Software Bug Quotes

Wit and puns aren't just decor in the mind; they're essential signs that the mind knows it's on, recognizes its own software, can spot the bugs in its own program.

If debugging is the process of removing software bugs, then programming must be the process of putting them in.

Software testing is a sport like hunting, it's bughunting.

Somewhere in the existing software there was a bug, a potentially lethal flaw. Nothing less than the unselfing of the self would do. If he could cleanse the whole machine, then maybe the bug, too, would end up in the trash. After that, he could perhaps begin to construct a new man.

Dijkstra once said, “Testing shows the presence, not the absence, of bugs.” In other words, a program can be proven incorrect by a test, but it cannot be proven correct. All that tests can do, after sufficient testing effort, is allow us to deem a program to be correct enough for our purposes.

The revolution has to be customised

Without requirements and design, programming is the art of adding bugs to an empty text file.

Deeply entrenched fantasies and persistent, most cherished illusions can at least partly be explained as ‘bugs’ or ‘viruses’ in, or ‘mis-activations’ of, our sophisticated and highly sensitive intellectual software, which is driven but also easily disrupted by, and addicted to, our restless and insatiable need for meaning, order, control, and reassurance.

Bugs will happen. They cannot be eliminated, so they must be survived instead.

This is what makes them good engineers. Perfectionism: incinerating perfectionism.

We must not blame programmers for their bugs. They belong to them only until the code is merged to the repository. After that, all bugs are ours!

I always wished the Lord had created a humanity that doesn't have to waste so much of their precious time sleeping… and fighting different types of software bugs.

I believe humanity would develop their way forward quicker if a human didn't have to waste so much time on sleep and fighting countless software and device bugs.

Software is easy to make, except when you want it to do something new. And then, of course, there is a corollary: The only software that's worth making is software that does something new.

It is unit tests that keep our code flexible, maintainable, and reusable. The reason is simple. If you have tests, you do not fear making changes to the code! Without tests every change is a possible bug.

The job of a tester is to prove that the software is bug free, while it has to be the other way around: The job of a tester is to prove that the software is broken. The better testers are doing their jobs, the more bugs they manage to find and report.

All right, it's a beach. I'm just messing with you." "It would be funnier if we hadn't spent the last two days trying to hunt down the glitch." "Did you find it?" "Yes. The software seems to be submitting fake bug reports. Try to be serious." "Try to not call me 'the software.

I read every book and magazine I could. Heck, three bucks for a magazine, twenty bucks for a book. One good idea would lead to a customer or a solution, and those magazines and books paid for themselves many times over. Some of the ideas I read were good, some not. In doing all the reading I learned a valuable lesson. Everything I read was public. Anyone could buy the same books and magazines. The same information was available to anyone who wanted it. Turns out most people didn't want it. I remember going into customer meetings or talks or go to people in the industry and tossing out tidbits about software or hardware. Features that worked, bugs in the software. All things I had read. I expected the ongoing response of: "Oh yeah, I read that too in such-and-such." That's not what happened. They hadn't read it then, and they still haven't starting reading it. Most people won't put in the time to get a knowledge advantage. Sure, there were folks that worked hard at picking up every bit of information that they could, but we were few and far between. To this day, I feel like if I put in enough time consuming all the information available, particularly with the internet making it so readily accessible, I can get an advantage in any technology business. Of course, my wife hates that I read more than three hours almost every day, but it gives me a level of comfort and confidence in my businesses.

Software development is the process of creating a computer software. It includes preparing a design, coding the program, and fixing the bugs. The final goal of software development is to translate user needs to software product, while continuously improving the team and the process.

I write them to improve my productivity as a programmer. Making the quality assurance department happy is just a side effect. Unit tests are highly localized. Each test class works within a single package. It tests the interfaces to other packages, but beyond that it assumes the rest just works. Functional tests are a different animal. They are written to ensure the software as a whole works. They provide quality assurance to the customer and don't care about programmer productivity. They should be developed by a different team, one who delights in finding bugs.

