First Recorded Usage of "Hacker"

Here’s the first known recorded usage of the word “hacker” in the tech sense, published in 1963 in MIT’s The Tech newspaper:

First recorded usage of hacker

It was tracked down by Fred Shapiro, editor of The Yale Dictionary Of Quotations and author of a paper with a most hilarious and offensive name. The MIT article dispels the common notion that “hacker” was a purely white-hat term later corrupted by the media. The black-hat connotation was there early on; Richard Stallman was 10 years old when this was printed.

Most of what the article describes is now known as phone phreaking, though some sounds like war dialing. It is fascinating this was taking place in 63, over four decades ago! The international phreaking scene was still strong through the late 90s, abusing home country direct lines with software like BlueBEEP (“when freedom is outlawed, only outlaws will be free”), plus cell phone cloning and whatnot. That’s nearly 40 years of phreaking, though phone companies have since managed to stop widespread fraud.

A hacker Hacking

This of course doesn’t “prove” that the black-hat meaning is the “true” meaning of hacker, just as “one who is employed doing mathematical calculations” is not the “true” meaning of computer. Language is fluid. The New Hacker’s Dictionary has this to say in the word’s definition:

  1. A person who enjoys exploring the details of programmable systems and how to stretch their capabilities, as opposed to most users, who prefer to learn only the minimum necessary.
  2. One who programs enthusiastically (even obsessively) or who enjoys programming rather than just theorizing about programming. (…)
  3. [deprecated] A malicious meddler who tries to discover sensitive information by poking around. Hence “password hacker”, “network hacker”. The correct term for this sense is cracker.
The white-hat definitions are popular among geeks, but I’m not so sure about the deprecation. For one thing, cracker has a precise and also popular meaning: one who removes copyright protection from software. Meanwhile, blackhats aren’t exactly rolling over to surrender their language either. From the latest Phrack issue:

So no, I wasn’t that kid that used to hang out at Radio Shack pulling apart electronic equipment and reassembling it to “see how it works.” (…) that doesn’t make you a “hacker” – it makes you a wannabe EE undergrad. (…) Hacking boxes makes you a “hacker” ! That’s right! Write your local representatives at Wikipedia / urbandictionary / OED and let them know that hackers are people that gain unauthorized access/privileges to computerized systems!
The whole thing would offend most people, so no link. It’s readily googable but be careful about browser exploits, you never know. As a neutral party, Wikipedia has sensible guidelines when it comes to controversial names:

A city, country, people or person, by contrast, is a self-identifying entity: it has a preferred name for itself. The city formerly called Danzig now calls itself Gdansk; the man formerly known as Cassius Clay now calls himself Muhammad Ali. These names are not simply arbitrary terms but are key statements of an entity’s own identity. This should always be borne in mind when dealing with controversies involving self-identifying names. (…)

A number of objective criteria can be used to determine common or self-identifying usage: Is the name in common usage in English? (…) Is it the name used by the subject to describe itself or themselves?

These criteria apply squarely to both types of “hackers.” Common usage? Check. Used to describe themselves? Definitely. The word is now hopelessly ambiguous, as it seems to have been from the start, puzzling outsiders. But it’s always clear to hackers.

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Richard Feynman’s Modest Science

When I was 18 and newly arrived in the US, I used to wonder around enjoying new features like the rule of law and great libraries everywhere. Once while bumming out in North Denver I went into the Regis University library determined to read about physics. I had tried that once before, back in my high school, with poor results. As a teenager I had been obsessed with “understanding” physics and chemistry, especially atomic and quantum theory. I didn’t know enough math to study the subjects deeply, but I wanted a conceptual grasp, however incomplete, that was at least half-way consistent and clear.

