Bloomberg the Company Bloomberg Anywhere Login WHAT CODE? BUSINESSWEEK JUNE 11, 2015 A message from Josh Tyrangiel 1 The Man in the Taupe Blazer You are an educated, successful person capable of abstract thought. A VP doing an SVP’s job. Your office, appointed with decent furniture and a healthy amount of natural light filtered through vertical blinds, is commensurate with nearly two decades of service to the craft of management. Copper plaques on the wall attest to your various leadership abilities inside and outside the organization: One, the Partner in Innovation Banquet Award 2011, is from the sales team for your support of its 18-month effort to reduce cycle friction—net sales increased 6.5 percent; another, the Civic Guidelight 2008, is for overseeing a volunteer team that repainted a troubled public school top to bottom. You have a reputation throughout the organization as a careful person, bordering on penny-pinching. The way you’d put it is, you are loath to pay for things that can’t be explained. You expect your staff to speak in plain language. This policy has served you well in many facets of operations, but it hasn’t worked at all when it comes to overseeing software development. For your entire working memory, some Internet thing has come along every two years and suddenly hundreds of thousands of dollars (inevitably millions) must be poured into amorphous projects with variable deadlines. Content management projects, customer relationship management integration projects, mobile apps, paperless office things, global enterprise resource planning initiatives—no matter how tightly you clutch the purse strings, software finds a way to pry open your fingers. Here we go again. On the other side of your (well-organized) desk sits this guy in his mid-30s with a computer in his lap. He’s wearing a taupe blazer. He’s come to discuss spending large sums to create intangible abstractions on a “website re-architecture project.” He needs money, support for his team, new hires, external resources. It’s preordained that you’ll give these things to him, because the CEO signed off on the initiative—and yet should it all go pear-shaped, you will be responsible. Coders are insanely expensive, and projects that start with uncomfortably large budgets have an ugly tendency to grow from there. You need to understand where the hours will go. He says: “We’re basically at the limits with WordPress.” Who wears a taupe blazer? The CTO was fired six months ago. That CTO has three kids in college and a mustache. It was a bad exit. The man in the taupe blazer (TMitTB) works for the new CTO. She comes from Adobe and has short hair and no mustache. Here is what you’ve been told: All of the computer code that keeps the website running must be replaced. At one time, it GRAPHER: COREY OLSEN FOR BLOOMBERG BUSINESSWEEK was very valuable and was keeping the company running, but the new CTO thinks it’s garbage. She tells you the old code is spaghetti and your systems are straining as a result. That the thirdparty services you use, and pay for monthly, are old and busted. Your competitor has an animated shopping cart that drives across the top of the screen at checkout. That cart remembers everything customers have ever purchased and generates invoices on demand. Your cart has no memory at all. Salespeople stomp around your office, sighing like theater students, telling you how embarrassed they are by the site. Nothing works right on mobile. Orders are cutting off halfway. People are logged out with no warning. Something must be done. Which is why TMitTB is here. Who’s he, anyway? Webmaster? IT? No, he’s a “Scrum Master.” “My people are split on platform,” he continues. “Some want to use Drupal 7 and make it work with Magento—which is still PHP.” He frowns. “The other option is just doing the back end in Node.js with Backbone in front.” You’ve furrowed your brow; he eyes you sympathetically and explains: “With that option it’s all JavaScript, front and back.” Those are all terms you’ve heard. You’ve read the first parts of the Wikipedia pages and a book on software project estimation. It made some sense at the time. You ask the universal framing question: “Did you cost these options?” He gives you a number and a date. You know in your soul that the number is half of what it should be and that the project will go a year over schedule. He promises long-term efficiencies: The $85,000 in Oracle licenses will no longer be needed; engineering is moving to a free, open-sourced database. “We probably should have done that back when we did the Magento migration,” he says. Meaning, of course, that his predecessor probably should have done that. You consult a spreadsheet and remind him that the Oracle contract was renewed a few months ago. So, no, actually, at least for now, you’ll keep eating that cost. Sigh. This man makes a third less than you, and his education ended with a B.S. from a large, perfectly fine state university. But he has 500+ connections on LinkedIn. That plus sign after the “500” bothers you. How many more than 500 people does he know? Five? Five thousand? In some mysterious way, he outranks you. Not within the company, not in restaurant reservations, not around lawyers. Still: He strokes his short beard; his hands are tanned; he hikes; his socks are embroidered with little ninja. “Don’t forget,” he says, “we’ve got to budget for apps.” This is real. A Scrum Master in ninja socks has come into your office and said, “We’ve got to budget for apps.” Should it all go pear-shaped, his career will be just fine. You keep your work in perspective by thinking about barrels of cash. You once heard that a U.S. dry barrel can hold about $100,000 worth of singles. Next year, you’ll burn a little under a barrel of cash on Oracle. One barrel isn’t that bad. But it’s never one barrel. Is this a 5-barrel project or a 10-barreler? More? Too soon to tell. But you can definitely smell money burning. At this stage in the meeting, you like to look supplicants in the eye and say, OK, you’ve given me a date and a budget. But when will it be done? Really, truly, top-line-revenue-reporting finished? Come to confession; unburden your soul. This time you stop yourself. You don’t want your inquiry to be met by a patronizing sigh of impatience or another explanation about ship dates, Agile cycles, and continuous delivery. Better for now to hide your ignorance. When will it be done? You are learning to accept that the answer for software projects is never. 