I like my code to be elegant and efficient. The logic should be straightforward to make it hard for bugs to hide, the dependencies minimal to ease maintenance, error handling complete according to an articulated strategy, and performance close to optimal so as not to tempt people to make the code messy with unprincipled optimizations. Clean code does one thing well. -Bjarne Stroustrup, inventor of C++ and author of The C++ Programming Language

The Joel Test 1. Do you use source control? 2. Can you make a build in one step? 3. Do you make daily builds? 4. Do you have a bug database? 5. Do you fix bugs before writing new code? 6. Do you have an up-to-date schedule? 7. Do you have a spec? 8. Do programmers have quiet working conditions? 9. Do you use the best tools money can buy? 10. Do you have testers? 11. Do new candidates write code during their interview? 12. Do you do hallway usability testing?

Good ideas kill projects. Sometimes it's a quick death, but often it's a slow, lingering death caused by missed milestones and a spiraling bug count.

Testing does not improve a product; the improving is done by people fixing the bugs that testing has uncovered.

Without tests every change is a possible bug. No

Often when managers say, "Testing takes too long," what they should be saying is, "Fixing the bugs in the product takes too long"—a different cost category. Make sure you're accounting for effort and time under the correct cost category.

Testing may convincingly demonstrate the presence of bugs, but can never demonstrate their absence."- Edsger W. Dijkstra, Computing Pioneer (1930–2002), "Programming as a discipline of mathematical nature," Am. Math. Monthly, 81 (1974), No. 6, pp. 608–12.

Some people mistakenly refer to software defects as bugs. When called bugs, they seem like pesky things that should be swatted or even ignored. This trivializes a critical problem and fosters a wrong attitude. Thus, when an engineer says there are only a few bugs left in a program, the reaction is one of relief. *Supposed, however, that we called them time bombs instead of bugs.* Would you feel the same sense of relief if a programmer told you that he had thoroughly tested a program and there were only a few time bombs left in it? Just using a different term changes your attitude entirely.

Testing gathers information about a product; it does not fix things it finds that are wrong. Testing does not improve a product; the improving is done by people fixing the bugs that testing has uncovered. Often when managers say, "Testing takes too long," what they should be saying is, "Fixing the bugs in the product takes too long"—a different cost category.

Nintendo’s standards were exacting. “In terms of game testing they revolutionised the concept,” said Milgrom. “They said zero defects – we will not allow you to release a game that has any bugs in it whatsoever. Now zero defects was an unheard of concept in any other software or on any other gaming platform. Nintendo knew if they were going to sell it in the supermarkets and sell it to mums and dads it had to work off the shelf and had to be flawless. They didn’t want returns. We had to change our programming attitude and the way we developed games, which was brilliant. It was really hard work. If you had a bug in your final version you could miss Christmas because it would take a month for them to go through the testing of the title.

1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation

Set your sights higher. Don’t think of yourself as a programmer at a specific company—after all, it’s not likely that you’ll be at the same place forever—but as a participating member of an industry. You are a craftsperson or an artist. You have something to share beyond the expense-reporting application you’re developing for your human resources department or the bugs you’ve got stacked up in your company’s issue-tracking system.

Program maintenance involves no cleaning, lubrication, or repair of deterioration. It consists chiefly of changes that repair design defects. Much more often than with hardware, these changes include added functions. Usually they are visible to the user. The total cost of maintaining a widely used program is typically 40 percent or more of the cost of developing it. Surprisingly, this cost is strongly affected by the number of users. More users find more bugs.

Denise: "So your present project is ready to pass to the testing people?" Ralph: "Absolutely." Denise: "Okay, since you're so sure it's adequately tested, I'm going to make you the following generous offer: If fewer than three bugs turn up in your component during testing, I will give you a raise. But if three or more bugs turn up during testing, you won't earn a raise this year." Ralph: "Um . . ." Denise: "Um what?" "Could I just have the component back for a few little tests I want to do?

After manufacture, the units go into the field. With consumer products, that means they go into millions of homes where any bugs you created are enjoyed by many. With medical, aviation, or other critical products, your bugs may be catastrophic (which is why you get to do so much paperwork). With scientific or monitoring equipment, the field could be a place where the unit cannot ever be retrieved (or retrieved only at great risk and expense; consider the devices in volcano calderas), so it had better work.