My high school books and classes left me with the strong feeling that I simply did not get physics. Try as I might, I could not accept the bizarre results of quantum mechanics, wave-particle duality, or how Heisenberg’s uncertainty principle could even be science. I was baffled. When I brought it up with teachers, they had ready-made analogies to “teach” what happened in this sub-atomic world. “Think of the solar system,” “think of springs connected to each other,” “well, it’s like this, suppose you have…” These analogies didn’t help at all. “You think too concretely, that’s why you can’t visualize it,” told me a teacher.

So I’d sit there and try things, think nonverbally, think in wild shapes, somehow think differently to see if I could imagine a sub-atomic particle and “get it.” No go. I wondered whether programming had perhaps damaged my mind by making it inflexible. I went to the school library and found a more advanced physics book, a bit tattered but no matter. I quit reading when I realized the book still assumed the existence of the ether. “Screw this,” I thought. So I flipped off the science bit, kept to my computers, and carried on.

Feynman Lectures on Physics

But here I was in the USA, land of opportunity and well-stocked libraries. Looking in the physics section I saw “The Feynman Lectures on Physics” sitting there, three volumes. I had a vague idea of who Feynman was, so I picked up the books and went straight to Volume 3, Chapter 1, Quantum Behavior. In the very first page he comes right out and says:

Things on a very small scale behave like nothing that you have any direct experience about. They do not behave like waves, they do not behave like particles, they do not behave like clouds, or billiard balls, or weights on springs, or like anything that you have ever seen. (…)

Because atomic behavior is so unlike ordinary experience, it is very difficult to get used to, and it appears peculiar and mysterious to everyone—both to the novice and the experienced physicist. Even the experts do not understand it the way they would like to, and it is perfectly reasonable that they should not, because all of direct human experience and human intuition applies to large objects. We know how large objects will act, but things on a small scale just do not act that way.

I felt a rush of enthusiasm reading this. It was so humble and visceral and honest. This was science in a way I had never seen before, simultaneously more rigorous and human. That first page alone drove a sledgehammer to my worldview and started rebuilding it. Perhaps childishly, I thought of the Hacker’s Manifesto: “we’ve been spoon-fed baby food at school when we hungered for steak.” I had just found one hell of a juicy stake. At one point Feynman asks students to imagine the various electromagnetic fields and waves in the classroom: coming from the earth’s interior, carrying radio and TV signals, traveling from warm foreheads to the blackboard, and so on. Then he says:

I have asked you to imagine these electric and magnetic fields. What do you do? Do you know how? How do I imagine the electric and magnetic field? What do I actually see? What are the demands of the scientific imagination? Is it any different from trying to imagine that the room is full of invisible angels? No, it is not like imagining invisible angels. It requires a much higher degree of imagination (…). Why? Because invisible angels are understandable. (…) So you say, “Professor, please give me an approximate description of the electromagnetic waves, even though it may be slightly innacurate, so that I too can see them as well as I can see almost-invisible angels. Then I will modify the picture to the necessary abstraction.”

I’m sorry I can’t do that for you. I don’t know how. I have no picture of this electromagnetic field that is in any sense accurate. (…) So if you have some difficulty in making such a picture, you should not be worried that your difficulty is unusual.

Volume 2, pages 20-9 and 20-10

Surely you’re joking – you don’t know?? I could hardly believe what I was reading. I had been hoping for a better explanation – a masterful analogy of weights on springs that would allow me to really understand physics. Instead, here was a Nobel laureate telling me that he didn’t really understand it either – not in the definite, make-believe fashion of high school science. Feynman lifted the veil for me – all my sanitized textbooks and uninspired teachers presented science with finality and devoid of context, as if the gods had handed down a few scientific models to us. Analogies that were meant to “help understand” reality had in fact supplanted it; it was not simplification, but a gross distortion of what science really is. This fake teaching would never say that atomic behavior is “peculiar and mysterious” because “human intuition applies to large objects.” No, its entire aim was to pretend that science is not mysterious.