1.1 Why Are We Here? We are here because the editor of this magazine asked me, “Can you tell me what code is?” “No,” I said. “First of all, I’m not good at the math. I’m a programmer, yes, but I’m an East Coast programmer, not one of these serious platform people from the Bay Area.” I began to program nearly 20 years ago, learning via oraperl, a special version of the Perl language modified to work with the Oracle database. A month into the work, I damaged the accounts of 30,000 fantasy basketball players. They sent some angry e-mails. After that, I decided to get better. Which is to say I’m not a natural. I love computers, but they never made any sense to me. And yet, after two decades of jamming information into my code-resistant brain, I’ve amassed enough knowledge that the computer has revealed itself. Its magic has been stripped away. I can talk to someone who used to work at Amazon.com or Microsoft about his or her work without feeling a burning shame. I’d happily talk to people from Google and Apple, too, but they so rarely reenter the general population. The World Wide Web is what I know best (I’ve coded for money in the programming languages Java, JavaScript, Python, Perl, PHP, Clojure, and XSLT), but the Web is only one small part of the larger world of software development. There are 11 million professional software developers on earth, according to the research firm IDC. (An additional 7 million are hobbyists.) That’s roughly the population of the greater Los Angeles metro area. Imagine all of L.A. programming. East Hollywood would be for Mac programmers, West L.A. for mobile, Beverly Hills for finance programmers, and all of Orange County for Windows. There are lots of other neighborhoods, too: There are people who write code for embedded computers smaller than your thumb. There are people who write the code that runs your TV. There are programmers for everything. They have different cultures, different tribal folklores, that they use to organize their working life. If you told me a systems administrator was taking a juggling class, that would make sense, and I’d expect a product manager to take a trapeze class. I’ve met information architects who list and rank their friendships in spreadsheets. Security research specialists love to party. What I’m saying is, I’m one of 18 million. So that’s what I’m writing: my view of software development, as an individual among millions. Code has been my life, and it has been your life, too. It is time to understand how it all works. Every month it becomes easier to do things that have never been done before, to create new kinds of chaos and find new kinds of order. Even though my math skills will never catch up, I love the work. Every month, code changes the world in some interesting, wonderful, or disturbing way 2 Let’s Begin A computer is a clock with benefits. They all work the same, doing secondgrade math, one step at a time: Tick, take a number and put it in box one. Tick, take another number, put it in box two. Tick, operate (an operation might be addition or subtraction) on those two numbers and put the resulting number in box one. Tick, check if the result is zero, and if it is, go to some other box and follow a new set of instructions. You, using a pen and paper, can do anything a computer can; you just can’t do those things billions of times per second. And those billions of tiny operations add up. They can cause a phone to boop, elevate an elevator, or redirect a missile. That raw speed makes it possible to pull off not one but multiple sleights of hand, card tricks on top of card tricks. Take a bunch of pulses of light reflected from an optical disc, apply some math to unsqueeze them, and copy the resulting pile of expanded impulses into some memory cells—then read from those cells to paint light on the screen. Millions of pulses, 60 times a second. That’s how you make the rubes believe they’re watching a movie. Apple has always made computers; Microsoft used to make only software (and occasional accessory hardware, such as mice and keyboards), but now it’s in the hardware business, with Xbox game consoles, Surface tablets, and Lumia phones. Facebook assembles its own computers for its massive data centers. So many things are computers, or will be. That includes watches, cameras, air conditioners, cash registers, toilets, toys, airplanes, and movie projectors. Samsung makes computers that look like TVs, and Tesla makes computers with wheels and engines. Some things that aren’t yet computers—dental floss, flashlights—will fall eventually. When you “batch” process a thousand images in Photoshop or sum numbers in Excel, you’re programming, at least a little. When you use computers too much—which is to say a typical amount—they start to change you. I’ve had Photoshop dreams, Visio dreams, spreadsheet dreams, and Web browser dreams. The dreamscape becomes fluid and can be sorted and restructured. I’ve had programming dreams where I move text around the screen. You can make computers do wonderful things, but you need to understand their limits. They’re not all-powerful, not conscious in the least. They’re fast, but some parts—the processor, the RAM—are faster than others—like the hard drive or the network connection. Making them seem infinite takes a great deal of work from a lot of programmers and a lot of marketers. The turn-of-last-century British artist William Morris once said you can’t have art without resistance in the materials. The computer and its multifarious peripherals are the materials. The code is the art. 2.1 How Do You Type an “A”? Consider what happens when you strike a key on your keyboard. Say a lowercase “a.” The keyboard is waiting for you to press a key, or release one; it’s constantly scanning to see what keys are pressed down. Hitting the key sends a scancode. Just as the keyboard is waiting for a key to be pressed, the computer is waiting for a signal from the keyboard. When one comes down the pike, the computer interprets it and passes it farther into its own interior. “Here’s what the keyboard just received—do with this what you will.” It’s simple now, right? The computer just goes to some table, figures out that the signal corresponds to the letter “a,” and puts it on screen. Of course not— too easy. Computers are machines. They don’t know what a screen or an “a” are. To put the “a” on the screen, your computer has to pull the image of the “a” out of its memory as part of a font, an “a” made up of lines and circles. It has to take these lines and circles and render them in a little box of pixels in the part of its memory that manages the screen. So far we have at least three representations of one letter: the signal from the keyboard; the version in memory; and the lines-and-circles version sketched on the screen. We haven’t even considered how to store it, or what happens to the letters to the left and the right when you insert an “a” in the middle of a sentence. Or what “lines and circles” mean when reduced to binary data. There are surprisingly many ways to represent a simple “a.” It’s amazing any of it works at all. Coders are people who are willing to work backward to that key press. It takes a certain temperament to page through standards documents, manuals, and documentation and read things like “data fields are transmitted least significant bit first” in the interest of understanding why, when you expected “ü,” you keep getting “�.” 