patterns. Yes, the former is that good, and let me tell you why. For starters, this is an incredibly polished work, much in the tradition of the highly refined GoF book; I’ll boldly venture out to say that Algorithms has set an even higher standard for what a technical book—or non-technical book for that matter—can offer to enhance the reading experience in an endearing and pleasing way. In a similar vein, you may wish to also take a peek at another awesome and incredibly well done book entitled Refactoring to Patterns (Addison-Wesley) by Joshua Kerievsky.

As you’ll come to appreciate, Algorithms is lavishly illustrated, replete with (Java) code that is pleasingly annotated at just the right level of granularity. I’ve seen other books kill trees in the process of regurgitating code snippets that leave me hanging; not this book, no sir! The more time I’ve spent with Algorithms, the more I’ve come to appreciate it as a trusted and expert personal consultant—goodness, the authors seem to have anticipated just about every question that has popped into my head as I pored over this book’s pages over the span of years.

Look, I’m a computer scientist who has been practicing the fine art of programming for over two decades. Nonetheless, we all need access to solid reference books to stay fresh and mindful of the basics. Here I find comfort in the wise words of Edward B. Burger (Southwestern University, Georgetown/Texas) and Michael Starbird (The University of Texas at Austin) who note in their slender yet rich book The 5 Elements of Effective Thinking (Princeton University Press) that

Understand simple things deeply. The most fundamental ideas in any subject can be understood with ever-increasing depth…. True experts continually deepen their mastery of the basics (italics mine).

And Algorithms is a breath of fresh air; you can even read it for sheer aesthetic pleasure 🌹

Some of you may recall Sedgewick’s Algorithms in C++. This book (Algorithms 4th Edition), though, uses Java and is, IMHO, a vast improvement over the old C++ book. It uses a sub-set of the Java object-orientation (OO) features, which actually makes the explanations flow more smoothly; in the process, this also tremendously helps in essentially side-stepping language complications that would surely have arisen had the authors chosen to go beyond using a sub-set of the Java OO features. And heaven forbid, you wouldn’t want an introductory book on algorithms to go past even that, and start looking into blending two seemingly unrelated paradigms (OO and FP) of programming, which has, though, a rightful and important place of its own in advanced aspects of program design 🐚

In sum, the authors of Algorithms use beautifully elegant and thoughtfully illustrative code throughout the book, preferring clarity over verboseness. All in all, pretty much all the essential goods on algorithms are in here, presented richly, dense—in a good condensed way—and with great taste 😎

 

2. Data Structures and Algorithms in Java 6th Edition (Wiley) by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser 🔔

If you’re going to read one more book on algorithms, you’ll want to make it this one: Data Structures and Algorithms in Java 6th Edition (Wiley) by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser.

For starters, the authors of Data Structures and Algorithms in Java succinctly round up the philosophy—in fact the very gist—of the book when they note how

The design and analysis of efficient data structures has long been recognized as a core subject in computing. 

Two standout chapters that I simply have to shout out are the following. Notwithstanding the stellar algorithms book that’s in the top spot, the treatment in Data Structures and Algorithms in Java of a couple of crucially important, thematically-related topics—(1) Maps, Hash Tables, Skip Lists, and (2) Graph Algorithms—simply knocked my socks off. You’ll find the goods on that pair of topics in chapters 10 and 14, respectively.

Consider, too, the care with which the authors explain just about everything you’ll be interested in, at least from a pragmatic standpoint 🐳 In that spirit, check out their sparkling clear coverage of the perennially important topic of Sorting with a Priority Queue. They remind us how 🏄

One application of priority queues is sorting, where we are given a sequence of elements that can be compared according to a total order relation, and we want to rearrange them in increasing order (or at least in nondecreasing order if there are ties). 