Feynman embraces the whole of science: its beauty, its methods, the history and relationships of its ideas, how our minds react to it, and above all how it stands before the ultimate judge, nature. He’s at once fiercely empirical yet mindful of the crucial human context surrounding scientific ideas. The lectures are not only great technical writing but also a deep look into how we think about the world, into reason and the nature of knowledge. Of course, much of the work is to be done with paper, pencil, and math. Back then I didn’t even know calculus, so I couldn’t really follow all the equations. But the books still gave me what I was looking for, and then some.

Now I have an undergrad in math, which puts me roughly in the 18th century, but better equipped to learn on my own. Some day I hope to take time off and hit physics again. If you want to read more of his stuff, Feynman wrote an insightful essay on engineering and there’s the classic Cargo Cult Science, both online. Amazon has the lectures along with other books, and so might your local library. :)

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CPU Rings, Privilege, and Protection

You probably know intuitively that applications have limited powers in Intel x86 computers and that only operating system code can perform certain tasks, but do you know how this really works? This post takes a look at x86 privilege levels, the mechanism whereby the OS and CPU conspire to restrict what user-mode programs can do. There are four privilege levels, numbered 0 (most privileged) to 3 (least privileged), and three main resources being protected: memory, I/O ports, and the ability to execute certain machine instructions. At any given time, an x86 CPU is running in a specific privilege level, which determines what code can and cannot do. These privilege levels are often described as protection rings, with the innermost ring corresponding to highest privilege. Most modern x86 kernels use only two privilege levels, 0 and 3:

x86 Protectiong Rings
x86 Protection Rings

About 15 machine instructions, out of dozens, are restricted by the CPU to ring zero. Many others have limitations on their operands. These instructions can subvert the protection mechanism or otherwise foment chaos if allowed in user mode, so they are reserved to the kernel. An attempt to run them outside of ring zero causes a general-protection exception, like when a program uses invalid memory addresses. Likewise, access to memory and I/O ports is restricted based on privilege level. But before we look at protection mechanisms, let’s see exactly how the CPU keeps track of the current privilege level, which involves the segment selectors from the previous post. Here they are:

x86 Segment Selectors
Segment Selectors – Data and Code

The full contents of data segment selectors are loaded directly by code into various segment registers such as ss (stack segment register) and ds (data segment register). This includes the contents of the Requested Privilege Level (RPL) field, whose meaning we tackle in a bit. The code segment register (cs) is, however, magical. First, its contents cannot be set directly by load instructions such as mov, but rather only by instructions that alter the flow of program execution, like call. Second, and importantly for us, instead of an RPL field that can be set by code, cs has a Current Privilege Level (CPL) field maintained by the CPU itself. This 2-bit CPL field in the code segment register is always equal to the CPU’s current privilege level. The Intel docs wobble a little on this fact, and sometimes online documents confuse the issue, but that’s the hard and fast rule. At any time, no matter what’s going on in the CPU, a look at the CPL in cs will tell you the privilege level code is running with.

Keep in mind that the CPU privilege level has nothing to do with operating system users. Whether you’re root, Administrator, guest, or a regular user, it does not matter. All user code runs in ring 3 and all kernel code runs in ring 0, regardless of the OS user on whose behalf the code operates. Sometimes certain kernel tasks can be pushed to user mode, for example user-mode device drivers in Windows Vista, but these are just special processes doing a job for the kernel and can usually be killed without major consequences.

Due to restricted access to memory and I/O ports, user mode can do almost nothing to the outside world without calling on the kernel. It can’t open files, send network packets, print to the screen, or allocate memory. User processes run in a severely limited sandbox set up by the gods of ring zero. That’s why it’s impossible, by design, for a process to leak memory beyond its existence or leave open files after it exits. All of the data structures that control such things – memory, open files, etc – cannot be touched directly by user code; once a process finishes, the sandbox is torn down by the kernel. That’s why our servers can have 600 days of uptime – as long as the hardware and the kernel don’t crap out, stuff can run for ever. This is also why Windows 95 / 98 crashed so much: it’s not because “M$ sucks” but because important data structures were left accessible to user mode for compatibility reasons. It was probably a good trade-off at the time, albeit at high cost.