2.2 From Hardware to Software Hardware is a tricky business. For decades the work of integrating, building, and shipping computers was a way to build fortunes. But margins tightened. Look at Dell, now back in private hands, or Gateway, acquired by Acer. Dell and Gateway, two world-beating companies, stayed out of software, typically building PCs that came preinstalled with Microsoft Windows—plus various subscription-based services to increase profits. This led to much cursing from individuals who’d spent $1,000 or more on a computer and now had to figure out how to stop the antivirus software from nagging them to pay up. Years ago, when Microsoft was king, Steve Ballmer, sweating through his blue button-down, jumped up and down in front of a stadium full of people and chanted, “Developers! Developers! Developers! Developers!” He yelled until he was hoarse: “I love this company!” Of course he did. If you can sell the software, if you can light up the screen, you’re selling infinitely reproducible nothings. The margins on Ballmer chants “Dev SOURCE: YOUTUBE nothing are great—until other people start selling even cheaper nothings or giving them away. Which is what happened, as free software- based systems such as Linux began to nibble, then devour, the server market, and free-to-use Web-based applications such as Google Apps began to serve as viable replacements for desktop software. Expectations around software have changed over time. IBM unbundled software from hardware in the 1960s and got to charge more; Microsoft rebundled Internet Explorer with Windows in 1998 and got sued; Apple initially refused anyone else the ability to write software for the iPhone when it came out in 2007, and then opened the App Store, which expanded into a vast commercial territory—and soon the world had Angry Birds. Today, much hardware comes with some software—a PC comes with an operating system, for example, and that OS includes hundreds of subprograms, from mail apps to solitaire. Then you download or buy more. There have been countless attempts to make software easier to write, promising that you could code in plain English, or manipulate a set of icons, or make a list of rules—software development so simple that a bright senior executive or an average child could do it. Decades of efforts have gone into helping civilians write code as they might use a calculator or write an e-mail. Nothing yet has done away with developers, developers, developers, developers. Thus a craft, and a professional class that lives that craft, emerged. Beginning in the 1950s, but catching fire in the 1980s, a proportionally small number of people became adept at inventing ways to satisfy basic human desires (know the time, schedule a flight, send a letter, kill a zombie) by controlling the machine. Coders, starting with concepts such as “signals from a keyboard” and “numbers in memory,” created infinitely reproducible units of digital execution that we call software, hoping to meet the needs of the marketplace. Man, did they. The systems they built are used to manage the global economic infrastructure. ■ 1 If coders don’t run the world, they run the things that run the world. Most programmers aren’t working on building a widely recognized application like Microsoft Word. Software is everywhere. It’s gone from a craft of fragile, built-from-scratch custom projects to an industry of standardized parts, where coders absorb and improve upon the labors of their forebears (even if those forebears are one cubicle over). Software is there when you switch channels and your cable box shows you what else is on. You get money from an ATM—software. An elevator takes you up five stories—the same. Facebook releases software every day to something like a billion people, and that software runs inside Web browsers and mobile applications. Facebook looks like it’s just pictures of your mom’s crocuses or your son’s school play—but no, it’s software. GRAPHER: BORU O’BRIEN O’CONNELL FOR BLOOMBERG BUSINESSWEEK; SET DESIGN: DAVE BRYANT 2.3 How Does Code Become Software? We know that a computer is a clock with benefits, and that software starts as code, but how? We know that someone, somehow, enters a program into the computer and the program is made of code. In the old days, that meant putting holes in punch cards. Then you’d put the cards into a box and give them to an operator who would load them, and the computer would flip through the cards, identify where the holes were, and update parts of its memory, and then it would—OK, that’s a little too far back. Let’s talk about modern typinginto-a-keyboard code. It might look like this: ispal: {x~|x} That’s in a language called, simply, K, famous for its brevity. ■ 2 That code will test if something is a palindrome. If you next typed in ispal "able was i ere i saw elba", K will confirm that yes, this is a palindrome. So how else might your code look? Maybe like so, in Excel (with all the formulas hidden away under the numbers they produce, and a check box that you can check): But Excel spreadsheets are tricky, because they can hide all kinds of things under their numbers. This opacity causes risks. One study by a researcher at the University of Hawaii found that 88 percent of spreadsheets contain errors. Programming can also look like Scratch, a language for kids: That’s definitely programming right there—the computer is waiting for a click, for some input, just as it waits for you to type an “a,” and then it’s doing something repetitive, and it involves hilarious animals. Or maybe: PRINT *, "WHY WON'T IT WORK END That’s in Fortran. The reason it’s not working is that you forgot to put a quotation mark at the end of the first line. Try a little harder, thanks. All of these things are coding of one kind or another, but the last bit is what most programmers would readily identify as code. A sequence of symbols (using typical keyboard characters, saved to a file of some kind) that someone typed in, or copied, or pasted from elsewhere. That doesn’t mean the other kinds of coding aren’t valid or won’t help you achieve your goals. Coding is a broad human activity, like sport, or writing. When software developers think of coding, most of them are thinking about lines of code in files. They’re handed a problem, think about the problem, write code that will solve the problem, and then expect the computer to turn word into deed. Code is inert. How do you make it ert? You run software that transforms it into machine language. The word “language” is a little ambitious here, given that you can make a computing device with wood and marbles. Your goal is to turn your code into an explicit list of instructions that can be carried out by interconnected logic gates, thus turning your code into something that can be executed—software. A compiler is software that takes the symbols you typed into a file and transforms them into lower-level instructions. Imagine a programming language called