Ah, if only more writers would write with such enviable clarity and precision ✂ Thus, with helpful and unambiguous descriptions such as the example above, Data Structures and Algorithms in Java is replete with the very essence of what makes algorithms tick 💎 The language aesthete—and pragmatist—in me believes that you’ll enjoy this marvelous book. I definitely did 🎧

3. The Nature of Computation (Oxford University Press) by Cristopher Moore and Stephan Mertens 🔦

Here’s the deal: We programmers and technologists, too, need inspiration from time to time; inspiration isn’t for artists alone. Lest anyone’s jaw dropped at that observation—saying, hey we’re a cerebral and logical bunch—I will to out on a limb and say that we’re at least as much artists as logical, sentient beings, us programmers. To underscore that precise point, I’ll remind you that there’s an Art in Donald Knuth’s eponymous magnum opus entitled The Art of Computer Programming (Addison-Wesley), which is of course composed of four intense volumes 🎓

And then there is the advice to programmers by David Heinemeier Hansson—the creator of the popular Ruby on Rails web development framework—who noted in his book entitled Rework (Crown Business), which he co-authored with Jason Fried that

When Inspiration Strikes, Strike Back (in a section entitled Inspiration is Perishable)

Having made the case, I suppose, for the rightful place of inspiration, allow me to re-introduce an astonishing book—I had mentioned about it elsewhere, too, many moons ago—which is nothing short of staggering in its potential of unleashing unfettered creativity: The Nature of Computation (Oxford University Press) by Cristopher Moore and Stephan Mertens.

This book—The Nature of Computation—is precisely the one that I had in mind, earlier on in this essay, when I had shared with you the following thought, noting how

Algorithms, more than anything else in the entire fabric of computer science, IMHO, evolve and thrive in the hotbed of creativity, and who better to illustrate this with than the true legend of Kekulé, who saw in a dream a snake eating its own tail, and which led Kekule—upon awaking from his dream—to the monumental discovery of the benzene molecule’s structure 🐍

Fancy that, I’m caught quoting myself in an act of self-referential circularity; this may well invite jabs about self-referential programming magic, as of course enshrined in the fabulous meta-circular evaluator 😆 At any rate, I can’t do any better than what Moore and Mertens themselves have articulated in the splendid Preface—and there is so much that is so splendid about this book—when they share the very origins of The Nature of Computation, telling us how

This book was born in 2005 when one of us was approached by a publisher to write a book explaining computational complexity to physicists. The tale grew in the telling, until we decided—with some hubris—to explain it to everyone, including computer scientists.

For engineers, computer scientists, mathematicians, physicists, and, truth be told, for creativity connoisseurs of all stripes who are looking for a refreshing tour of the amazing intellectual fabric that underlies our universe, I can’t think of a better recommendation than a leisurely—or intensely studious and tactical—dive into the lushly cavernous pages of The Nature of Computation 🏃

Moore and Mertens have obviously lavished great care on knitting together some awesome themes of computation (think algorithms) into a unified thematic whole; I can only aspire to lavishing such care when I set about assembling the quotes and passages for these essays that I write for you ⛄ Consider, for example, these two delightful quotes which the authors use to great effect. Thus, they lead off Chapter 3: Insights and Algorithms with this enchanting quote from—yes, none other than Donald Knuth—whose magnum opus entitled The Art of Computer Programming I had mentioned just a breath away. They quote him as opining how

It has often been said that a person does not really understand something until he teaches it to someone else. Actually a person does not really understand something until he can teach it to a computer, i.e., express it as an algorithm… The attempt to formalize things as algorithms leads to a much deeper understanding than if we simply try to comprehend things in the traditional way.

~ Donald E. Knuth

Then, and in fact earlier still in The Nature of Computation, in a sub-section of the Preface that’s entitled How to read this book, they naughtily let us in on the starling secret that 🐕

Outside a dog a book is a man’s best friend. Inside a dog it’s too dark to read

~ Groucho Marx (italics mine)

Placing a marker here, as I need to revisit another peachy book by the source of the first quote above—Scott Aaronson (MIT)—which is entitled Quantum Computing since Democritus . Oh, and the money I spent on buying a copy of The Nature of Computation—and this was ages ago, or so it seems anyway—is some of the best investment I’ve ever made. Period. Expect to be repaid at an exponentially compounded rate 🚀

4. Essential Algorithms: A Practical Approach to Computer Algorithms (Wiley) by Rod Stephens 📫

Next up we have an eminently user friendly book on algorithms entitled Essential Algorithms: A Practical Approach to Computer Algorithms (Wiley) by Rod Stephens. It’s written in a pleasant and thoughtful tone, with the author neither talking down to the reader nor dumbing down the material in the least. The balance thus achieved, plus the blending of the granularity level, really hit the sweet spot for me 🍯, reminding me (albeit in a tangential way) of the following quote, from an essay elsewhere, where I was citing someone as saying that

Scala provides the tools needed to blend the object-oriented and functional programming worlds. Scala is at its best when these two evenly share a codebase. The biggest danger to misusing Scala is to ignore its object orientation or its functional programming. But combining the two is the sweet spot that the language was designed to fulfill (italics mine).