The CPU protects memory at two crucial points: when a segment selector is loaded and when a page of memory is accessed with a linear address. Protection thus mirrors memory address translation where both segmentation and paging are involved. When a data segment selector is being loaded, the check below takes place:

x86 Segment Protection
x86 Segment Protection

Since a higher number means less privilege, MAX() above picks the least privileged of CPL and RPL, and compares it to the descriptor privilege level (DPL). If the DPL is higher or equal, then access is allowed. The idea behind RPL is to allow kernel code to load a segment using lowered privilege. For example, you could use an RPL of 3 to ensure that a given operation uses segments accessible to user-mode. The exception is for the stack segment register ss, for which the three of CPL, RPL, and DPL must match exactly.

In truth, segment protection scarcely matters because modern kernels use a flat address space where the user-mode segments can reach the entire linear address space. Useful memory protection is done in the paging unit when a linear address is converted into a physical address. Each memory page is a block of bytes described by a page table entry containing two fields related to protection: a supervisor flag and a read/write flag. The supervisor flag is the primary x86 memory protection mechanism used by kernels. When it is on, the page cannot be accessed from ring 3. While the read/write flag isn’t as important for enforcing privilege, it’s still useful. When a process is loaded, pages storing binary images (code) are marked as read only, thereby catching some pointer errors if a program attempts to write to these pages. This flag is also used to implement copy on write when a process is forked in Unix. Upon forking, the parent’s pages are marked read only and shared with the forked child. If either process attempts to write to the page, the processor triggers a fault and the kernel knows to duplicate the page and mark it read/write for the writing process.

Finally, we need a way for the CPU to switch between privilege levels. If ring 3 code could transfer control to arbitrary spots in the kernel, it would be easy to subvert the operating system by jumping into the wrong (right?) places. A controlled transfer is necessary. This is accomplished via gate descriptors and via the sysenter instruction. A gate descriptor is a segment descriptor of type system, and comes in four sub-types: call-gate descriptor, interrupt-gate descriptor, trap-gate descriptor, and task-gate descriptor. Call gates provide a kernel entry point that can be used with ordinary call and jmp instructions, but they aren’t used much so I’ll ignore them. Task gates aren’t so hot either (in Linux, they are only used in double faults, which are caused by either kernel or hardware problems).

That leaves two juicier ones: interrupt and trap gates, which are used to handle hardware interrupts (e.g., keyboard, timer, disks) and exceptions (e.g., page faults, divide by zero). I’ll refer to both as an “interrupt”. These gate descriptors are stored in the Interrupt Descriptor Table (IDT). Each interrupt is assigned a number between 0 and 255 called a vector, which the processor uses as an index into the IDT when figuring out which gate descriptor to use when handling the interrupt. Interrupt and trap gates are nearly identical. Their format is shown below along with the privilege checks enforced when an interrupt happens. I filled in some values for the Linux kernel to make things concrete.

Interrupt Descriptor with Privilege Check
Interrupt Descriptor with Privilege Check

Both the DPL and the segment selector in the gate regulate access, while segment selector plus offset together nail down an entry point for the interrupt handler code. Kernels normally use the segment selector for the kernel code segment in these gate descriptors. An interrupt can never transfer control from a more-privileged to a less-privileged ring. Privilege must either stay the same (when the kernel itself is interrupted) or be elevated (when user-mode code is interrupted). In either case, the resulting CPL will be equal to to the DPL of the destination code segment; if the CPL changes, a stack switch also occurs. If an interrupt is triggered by code via an instruction like int n, one more check takes place: the gate DPL must be at the same or lower privilege as the CPL. This prevents user code from triggering random interrupts. If these checks fail – you guessed it – a general-protection exception happens. All Linux interrupt handlers end up running in ring zero.