Bitcoin’s Test Blockchains You might be surprised to learn that there is more than one bitcoin blockchain. The “main” bitcoin blockchain, the one created by Satoshi Nakamoto on January 3rd, 2009, the one with the genesis block we studied in this chapter, is called mainnet. There are other bitcoin blockchains that are used for testing purposes: at this time testnet, segnet, and regtest. Let’s look at each in turn. Testnet — Bitcoin’s Testing Playground Testnet is the name of the test blockchain, network, and currency that is used for testing purposes. The testnet is a fully featured live P2P network, with wallets, test bitcoins (testnet coins), mining, and all the other features of mainnet. There are really only two differences: testnet coins are meant to be worthless and mining difficulty should be low enough that anyone can mine testnet coins relatively easily (keeping them worthless). Any software development that is intended for production use on bitcoin’s mainnet should first be tested on testnet with test coins. This protects both the developers from monetary losses due to bugs and the network from unintended behavior due to bugs.

Or, suppose you want to motivate your managers to ship products on time, so you conspicuously promote each manager whose product goes out the door on schedule. All goes as planned until the situation arises in which one of your managers has a project where the testers are reporting numerous problems. Because managers who have shipped products on time have been promoted, this manager thinks, I want that promotion so I need to ship this on time, but those bug reports are getting in the way. I know what I'll do! I'll put the testers on another project until the developers have a chance to catch up.

One of those was Gary Bradski, an expert in machine vision at Intel Labs in Santa Clara. The company was the world’s largest chipmaker and had developed a manufacturing strategy called “copy exact,” a way of developing next-generation manufacturing techniques to make ever-smaller chips. Intel would develop a new technology at a prototype facility and then export that process to wherever it planned to produce the denser chips in volume. It was a system that required discipline, and Bradski was a bit of a “Wild Duck”—a term that IBM originally used to describe employees who refused to fly in formation—compared to typical engineers in Intel’s regimented semiconductor manufacturing culture. A refugee from the high-flying finance world of “quants” on the East Coast, Bradski arrived at Intel in 1996 and was forced to spend a year doing boring grunt work, like developing an image-processing software library for factory automation applications. After paying his dues, he was moved to the chipmaker’s research laboratory and started researching interesting projects. Bradski had grown up in Palo Alto before leaving to study physics and artificial intelligence at Berkeley and Boston University. He returned because he had been bitten by the Silicon Valley entrepreneurial bug.

There, in that presumed paradise, the engineers were stranded in the company of an infantile mentality. They created artificial smartness, made a simulacrum of intelligence. But what they talked to all day was little more than a mechanism that read bits off a disk drive. If a comma in the code was out of place, it complained like a kid who won’t tolerate a pea touching the mashed potatoes. And, exhausted though the programmer may be, the machine was like an uncanny child that never got tired. There was Karl and the rest of the team, fitting the general definition of the modern software engineer: a man left alone all day with a cranky, illiterate thing, which he must somehow make grow up. It was an odd and satisfying gender revenge. Is it any surprise that these isolated men need relief, seek company, hook up This is not to say that women are not capable of engineering’s male-like isolation. Until I became a programmer, I didn’t thoroughly understand the usefulness of such isolation: the silence, the reduction of life to thought and form; for example, going off to a dark room to work on a program when relations with people get difficult. I’m perfectly capable of this isolation. I first noticed it during the visit of a particularly tiresome guest. All I could think was: There’s that bug waiting for me, I really should go find that bug.

Bored with Pisit today, I switch to our public radio channel, where the renowned and deeply reverend Phra Titapika is lecturing on Dependent Origination. Not everyone’s cup of chocolate, I agree (this is not the most popular show in Thailand), but the doctrine is at the heart of Buddhism. You see, dear reader (speaking frankly, without any intention to offend), you are a ramshackle collection of coincidences held together by a desperate and irrational clinging, there is no center at all, everything depends on everything else, your body depends on the environment, your thoughts depend on whatever junk floats in from the media, your emotions are largely from the reptilian end of your DNA, your intellect is a chemical computer that can’t add up a zillionth as fast as a pocket calculator, and even your best side is a superficial piece of social programming that will fall apart just as soon as your spouse leaves with the kids and the money in the joint account, or the economy starts to fail and you get the sack, or you get conscripted into some idiot’s war, or they give you the news about your brain tumor. To name this amorphous morass of self-pity, vanity, and despair self is not only the height of hubris, it is also proof (if any were needed) that we are above all a delusional species. (We are in a trance from birth to death.) Prick the balloon, and what do you get? Emptiness. It’s not only us-this radical doctrine applies to the whole of the sentient world. In a bumper sticker: The fear of letting go prevents you from letting go of the fear of letting go. Here’s the good Phra in fine fettle today: “Take a snail, for example. Consider what brooding overweening self-centered passion got it into that state. Can you see the rage of a snail? The frustration of a cockroach? The ego of an ant? If you can, then you are close to enlightenment.” Like I say, not everyone’s cup of miso. Come to think of it, I do believe I prefer Pisit, but the Phra does have a point: take two steps in the divine art of Buddhist meditation, and you will find yourself on a planet you no longer recognize. Those needs and fears you thought were the very bones of your being turn out to be no more than bugs in your software. (Even the certainty of death gets nuanced.) You’ll find no meaning there. So where?