Oh, and check out the author’s endearingly smart introduction to how he came upon making the field of algorithms his own. When you get yourself a copy of this, you’ll be regaled with how 😂

Rod Stephens started out as a mathematician, but while studying at MIT, he discovered how much fun algorithms are. He took every algorithms course MIT offered and has been writing complex algorithms ever since. During his career, Rod has worked on an eclectic assortment of applications in such fields as telephone switching, billing, repair dispatching, tax processing, wastewater treatment, concert ticket sales, cartography, and training for professional football players.

Stephens aptly reminds us of the vitality and centrality of algorithms by observing that 🔧🔨🔩

Studying algorithms lets you build a useful toolkit of methods for solving specific problems. It lets you understand which algorithms are most effective under different circumstances so that you can pick the one best suited for a particular program. 

Last, but certainly not the least, I invite you to note a crucial point that Stephens make in an introductory section entitled Who This Book Is For. This will let you decide whether Essential Algorithms: A Practical Approach to Computer Algorithms is truly the right algorithms book for you.

Should you find yourself fit any part of the description above, all I can say is: Go out and grab this book; you won’t regret it; I certainly didn’t 🙇

5. Algorithms to Live By: The Computer Science of Human Decisions (Henry Holt and Co.) by Brian Christian and Tom Griffiths 🔐

Okay, so the last algorithms book we’ll be looking at today won’t actually teach you the ins and outs of algorithms in any details; in fact, not at all, at least from the implementation perspective. But I include Algorithms to Live By: The Computer Science of Human Decisions (Henry Holt and Co.) by by Brian Christian and Tom Griffiths in this list because it deserves a wide readership among those wishing to truly grok algorithms.

Algorithms to Live By will help you situate algorithms in their applicability to our personal world, and indeed to the business world as well. Dare I say, it will help answer the question that I had posed at the outset: Will algorithms remain our servants, or will they overrun as like an out-of-control juggernaut?

In the same breath—and there I had mentioned in passing the evocatively named article Why Software Is Eating the World by Marc Andreessen—I invite you again to hold on to the thought of finally deciphering the stuff of algorithmic magic. This book will tremendously aid you in grokking the bottomline of this precise area 💰

There is a lot going on in this excellent book, far more than I can do justice to at this juncture. Suffice it to say that I’m becoming increasingly and acutely aware of a startling phrase—at least that’s how the phrase grabbed me on my first encounter with it—that “Real Artists Ship”. There, in his bestseller entitled Linchpin: Are You Indispensable? (p.101), Seth Godin was reminding us of the importance that shipping a product must occupy in our collective consciousness 🚚

So it is that I will now exit, but not before an admittedly flamboyant flourish that harkens back to the 1937 Disney classic, Snow White and the Seven Dwarfs, in which the Evil Queen utters the famous line that I’m here taking the liberty of wildly paraphrasing—with a nod to Godin’s moniker that “Real Artists Ship“—by intoning

Magic mirror, on the wall—which one is the fastest shipping method of them all?

🚂 🚃 🚚 🚢 🚅

In the end—and much as I hinted at, at the outset—I invite your comments. Much more importantly, please, do please consider helping our fellow Texans affected by the fury of Hurricane Harvey. I dedicate this essay, once again, to you, fellow Texans, as we go about rebuilding our homes in the Lone Star State 🇺🇸️ Here’s how you can help those affected by Harvey 🎯

BTW, and I’ll mention this as a friendly reminder—your comments are welcomed, as always—that having read my brief take each on a handful of the finest algorithms books…

• Did you find that your experience of reading these books was perhaps different?
• Were there other qualities, perhaps, that I did not cover, and which happen to be the ones that you found the more helpful—in these or other books—as you mastered algorithms?
• Did I leave out any of your favorite algorithms books?!
• I’ve covered only a tiny fraction of the algorithms books that I’ve read, necessarily limited by the time available—stay tuned for future installments of this essay

I trust that these brief vignettes will help you in some small way along your journey to grokking algorithms 🚣