During initialization, the Linux kernel first sets up an IDT in setup_idt() that ignores all interrupts. It then uses functions in include/asm-x86/desc.h to flesh out common IDT entries in arch/x86/kernel/traps_32.c. In Linux, a gate descriptor with “system” in its name is accessible from user mode and its set function uses a DPL of 3. A “system gate” is an Intel trap gate accessible to user mode. Otherwise, the terminology matches up. Hardware interrupt gates are not set here however, but instead in the appropriate drivers.

Three gates are accessible to user mode: vectors 3 and 4 are used for debugging and checking for numeric overflows, respectively. Then a system gate is set up for the SYSCALL_VECTOR, which is 0x80 for the x86 architecture. This was the mechanism for a process to transfer control to the kernel, to make a system call, and back in the day I applied for an “int 0x80” vanity license plate :). Starting with the Pentium Pro, the sysenter instruction was introduced as a faster way to make system calls. It relies on special-purpose CPU registers that store the code segment, entry point, and other tidbits for the kernel system call handler. When sysenter is executed the CPU does no privilege checking, going immediately into CPL 0 and loading new values into the registers for code and stack (cs, eip, ss, and esp). Only ring zero can load the sysenter setup registers, which is done in enable_sep_cpu().

Finally, when it’s time to return to ring 3, the kernel issues an iret or sysexit instruction to return from interrupts and system calls, respectively, thus leaving ring 0 and resuming execution of user code with a CPL of 3. Vim tells me I’m approaching 1,900 words, so I/O port protection is for another day. This concludes our tour of x86 rings and protection. Thanks for reading!

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Memory Translation and Segmentation

This post is the first in a series about memory and protection in Intel-compatible (x86) computers, going further down the path of how kernels work. As in the boot series, I’ll link to Linux kernel sources but give Windows examples as well (sorry, I’m ignorant about the BSDs and the Mac, but most of the discussion applies). Let me know what I screw up.

In the chipsets that power Intel motherboards, memory is accessed by the CPU via the front side bus, which connects it to the northbridge chip. The memory addresses exchanged in the front side bus are physical memory addresses, raw numbers from zero to the top of the available physical memory. These numbers are mapped to physical RAM sticks by the northbridge. Physical addresses are concrete and final – no translation, no paging, no privilege checks – you put them on the bus and that’s that. Within the CPU, however, programs use logical memory addresses, which must be translated into physical addresses before memory access can take place. Conceptually address translation looks like this:

Memory address translation
Memory address translation in x86 CPUs with paging enabled

This is not a physical diagram, only a depiction of the address translation process, specifically for when the CPU has paging enabled. If you turn off paging, the output from the segmentation unit is already a physical address; in 16-bit real mode that is always the case. Translation starts when the CPU executes an instruction that refers to a memory address. The first step is translating that logic address into a linear address. But why go through this step instead of having software use linear (or physical) addresses directly? For roughly the same reason humans have an appendix whose primary function is getting infected. It’s a wrinkle of evolution. To really make sense of x86 segmentation we need to go back to 1978.

The original 8086 had 16-bit registers and its instructions used mostly 8-bit or 16-bit operands. This allowed code to work with 216 bytes, or 64K of memory, yet Intel engineers were keen on letting the CPU use more memory without expanding the size of registers and instructions. So they introduced segment registers as a means to tell the CPU which 64K chunk of memory a program’s instructions were going to work on. It was a reasonable solution: first you load a segment register, effectively saying “here, I want to work on the memory chunk starting at X”; afterwards, 16-bit memory addresses used by your code are interpreted as offsets into your chunk, or segment. There were four segment registers: one for the stack (ss), one for program code (cs), and two for data (ds, es). Most programs were small enough back then to fit their whole stack, code, and data each in a 64K segment, so segmentation was often transparent.