Business Operating Language United System, or Bolus. It’s a terrible language that will have to suffice for a few awkward paragraphs. It has one real command, PRINT. We want it to print HELLO NERDS on our screen. To that end, we write a line of code in a text file that says: PRINT {HELLO NERDS} And we save that as nerds.bol. Now we run gnubolus nerds.bol, our imaginary compiler program. How does it start? The only way it can: by doing lexical analysis, going character by character, starting with the “p,” grouping characters into tokens, saving them into our one-dimensional tree boxes. Let’s be the computer. Character Meaning Hmmmm...? P Someone say something? R I’m waiting... I [drums fingers] N Any time now... T Ah, "PRINT" Space String coming! { These H letters E don’t L matter L la O la Space just N saving E them R for later Stringtime is over! Time to get to work. D S } End of file The reason I’m showing it to you is so you can see how every character matters. Computers usually “understand” things by going character by character, bit by bit, transforming the code into other kinds of code as they go. The Bolus compiler now organizes the tokens into a little tree. Kind of like a sentence diagram. Except instead of nouns, verbs, and adjectives, the computer is looking for functions and arguments. Our program above, inside the computer, becomes this: "HE LLO RD NE S" fun ctio n n am ar gu m e en t s " PR I NT " Trees are a really pleasant way of thinking of the world. Your memo at work has sections that have paragraphs? Tree. Your e-mail program contains messages that contain subject lines and addresses? Tree. Your favorite software program that has a menu bar with individual items that have subitems? Tree. Every day is Arbor Day in Codeville. Of course, it’s all a trick. If you cut open a computer, you’ll find countless little boxes in rows, places where you can put and retrieve bytes. Everything ultimately has to get down to things in little boxes pointing to each other. That’s just how things work. So that tree is actually more like this: fun ctio n n am e "PRINT " argu m ent s "HELLO NERDS" Every character truly, truly matters. Every single stupid misplaced semicolon, space where you meant tab, bracket instead of a parenthesis— mistakes can leave the computer in a state of panic. The trees don’t know where to put their leaves. Their roots decay. The boxes don’t stack neatly. For not only are computers as dumb as a billion marbles, they’re also positively Stradivarian in their delicacy. That process of going character by character can be wrapped up into a routine—also called a function, a method, a subroutine, or component. (Little in computing has a single, reliable name, which means everyone is always arguing over semantics.) And that routine can be run as often as you need. Second, you can print anything you wish, not just one phrase. Third, you can repeat the process forever, and nothing will stop you until the machine breaks or, barring that, heat death of the universe. Obviously no one besides Jack Nicholson in The Shining really needs to keep typing the same phrase over and over, and even then it turned out to be a bad idea. Instead of worrying about where the words are stored in memory and having to go character by character, programming languages let you think of things like strings, arrays, and trees. That’s what programming gives you. You may look over a programmer’s shoulder and think the code looks complex and boring, but it’s covering up repetitive boredom that’s unimaginably vast. ■ 3 This thing we just did with individual characters, compiling a program down into a fake assembly language so that the nonexistent computer can print each character one at a time? The same principle applies to every pixel on your screen, every frequency encoded in your MP3 files, and every imaginary cube in Minecraft. Computing treats human language as an arbitrary set of symbols in sequences. It treats music, imagery, and film that way, too. It’s a good and healthy exercise to ponder what your computer is doing right now. Maybe you’re reading this on a laptop: What are the steps and layers between what you’re doing and the Lilliputian mechanisms within? When you double-click an icon to open a program such as a word processor, the computer must know where that program is on the disk. It has some sort of accounting process to do that. And then it loads that program into its memory—which means that it loads an enormous to-do list into its memory and starts to step through it. What does that list look like? Maybe you’re reading this in print. No shame in that. In fact, thank you. The paper is the artifact of digital processes. Remember how we put that “a” on screen? See if you can get from some sleepy writer typing that letter on a keyboard in Brooklyn, N.Y., to the paper under your thumb. What framed that fearful symmetry? Thinking this way will teach you two things about computers: One, there’s no magic, no matter how much it looks like there is. There’s just work to make things look like magic. And two, it’s crazy in there. GRAPHER: ASGER CARLSEN FOR BLOOMBERG BUSINESSWEEK; SET DESIGN: DAVE BRYANT 2.4 What Is an Algorithm? “Algorithm” is a word writers invoke to sound smart about technology. Journalists tend to talk about “Facebook’s algorithm” or a “Google algorithm,” which is usually inaccurate. They mean “software.” Algorithms don’t require computers any more than geometry does. An algorithm solves a problem, and a great algorithm gets a name. Dijkstra’s algorithm, after the famed computer scientist Edsger Dijkstra, finds the shortest path in a graph. By the way, “graph” here doesn’t mean but rather . Think of a map; streets connect to streets at intersections. It’s a graph! There are graphs all around you. Plumbing, electricity, code compilation, social networks, the Internet, all can be represented as graphs! (Now to monetize …) Many algorithms have their own pages on Wikipedia. You can spend days poking around them in wonder. Euclid’s algorithm, for example, is the go-to specimen that shows up whenever anyone wants to wax on about algorithms, so why buck the trend? It’s a simple way of determining the greatest common divisor for two numbers. Take two numbers, like 16 and 12. Divide the first by the second. If there’s a remainder (in this case there is, 4), divide the smaller number, 12, by that remainder, 4, which gives you 3 and no remainder, so we’re done—and 4 is the greatest common divisor. ∆ (Now translate that into machine code, and we can get out of here.) There’s a site called Rosetta Code that shows you different algorithms in different languages. The Euclid’s algorithm page is great. Some of the examples are suspiciously long and laborious, and some are tiny nonsense poetry, like this one, in the language Forth: ■ 4 : gcd ( a b -- n ) begin dup while tuck mod repeat drop ; Read it out loud, preferably to friends. Forth is based on the concept of a