The thing about Web companies is there's always something severely fucked-up. There is always an outage, always lost data, always compromised customer information, always a server going offline. You work with these clugey internal tools and patch together work-arounds to compensate for the half-assed, rushed development, and after a while the fucked-upness of the whole enterprise becomes the status quo. VPs insecure that they're not as in touch as they need to be with conditions on the ground insert themselves into projects midstream and you get serious scope creep. You present to the world this image that you're a buttoned-down tech company with everything in its right place but once you're on the other side of the firewall it looks like triage time in an emergency room, 24/7. Systems break down, laptops go into the blue screen of death, developers miskey a line of code, error messages appear that mean absolutely nothing. The instantaneousness with which you can fix stuff creates a culture that works by the seat of its pants. I swear the whole Web was built by virtue of developers fixing one mistake after another, constantly forced to compensate for the bugginess of their code.

five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle.

In quel preciso momento, Karla è entrata nella stanza. Ha spento la televisione, ha guardato Todd fisso negli occhi e ha detto: "Todd, tu esisti non soltanto come membro di una famiglia o di una compagnia o di una nazione, ma come membro di una specie... sei un essere umano. Sei parte dell'umanità. Attualmente la nostra specie ha problemi profondi e stiamo cercando di sognare un modo per uscirne e stiamo usando i computer per cavarcela. La costruzione di hardware e software è il campo in cui la specie ha deciso di investire energie per la sua sopravvivenza e questa costruzione richiede zone di pace, bambini nati dalla pace, e l'assenza di distrazioni che interferiscano col codice. Non possiamo acquisire conoscenza attraverso l'informatica, ma riusciremo a usarla per tenerci fuori dalla merda. Quello che tu percepisci come un vuoto è un paradiso terrestre: alla lettera, linea per linea, la libertà di impedire all'umanità di diventare non lineare". Si è seduta sul divano e c'era il rumore della pioggia che tamburellava sul soffitto e mi sono reso conto del fatto che non c'era abbastanza luce nella stanza e che noi eravamo tutti in silenzio. Karla ha detto: "Abbiamo avuto una vita discreta. Nessuno di noi, a quanto mi risulta, è mai stato maltrattato. Non abbiamo mai desiderato niente, né abbiamo mai voluto possedere qualcosa. I nostri genitori sono tutti ancora insieme, a parte quelli di Susan. Ci hanno trattato bene, ma la vera moralità, qui. Todd consiste nel sapere se le loro mani sono state sprecate in vite non creative, o se queste mani sono utilizzate per portare avanti il sogno dell'umanità". Continuava a piovere. "Non è una coincidenza che come specie abbiamo inventato la classe media. Senza la classe media, non avremmo potuto avere quel particolare tipo di configurazione mentale che contribuisce in misura consistente a sputar fuori i sistemi informatici e la nostra specie non avrebbe mai potuto farcela ad arrivare allo stadio evolutivo successivo, qualunque esso sia. Ci sono buone probabilità che la classe media non rientri neanche parzialmente nella prossima fase evolutiva. Ma non è né qui né là. Che ti piaccia o no, Todd, tu, io, Dan, Abe, Bug, e Susan... tutti noi siamo fabbricanti del prossimo ciclo Rem del sogno umano. Tutti gli altri ne saranno attratti. Non metterli in discussione, Todd, e non crogiolartici dentro, ma non permettere mai a te stesso di dimenticarlo".

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

I became a broken record on the algorithm,” Musk says. “But I think it’s helpful to say it to an annoying degree.” It had five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

There's an old joke among software developers. When something works in an unexpected but strangely effective way, the developers often kid, "Oh, that's not a bug. That's a future." While this is usually a joke, designers can use the same technique of reframing the problem when tackling their own projects. In fact, there's an old joke among designers: "It's not a problem. It's an opportunity.