Nowadays segmentation is still present and is always enabled in x86 processors. Each instruction that touches memory implicitly uses a segment register. For example, a jump instruction uses the code segment register (cs) whereas a stack push instruction uses the stack segment register (ss). In most cases you can explicitly override the segment register used by an instruction. Segment registers store 16-bit segment selectors; they can be loaded directly with instructions like MOV. The sole exception is cs, which can only be changed by instructions that affect the flow of execution, like CALL or JMP. Though segmentation is always on, it works differently in real mode versus protected mode.

In real mode, such as during early boot, the segment selector is a 16-bit number specifying the physical memory address for the start of a segment. This number must somehow be scaled, otherwise it would also be limited to 64K, defeating the purpose of segmentation. For example, the CPU could use the segment selector as the 16 most significant bits of the physical memory address (by shifting it 16 bits to the left, which is equivalent to multiplying by 216). This simple rule would enable segments to address 4 gigs of memory in 64K chunks, but it would increase chip packaging costs by requiring more physical address pins in the processor. So Intel made the decision to multiply the segment selector by only 24 (or 16), which in a single stroke confined memory to about 1MB and unduly complicated translation. Here’s an example showing a jump instruction where cs contains 0x1000:

Real mode segmentation
Real mode segmentation

Real mode segment starts range from 0 all the way to 0xFFFF0 (16 bytes short of 1 MB) in 16-byte increments. To these values you add a 16-bit offset (the logical address) between 0 and 0xFFFF. It follows that there are multiple segment/offset combinations pointing to the same memory location, and physical addresses fall above 1MB if your segment is high enough (see the infamous A20 line). Also, when writing C code in real mode a far pointer is a pointer that contains both the segment selector and the logical address, which allows it to address 1MB of memory. Far indeed. As programs started getting bigger and outgrowing 64K segments, segmentation and its strange ways complicated development for the x86 platform. This may all sound quaintly odd now but it has driven programmers into the wretched depths of madness.

In 32-bit protected mode, a segment selector is no longer a raw number, but instead it contains an index into a table of segment descriptors. The table is simply an array containing 8-byte records, where each record describes one segment and looks thus:

Segment descriptor
Segment descriptor

There are three types of segments: code, data, and system. For brevity, only the common features in the descriptor are shown here. The base address is a 32-bit linear address pointing to the beginning of the segment, while the limit specifies how big the segment is. Adding the base address to a logical memory address yields a linear address. DPL is the descriptor privilege level; it is a number from 0 (most privileged, kernel mode) to 3 (least privileged, user mode) that controls access to the segment.

These segment descriptors are stored in two tables: the Global Descriptor Table (GDT) and the Local Descriptor Table (LDT). Each CPU (or core) in a computer contains a register called gdtr which stores the linear memory address of the first byte in the GDT. To choose a segment, you must load a segment register with a segment selector in the following format:

Segment Selector
Segment Selector

The TI bit is 0 for the GDT and 1 for the LDT, while the index specifies the desired segment selector within the table. We’ll deal with RPL, Requested Privilege Level, later on. Now, come to think of it, when the CPU is in 32-bit mode registers and instructions can address the entire linear address space anyway, so there’s really no need to give them a push with a base address or other shenanigan. So why not set the base address to zero and let logical addresses coincide with linear addresses? Intel docs call this “flat model” and it’s exactly what modern x86 kernels do (they use the basic flat model, specifically). Basic flat model is equivalent to disabling segmentation when it comes to translating memory addresses. So in all its glory, here’s the jump example running in 32-bit protected mode, with real-world values for a Linux user-mode app:

Protected Mode Segmentation
Protected Mode Segmentation

The contents of a segment descriptor are cached once they are accessed, so there’s no need to actually read the GDT in subsequent accesses, which would kill performance. Each segment register has a hidden part to store the cached descriptor that corresponds to its segment selector. For more details, including more info on the LDT, see chapter 3 of the Intel System Programming Guide Volume 3a. Volumes 2a and 2b, which cover every x86 instruction, also shed light on the various types of x86 addressing operands – 16-bit, 16-bit with segment selector (which can be used by far pointers), 32-bit, etc.