stack, which is a special data structure. You make “words” that do things on the stack, building up a little language of your own. PostScript, ■ 5 the language of laser printers, came after Forth but is much like it. Look at how similar the code is, give or take some squiggles: /gcd { { {0 gt} {dup rup mod} {pop exit} ifte } loop }. And that’s Euclid’s algorithm in PostScript. ✱ I admit, this might be fun only for me. Here it is in Python (all credit to Rosetta Code): def gcd(u, v): return gcd(v, u % v) if v else abs(u) A programming language is a system for encoding, naming, and organizing algorithms for reuse and application. It’s an algorithm management system. This is why, despite the hype, it’s silly to say Facebook has an algorithm. An algorithm can be translated into a function, and that function can be called (run) when software is executed. There are algorithms that relate to image processing and for storing data efficiently and for rapidly running through the elements of a list. Most algorithms come for free, already built into a programming language, or are available, organized into libraries, for download from the Internet in a moment. You can do a ton of programming without actually thinking about algorithms—you can save something into a database or print a Web page by cutting and pasting code. But if you want the computer to, say, identify whether it’s reading Spanish or Italian, you’ll need to write a language-matching function. So in that sense, algorithms can be pure, mathematical entities as well as practical expressions of ideas on which you can place your grubby hands. One thing that took me forever to understand is that computers aren’t actually “good at math.” They can be programmed to execute certain operations to certain degrees of precision, so much so that it looks like “doing math” to humans. ■ 6 Dijkstra said: “Computer science is no more about computers than astronomy is about telescopes.” ■7 A huge part of computer science is about understanding the efficiency of algorithms— how long they will take to run. Computers are fast, but they can get bogged down—for example, when trying to find the shortest path between two points on a large map. Companies such as Google, Facebook, and Twitter are built on top of fundamental computer science ■ 8 and pay great attention to efficiency, because their users do a distributed rkable and nging set of t 1318 s to the computer e community, g in the things (searches, status updates, tweets) an extraordinary number of times. Thus it’s absolutely worth their time to find excellent computer scientists, many with doctorates, who know where all the efficiencies are buried. It takes a good mathematician to be a computer scientist, but a middling one to be an effective programmer. Until you start dealing with millions uing up until of people on a network or you need to blur or sharpen a million photos ath in 2002, quickly, you can just use the work of other people. When it gets real, as “EWDs,” of them break out the comp sci. When you’re doing anything a hundred trillion written written. ∆ times, nanosecond delays add up. Systems slow down, users get cranky, money burns by the barrel. ■ 9 The hardest work in programming is getting around things that aren’t computable, in finding ways to break impossible tasks into small, possible components, and then creating the impression that the computer is doing something it actually isn’t, like having a human conversation. This used to be known as “artificial intelligence research,” but now it’s more likely to go under the name “machine learning” or “data mining.” When you speak to Siri or Cortana and they respond, it’s not because these services understand you; they convert your words into text, break that text into symbols, then match those symbols against the symbols in their database of terms, and produce an answer. Tons of algorithms, bundled up and applied, mean that computers can fake listening. A programming language has at least two jobs, then. It needs to wrap up lots of algorithms so they can be reused. Then you don’t need to go looking for a square-root algorithm (or a genius programmer) every time you need a square root. And it has to make it easy for programmers to wrap up new algorithms and routines into functions for reuse. The DRY principle, for Don’t Repeat Yourself, is one of the colloquial tenets of programming. That is, you should name things once, do things once, create a function once, and let the computer repeat itself. This doesn’t always work. Programmers repeat themselves constantly. I’ve written certain kinds of code a hundred times. This is why DRY is a principle. Enough talk. Let’s code! 2.5 The Sprint After a few months the budget is freed up, and the Web re-architecture project is under way. They give it a name: Project Excelsior. Fine. TMitTB (who, to be fair, has other clothes and often dresses like he’s in Weezer) checks in with you every week. He brings documents. Every document has its own name. The functional specification is a set of at least a thousand statements about users clicking buttons. “Upon accessing the Web page the user if logged in will be identified by name and welcomed and if not logged in will be encouraged to log in or create an account. (See user registration workflow.)” God have mercy on our souls. From there it lists various error messages. It’s a sort of blueprint in that it describes—in words, with occasional diagrams—a program that doesn’t exist. Some parts of the functional specification refer to “user stories,” tiny hypothetical narratives about people using the site, e.g., “As a visitor to the website, I want to search for products so I can quickly purchase what I want.” ■ 10 Then there’s something TMitTB calls wireframe mock-ups, which are pictures of how the website will look, created in a program that makes everything seem as if it were sketched by hand, all a little squiggly—even though it was produced on a computer. This is so no one gets the wrong idea about these ideas-in-progress and takes them too seriously. Patronizing, but point taken. You rarely see TMitTB in person, because he’s often at conferences where he presents on panels. He then tweets about the panels and notes them on his well-populated LinkedIn page. Often he takes a picture of the audience from the stage, and what you see is an assembly of mostly men, many with beards, the majority of whom seem to be peering into their laptop instead of up at the stage. Nonetheless the tweet that accompanies that photo says something like, “AMAZING audience! @ the panel on #microservice architecture at #ArchiCon2015.” He often tells you just how important this panel-speaking is for purposes of recruiting. Who’s to say he is wrong? It costs as much to hire a senior programmer as it does to hire a midlevel executive, so maybe going to conferences is his job, and in the two months he’s been here he’s hired four people. His two most recent hires have been