Software development requires the cooperation of everyone on the team. Programmers are often called “developers,” but in reality everyone on the team is part of the development effort. When you share the work, customers identify the next requirements while programmers work on the current ones. Testers help the team figure out how to stop introducing bugs. Programmers spread the cost of technical infrastructure over the entire life of the project. Above all, everyone helps keep everything clean.

Continuous delivery is a set of capabilities that enable us to get changes of all kinds—features, configuration changes, bug fixes, experiments—into production or into the hands of users safely, quickly, and sustainably.

Complexity contributes to two major failure categories: software bugs and operator error.

Anything written by people has bugs. Not testing something is equivalent to asserting that it's bug-free. Programmers can't think of everything especially of all the possible interactions between features and between different pieces of software. We try to break software because that's the only practical way we know of to be confident about the product's fitness for use.

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There were in fact bugs," he recalls, "But the essential difference was in the obviousness of bugs, the repeatability of bugs, and potential for fixing bugs oneself. In this environment, bugs were only temporary delays on a steady road towards excellence and stability.

Start by writing a list of questions that you expect testing activities to answer. For example, you might have very general questions, like these: Can a user actually use the software for its intended purpose? Do the basic workflows work? You might also have specific questions about capabilities or interactions, such as this: How does the discounting feature interact with the bundling feature? You might have questions about overarching concerns or characteristics: Will the software fail gracefully if it’s overloaded? Brainstorm a list of questions. When you run out of steam, review your list.

Minsky was an ardent supporter of the Cyc project, the most notorious failure in the history of AI. The goal of Cyc was to solve AI by entering into a computer all the necessary knowledge. When the project began in the 1980s, its leader, Doug Lenat, confidently predicted success within a decade. Thirty years later, Cyc continues to grow without end in sight, and commonsense reasoning still eludes it. Ironically, Lenat has belatedly embraced populating Cyc by mining the web, not because Cyc can read, but because there’s no other way. Even if by some miracle we managed to finish coding up all the necessary pieces, our troubles would be just beginning. Over the years, a number of research groups have attempted to build complete intelligent agents by putting together algorithms for vision, speech recognition, language understanding, reasoning, planning, navigation, manipulation, and so on. Without a unifying framework, these attempts soon hit an insurmountable wall of complexity: too many moving parts, too many interactions, too many bugs for poor human software engineers to cope with. Knowledge engineers believe AI is just an engineering problem, but we have not yet reached the point where engineering can take us the rest of the way. In 1962, when Kennedy gave his famous moon-shot speech, going to the moon was an engineering problem. In 1662, it wasn’t, and that’s closer to where AI is today. In industry, there’s no sign that knowledge engineering will ever be able to compete with machine learning outside of a few niche areas. Why pay experts to slowly and painfully encode knowledge into a form computers can understand, when you can extract it from data at a fraction of the cost? What about all the things the experts don’t know but you can discover from data? And when data is not available, the cost of knowledge engineering seldom exceeds the benefit. Imagine if farmers had to engineer each cornstalk in turn, instead of sowing the seeds and letting them grow: we would all starve.

Bugs were the backdrop of the code writer’s life. A comma in the wrong place. An “if” where there should be a “then.” An erroneous call from one piece of the program to another. Each could instantly cause a seizure, the collapse of a finely wrought abstraction into a puddle of ones and zeroes. Only human, software was born to fail. If not catastrophically, then aesthetically. Every software captain knew this.

All software has bugs – it’s just a fact of life. You

Then, just when it seemed that only the barest of bugs survived, there would be a new version of the software. And with that, a fresh opportunity for introducing bugs.

Fixing a bug is much like adding a new feature: the presence of the bug suggests that a case was missing from the initial test suite, and the bug fix should include that missing test case.

They can mislead us and can even cause pain, but their quirky behavior, to borrow from computer programming parlance, is almost always a feature of the software, not a bug in the program. However abnormal your mind may seem to you, it is probably functioning as it should.