In Linux, only 3 segment descriptors are used during boot. They are defined with the GDT_ENTRY macro and stored in the boot_gdt array. Two of the segments are flat, addressing the entire 32-bit space: a code segment loaded into cs and a data segment loaded into the other segment registers. The third segment is a system segment called the Task State Segment. After boot, each CPU has its own copy of the GDT. They are all nearly identical, but a few entries change depending on the running process. You can see the layout of the Linux GDT in segment.h and its instantiation is here. There are four primary GDT entries: two flat ones for code and data in kernel mode, and another two for user mode. When looking at the Linux GDT, notice the holes inserted on purpose to align data with CPU cache lines – an artifact of the von Neumann bottleneck that has become a plague. Finally, the classic “Segmentation fault” Unix error message is not due to x86-style segments, but rather invalid memory addresses normally detected by the paging unit – alas, topic for an upcoming post.

Intel deftly worked around their original segmentation kludge, offering a flexible way for us to choose whether to segment or go flat. Since coinciding logical and linear addresses are simpler to handle, they became standard, such that 64-bit mode now enforces a flat linear address space. But even in flat mode segments are still crucial for x86 protection, the mechanism that defends the kernel from user-mode processes and every process from each other. It’s a dog eat dog world out there! In the next post, we’ll take a peek at protection levels and how segments implement them.

Thanks to Nate Lawson for a correction in this post.

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Lucky to Be a Programmer

For the past few weeks I’ve been working with a fellow developer on a project that required an all-out programming effort. It’s done now, so we’re back to a regular schedule, but when people hear about the crazy hours they often say they’re sorry. They really shouldn’t be. I would never do this often, or for long periods, or without proper compensation if done for an employer, but the truth is that these programming blitzkriegs are some of my favorite periods in life. Under the right conditions, writing software is so intensely pleasurable it should be illegal.

Many programmers relate to this, but others are taken aback when they hear it. I think it’s because institutions are so good at squeezing the fun out of everything. It’s appalling for example how schools can take the most vibrant topics and mangle them into formulaic, mediocre slog. And so it is for programming. Many corporations turn an inherently rewarding experience into something people just barely stomach in exchange for a paycheck.

That’s too bad. Few things are better than spending time in a creative haze, consumed by ideas, watching your work come to life, going to bed eager to wake up quickly and go try things out. I am not suggesting that excessive hours are needed or even advisable; a sane schedule is a must except for occasional binges. The point is that programming is an intense creative pleasure, a perfect mixture of puzzles, writing, and craftsmanship.

Programming offers intriguing challenges and ample room for invention. Some problems are investigative and reductionist: Why is this code running slowly? What on earth is causing that bug? Others are constructive, like devising algorithms and architectures. All of them are a delight if you enjoy analytical work, immersed in a world full of beasts like malware, routers, caches, protocols, databases, graphs, and numbers.

This analytical side is what most people associate with programming. It does make it interesting, like a complex strategy game. But in most software the primary challenge is communication: with fellow programmers via code and with users via interfaces. By and large, writing code is more essay than puzzle. It is shaping your ideas and schemes into a coherent body; it is seeking clarity, simplicity and conciseness. Both code and interfaces abound with the simple joy of creation.

Another source of pleasure is that under certain conditions, beauty arises in programming. It may sound like bullshit but it’s real, the kind of thing that makes your day better. Take for example Euclid’s 2-line proof that prime numbers are infinite. I think many would find it beautiful – so succint and such a fascinating result. This is the beauty of math, cold and austere, and it pervades software. It is in clever algorithms like quicksort, in the sources of kernels and compilers, in elegant exploits and in the tricks we pull to solve everyday problems. When you see these solutions, be it famous algorithm or mundane trick, you smile and think “how smart” and it feels good. How noble in reason!