in Boston and Hungary, neither of which is a place where you have an office. But what does it matter? Every day he does a 15-minute “standup” meeting via something called Slack, which is essentially like Google Chat but with some sort of plaid visual theme, and the programmers seem to agree that this is a wonderful and fruitful way to work. “I watch the commits,” TMitTB says. Meaning that every day he reviews the code that his team writes to make sure that it’s well-organized. “No one is pushing to production without the tests passing. We’re good.” Your meetings, by comparison, go for hours, with people arranged around a table—sitting down. You wonder how he gets his programmers to stand up, but then some of them already use standing desks. Perhaps that’s the ticket. Honestly, you would like to go to conferences sometimes and be on panels. You could drink bottled water and hold forth just fine. 2.6 What’s With All These Conferences, Anyway? Conferences! The website Lanyrd lists hundreds of technology conferences for June 2015. There’s an event for software testers in Chicago, a Twitter conference in São Paulo, and one on enterprise content management in Amsterdam. In New York alone there’s the Big Apple Scrum Day, the Razorfish Tech Summit, an entrepreneurship boot camp for veterans, a conference dedicated to digital mapping, many conferences for digital marketers, one dedicated to Node.js, one for Ruby, and one for Scala (these are programming languages), a couple of breakfasts, a conference for cascading style sheets, one for text analytics, and something called the Employee Engagement Awards. Tech conferences look like you’d expect. Tons of people at a Sheraton, keynote in Ballroom D. Or enormous streams of people wandering through South by Southwest in Austin. People come together in the dozens or thousands and attend panels, ostensibly to learn; they attend presentations and brush up their skills, but there’s a secondary conference function, one of acculturation. You go to a technology conference to affirm your tribal identity, to transfer out of the throng of dilettantes and into the zone of the professional. You pick up swag and talk to vendors, if that’s your thing. row: TechCrunch Disrupt NYC, May 2011; Google I/O developers conference, San Francisco, May​2013; Global Mobile et Conference, Beijing, April 2015 nd row: Nvidia GPU, San Jose, September​2010; South by Southwest (SXSW) Interactive Festival, Austin, March 2013; A wide Developers Conference (WWDC), San Francisco, June 2008 row: TechCrunch Disrupt NYC, May 2012; Re:publica conference, Berlin, May 2015; TechCrunch Disrupt NYC, May 2015 h row: SXSW Interactive Festival, Austin, March​2014; WWDC, San Francisco, June​2015; Bloomberg Technology Confer rancisco, June 15-16 Technology conferences are where primate dynamics can be fully displayed, where relationships of power and hierarchy can be established. There are keynote speakers—often the people who created the technology at hand or crafted a given language. There are the regular speakers, often paid not at all or in airfare, who present some idea or technique or approach. Then there are the panels, where a group of people are lined up in a row and forced into some semblance of interaction while the audience checks its e-mail. I’m a little down on panels. They tend to drift. I’m not sure why they exist. Here’s the other thing about technology conferences: There has been much sexual harassment and much sexist content in conferences. Which is stupid, because computers are dumb rocks lacking genitalia, but there you have it. Women in software, having had enough, started to write it up, post to blogs. Other women did the same. The problem is pervasive: There are a lot of conferences, and there have been many reports of harassing behavior. The language Ruby, the preferred language for startup bros, developed the worst reputation. At a Ruby conference in 2009, someone gave a talk subtitled “Perform Like a Pr0n Star,” with sexy slides. That was dispiriting. There have been criminal incidents, too. Conferences began to develop codes of conduct, rules and algorithms for people (men, really) to follow. If you are subject to or witness unacceptable behavior, or have any other concerns, please notify a community organizer as soon as possible … — Burlington Ruby Conference php[architect] is dedicated to providing a harassment-free event experience for everyone and will not tolerate harassment or offensive behavior in any form. — php[architect] The Atlanta Java Users Group (AJUG) is dedicated to providing an outstanding conference experience for all attendees, speakers, sponsors, volunteers, and organizers involved in DevNexus (GeekyNerds) regardless of gender, sexual orientation, disability, physical appearance, body size, race, religion, financial status, hair color (or hair amount), platform preference, or text editor of choice. — devnexus When people started talking about conference behavior, they also began to talk about the larger problems of programming culture. This was always an issue, but the conference issues gave people a point of common reference. Why were there so many men in this field? Why do they behave so strangely? Why is it so hard for them to be in groups with female programmers and behave in a typical, adult way? “I go to work and I stick out like a sore thumb. I have been mistaken for an administrative assistant more than once. I have been asked if I was physical security (despite security wearing very distinctive uniforms),” wrote Erica Joy Baker on Medium.com who has worked, among other places, at Google. ∆ “Always the only woman in the meeting, often the first—the first female R&D engineer, first female project lead, first female software team lead —in the companies I worked for,” wrote another woman in Fast Company magazine. ✱ Famous women coding history Fewer than a fifth of undergraduate degrees in computer science awarded in 2012 went to women, according to the National Center for Women & Information Technology. Less than 30 percent of the people in computing are women. And the number of women in computing has fallen since the 1980s, even as the market for their skills has expanded. The pipeline is a huge problem. And yet it’s not unsolvable. I’ve met managers who have built perfectly functional large teams that are more than half female coders. Places such as the handicrafts e-commerce site Etsy have made a particular effort to develop educational programs and mentorship programs. Organizations such as the not-for-profit Girl Develop It teach women, and just women, how to create software. Ada Lovelace first programm She devised algorithms fo Charles Babb “analytical en which he neve built. It’s all happening very late in the boom, though. In 2014 some companies began to release diversity reports for their programming teams. It wasn’t a popular practice, but it was revealing. Intel is 23 percent female; Yahoo! is 37 percent. Apple, Facebook, Google, Twitter, and Microsoft are all around 30 percent. These numbers are for the whole companies, not only programmers. That’s a lot of women who Grace Murray Hopper: Worl II hero and inv of the compile didn’t get stock options. The numbers of people who aren’t white or Asian are worse yet. Apple just gave $50 million to fund diversity initiatives, equivalent to 0.007 percent of its market cap. Intel has a $300 million diversity project. The average programmer is moderately diligent, capable of basic mathematics, has a working knowledge of one or more programming languages, and can communicate what he or she is doing to management and his or her peers. Given that a significant number of women work as journalists and editors, perform surgery, run companies, manage small businesses, and use spreadsheets, that a few even serve on the Supreme Court, and that we are no longer surprised to find women working as accountants, professors, statisticians, or project managers, it’s hard to imagine that they can’t write JavaScript. Programming, despite the hype and the self-serving fantasies of programmers the world over, isn’t the most intellectually demanding task imaginable. Which leads one to the inescapable conclusion: The problem with women in technology isn’t the women. demographics taken from Stack Overflow's 2015 developer survey: 3 Why Are Programmers So Intense About Languages? Many conferences are organized around specific programming languages or specific communities (PyCon for Python programmers; the Strata conference for big data; Oscon for open-source coders); these are ritual events for the people in those communities. Attendees gather, talk, and post the videos on YouTube. Language matters. Programmers track the success of computer languages the way other people track sports rankings, commenting on Web forums such as Reddit (where many languages get their own “subreddit,” and reddit.com/r/programming currently has 620,202 readers), or Hacker News, run by the venture capital firm Y Combinator (a company named after a special kind of function that operates on other functions), or Lambda the Ultimate (named after a series of papers written mostly in the 1970s about the influential programming language Scheme—the more inside-baseball the name, the nerdier the subject matter). There are hundreds of programming blogs. Many large corporations let their engineers blog (a generous gift, given how many recruiters are hovering). Discussions about programming go on everywhere, in public, at all times, about hundreds of languages. There is a keen sense of what’s coming up and what’s fading out. It’s not simply fashion; one’s career as a programmer depends on demonstrating capacity in one or more languages. So there are rankings, frequently updated, rarely shocking. As of April 15, the world’s most-used computer languages, according to the Tiobe index (which uses a variety of indicators to generate a single ranking for the world of programming), are Java, C, C++, Objective-C, and C#, followed by JavaScript, PHP, and Python. The rankings are necessarily inexact; another list, by a consulting firm called RedMonk, gives JavaScript the top spot, followed by Java. There are many possible conclusions here, but the obvious one is that, all things being equal, a very good Java programmer who performs well in interviews will have more career options than a similar candidate using a more obscure language. If you code, by the time a language breaks through to the top 10 or 20, you’ve heard of it, read blog posts about it, heard people lament how terrible or wonderful or misguided it is, possibly watched a few video tutorials, or played with it a little. Taking new languages out for a spin is a good thing for a programmer to do. Often all you have to do is download some files and write a couple lines of code, then decide if you want to go further. Most languages are free to download and use. Why do people construct and then give away free languages? Well, the creation of a good computer language is the work of an apex programmer. To have produced a successful language is acknowledged as a monumental effort, akin to publishing a multivolume history of a war, or fighting in one. The reward is glory. Changing a language is like fighting that war all over again, and some languages have at times been trapped in a liminal state between their old, busted selves, and their new, promised version. Perl 5, released in the mid1990s, was a language uniquely suited to the World Wide Web, and it grew as the Web grew; Perl 6 was supposed to be better in every way, and a redesign began with grand pronouncements in 2000. But after 15 years of people working continually and often for free on a project they consider in the public interest, there’s still no official Perl 6. (Latest ETA: Christmas 2015.) The Python language community, keenly aware of the Perl community’s problems, decided to make necessary but difficult changes to the language as part of the transition from Version 2 to Version 3. They would modernize, clean up rough edges—but avoid grand reinventions. Development of Python 3.0 started in 2006; the first working version came out in 2008; and in 2015, the transition is ongoing. Making a new language is hard. Making a popular language is much harder still and requires the smile of fortune. And changing the way a popular language works appears to be one of the most difficult things humans can do, requiring years of coordination to make the standards align. Languages are large, complex, dynamic expressions of human culture. 3.1 The Beauty of the Standard Library The true measure of a language isn’t how it uses semicolons; it’s the standard library of each language. A language is software for making software. The standard library is a set of premade software that you can reuse and reapply. Take Python, which is “batteries included,” meaning that it comes with tons of preexisting code, organized into “modules,” that you can reuse. Its standard library has functions that let you copy Web pages or replace words in a document. What does that mean, to process text? Well, you might have a string of text (The Quick Brown Fox) and save it in a variable called my_string. So now you can call standard methods on that string. You can say my_string.lower(), and it will make all the words lowercase, producing “the quick brown fox.” Truly understanding a language’s standard library is one of the ways one becomes proficient in that language. Typically you just visit Web pages or read a book. But the standard library is only the beginning. For many languages—and Python is exemplary—there’s an enormous library of prewritten modules available for nearly instantaneous download, using “package manager” software. A module (or library, or package) is code that is intended to extend a language’s capabilities. Let’s say you work for an advertising agency and need to process through 100,000 pictures and