A non-math sort of beauty also exists in code, analogous to eloquence in discourse. It’s present in well-factored software that does a lot with little code, in short and crisp methods, in well-done architectures. Some languages make this hard and not all programmers produce it, but it’s a joy to read and work on such code. If you’re working in an expressive language with coworkers whose code you enjoy, it happens often enough to brighten things up.

Now for craftsmanship. In a sense software is abstract – where does program behavior exist but in our minds? Yet we call it building software for a reason. Programs are shaped feature by feature, architectures start out as scaffolds and grow, user interfaces come together, bugs are fixed and hotspots are optimized to make things run fast. Software provides a deeply satisfying sense of craft. We build stuff out of pure ideas and then get to watch it working to solve real problems and make people a little better off. Or far better off, as the case may be.

Take Biology. Despite nearly 400 years of scientific revolution, Biology has been unable to deliver on crucial problems like effective cures for viral infections or cancer. Some of our best progress, like antibiotics, has been due to chance and random experimentation. You start a clinical trial for a hypertension drug and suddenly – whoah – all your subjects have hard-ons! Viagra is born. To be sure, chance plays a role in all endeavours, but Physics and Chemistry have a comprehensive theoretical basis powering systematic improvements, whereas Biology has been largely confined to kludges. Wanna treat cancer? Here, blast the patient with radiation and poison and hopefully the cancer will die first. They’re brilliant kludges, and I’m happy to have them, but it’s a far cry from the precision we’ve had elsewhere.

Software is changing that. Just barely 50 years ago the shape of DNA was being discovered, but now anyone can browse and download hundreds of complete genome sequences. Or look up thousands of genes (DLEC1 for a random example), complete with nucleotide sequence, amino-acid sequence for expressed proteins, literature mentioning the gene, you name it! Or you can search vast gene and protein databases for nucleotide or amino-acid sequences, perhaps after sequencing something in ever-cheaper devices, and get a comprehensive report on the match. It doesn’t matter if they’re exact, because the algorithm in BLAST, the standard sequence search tool, delivers partial maches across databases and species, scored by match likelihood. These advances will enable massive breakthroughs in medicine. Biology is entering a new era, like Physics in the 18th century, propelled by software.

Yea, sure, biologists have a minor role :P, but we in computing increasingly power major developments in science, culture, and business. When a third-world kid looks up a Wikipedia entry, it’s our work too! We wrote the RFCs and the networking stacks, the browser and MediaWiki, the OSes and the HTTP servers. Not to mention a lot of the Wikipedia entries, but since a few were on company time I’ll leave them aside. The influence of technologists goes beyond bits and bytes: it was a programmer who invented wikis and our community started blogs. Henry Mencken pointed out correctly that “freedom of the press is limited to those who own one”. It’s a pity he’s not around to watch our creations break down the stifling conformity and cozy subservience of professional journalism. Less glamorously but to great benefit our applications have delivered steep productivity gains to businesses across the economy. These are a few examples in a long list.

Three years ago, when I finished my undergrad (after being a programmer for many years), I was about to enter med school. At that point, a couple of negative experiences had me somewhat burned out on computer work. I’m happy I stuck with it. I’m still interested in biomedical research, but if I were to get involved I’d rather come in from the software angle, because frankly it’s too much fun to pass on. My mom thinks I’m a typist but oh well.

If you find yourself stuck in a place that’s killing your innate passion for technology, by all means, move the hell on! Don’t stay put while your enthusiasm is slowly drained. It’s hard to find motivated people to hire so you’ve got a major asset already; there are plenty of employers – and companies to be started – that will better suit you. For people who think they might like programming, your mileage may vary, but I highly recommend it as a career. Not only is the outlook bullish on the job front, but as the role of software grows in society we’ll see more exciting and beneficial changes delivered by technology. I’m delighted to be along for the ride as constantly my art and craft I try to master.

PS: thanks for putting up with the irregular posting schedule. The plan is to stick to regular posting now that things have calmed down. And if you like the song, download the mp3 because the YouTube audio doesn’t do it justice.

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