scale and sharpen them. You type one command: sudo pip install Pillow, and the Pillow module is downloaded, compiled automatically, and placed into the correct directory for later reuse. You have to know, of course, that most modern languages have modules for image processing; you also need to know that Pillow is the most commonly used image-processing toolkit. Knowing how to find that out is part of the job of coding. You might learn it by Googling. You might ask a friend. You might get that information out of a book, or a website like The Hitchhiker’s Guide to Python. A coder needs to be able to quickly examine and identify which giant, complex library is the one that’s the most recently and actively updated and the best match for his or her current needs. A coder needs to be a good listener. But what a payoff! Now that Pillow is installed, you have, at your typing fingertips, dozens of routines and functions related to image processing that you can use in your code: change colors, rotate by a number of degrees, scale, convert GIF images to JPEGs, and so forth. Or if you need to do very complex numerical analysis and statistics work, you can download NumPy, and suddenly an enormous range of mathematical algorithms are available to you, hundreds of years of science and research boiled down. Audio processing, interacting with peculiar hardware, speaking to databases— there are packages for all of these things. But you need to know how to find them, what they are called. Code isn’t just obscure commands in a file. It requires you to have a map in your head, to know where the good libraries, the best documentation, and the most helpful message boards are located. If you don’t know where those things are, you will spend all of your time searching, instead of building cool new things. 3.2 What Do Different Languages Do? GRAPHER: STEVEN BRAHMS FOR BLOOMBERG BUSINESSWEEK; PROP STYLIST: ZACHARY KINSELLA If all computer languages do the same thing (make the computer do what you want), then why does it matter which one you choose? For the same reason that you wouldn’t take a bicycle to pick up a fridge or get a physical from an oncological neurosurgeon. Some tools are better for certain jobs. It’s possible for a C programmer and a Java programmer to read each other’s code, but it’s harder to make C code and Java code work together. C and Java represent the world in different ways, structure data in different ways, and address the components of the computer in different ways. There are true benefits to everyone on a team using the same language. They’re all thinking the same way about how to instruct the computer to process data. It’s not necessary for every team across a big organization to use the same language. In fact, it’s often counterproductive. Large organizations have lots of needs and use many languages and services to meet them. For example, Etsy is built atop PHP—but its product-search service uses Java libraries, because the solutions for search available in Java are great. Some programming languages, such as C, will do their best to do exactly as you ask, even if that means crashing your computer. Others, like OCaml and Haskell, are very constrained and ask a programmer to hew to a narrow form, trying to steer you away from anything stupid. ■ 11 Some languages have cute logos, like the Go gopher. There’s Scratch, a teaching language for kids. It doesn’t use text much at all but allows li’l coders to move icons around on screen and assemble programs like Legos. Its logo is a smiling cat on two legs. And then there’s Lisp, which didn’t come with a logo when it was first proposed in the 1950s but now has a community-created five-eyed alien holding a flag with its proboscis. Lisp is a classic language. There are some languages that just have authority, elegance—canonical computer languages. And one of these is C. Most of the popular languages look a lot like it. C’s de facto logo is, well, the letter C. C is called C because it came after another language. That language was called B. 3.3 The Importance of C C is as big a deal as you can get in computing. Created by Dennis Ritchie starting in the late 1960s at Bell Labs, it’s the principal development language of the UNIX operating system. Unix (lowercased now, to refer to the idea of Unix instead of the branded version) is a simple operating system— basically it’s a kernel ■ 12 that manages memory and runs software, a large collection of very small utility programs, and a “shell” that helps you knit programs into “shell scripts.” If you couldn’t do what you needed with shell scripts, you might write a new utility in C and add it to the utility library. This was a nice and practical way of working, and it coincided with the rise of various kinds of networks that today we refer to collectively as the Internet. So Unix spread from Bell Labs to academia, to large industrial systems, and eventually leached into the water supply of computing until it was everywhere. And everywhere that Unix went, C was sure to go. C is a simple language, simple like a shotgun that can blow off your foot. It allows you to manage every last part of a computer—the memory, files, a hard drive—which is great if you’re meticulous and dangerous if you’re sloppy. Software made in C is known for being fast. When you compile C, it doesn’t simply become a bunch of machine language in one go; there are many steps to making it really, ridiculously fast. These are called optimizations, and they are to programming what loopholes are to taxes. Think of C as sort of a plainspoken grandfather who grew up trapping beavers and served in several wars but can still do 50 pullups. C’s legendary, lucid manual and specification, The C Programming Language, written by Ritchie and Brian Kernighan (known by its nickname, K&R), is a quick and simple read— physically light in comparison with modern, heavy-stock guides to programming on bookstore shelves. This recommended text was published in 1978, when personal computing barely existed, back when a computer was a GRAPHER: JEREMY LIEBMAN FOR BLOOMBERG BUSINESSWEEK large piece of industrial equipment used to control a refrigeration system or calculate actuarial tables. It was in K&R that “Hello, world!” became the canonical example program for any language. By convention, almost every introduction to any programming language since then starts with a variation on “Hello, world!” Here is the ur-text of computational self-introduction: #include int main() { printf("Hello, world!\n"); } Which will, when compiled and run, print “Hello, world!” to the screen. Let’s write a program where you give it a number x and it prints out all the squares of the numbers from 1 to x—just the sort of practical, useful program that always appears in programming tutorials to address the needs of people who urgently require a list of squares. #include void squares(int v) { for (int i=1;i
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