They gave you, like, an hour of time. That’s all you’d get. But someone figured out that if you put in ‘time equals’ and then a letter, like t equals k, they wouldn’t charge you,” he said, laughing at the memory. “It was a bug in the software. You could put in t equals k and sit there forever.” Just look at the stream of opportunities that came Bill Joy’s way. Because he happened to go to a farsighted school like the University of Michigan,

The systems that we build please their users more. We see dramatically fewer bugs in production, and teams that employ these ideas find it significantly easier to change almost any aspect of the systems that they work on as their learning evolves. The bottom-line result of this is usually greater commercial success for the organizations that practice in this way. These attributes are the hallmarks of engineering.

I think what’s occurring is a stealthy rebranding: the word ‘problem’ has become too emotionally loaded to be uttered in polite company in case we think bad things about the companies responsible. So software bugs are now issues rather than problems, even if they stop our computers working and ruin our day. Or, for my CEO, the bug is an opportunity. He was in the software business, and the only opportunity a broken computer gives you is the opportunity to wait for tech support to call back. We now have ‘performance issues’ with staff who fall asleep on their keyboard, or ‘brand issues’ with companies that nobody likes, or, worst of all, ‘balance sheet issues’, as described by Lehman Brothers, shortly before it ceased to be Lehman Brothers. At least they didn’t call it a ‘balance sheet opportunity’, though I bet someone suggested it. Rule of thumb on issues: it doesn’t matter whether your company admits to balance sheet issues or problems, it still might be time to send out your CV.

Program testing can be used to show the presence of bugs, but never to show their absence!

the greatest limitation in writing software is our ability to understand the systems we are creating. As a program evolves and acquires more features, it becomes complicated, with subtle dependencies between its components. Over time, complexity accumulates, and it becomes harder and harder for programmers to keep all of the relevant factors in their minds as they modify the system. This slows down development and leads to bugs, which slow development even more and add to its cost. Complexity increases inevitably over the life of any program. The larger the program, and the more people that work on it, the more difficult it is to manage complexity.

Overall, the best way to reduce bugs is to make software simpler.

Of the three manifestations of complexity, unknown unknowns are the worst. An unknown unknown means that there is something you need to know, but there is no way for you to find out what it is, or even whether there is an issue. You won’t find out about it until bugs appear after you make a change.

If code is obvious, a reader doesn’t need to spend much time or effort to gather all the information they need to work with the code. If code is not obvious, then a reader must expend a lot of time and energy to understand it. Not only does this reduce their efficiency, but it also increases the likelihood of misunderstanding and bugs. Obvious code needs fewer comments than nonobvious code.

Selecting names for variables, methods, and other entities is one of the most underrated aspects of software design. Good names are a form of documentation: they make code easier to understand. They reduce the need for other documentation and make it easier to detect errors. Conversely, poor name choices increase the complexity of code and create ambiguities and misunderstandings that can result in bugs.

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physical sharing and exchange of computer tapes and disks on which the code was recorded. In current Internet days, rapid technological advances in computer hardware and software and networking technologies have made it much easier to create and sustain a communal development style on ever-larger scales. Also, implementing new projects is becoming progressively easier as effective project design becomes better understood, and as prepackaged infrastructural support for such projects becomes available on the Web. Today, an open source software development project is typically initiated by an individual or a small group seeking a solution to an individual's or a firm's need. Raymond (1999, p. 32) suggests that "every good work of software starts by scratching a developer's personal itch" and that "too often software developers spend their days grinding away for pay at programs they neither need nor love. But not in the (open source) world...." A project's initiators also generally become the project's "owners" or "maintainers" who take on responsibility for project management." Early on, this individual or group generally develops a first, rough version of the code that outlines the functionality envisioned. The source code for this initial version is then made freely available to all via downloading from an Internet website established by the project. The project founders also set up infrastructure for the project that those interested in using or further developing the code can use to seek help, provide information or provide new open source code for others to discuss and test. In the case of projects that are successful in attracting interest, others do download and use and "play with" the code-and some of these do go on to create new and modified code. Most then post what they have done on the project website for use and critique by any who are interested. New and modified code that is deemed to be of sufficient quality and of general interest by the project maintainers is then added to the authorized version of the code. In many projects the privilege of adding to the authorized code is restricted to only a few trusted developers. These few then serve as gatekeepers for code written by contributors who do not have such access (von Krogh and Spaeth 2002). Critical tools and infrastructure available to open source software project participants includes email lists for specialized purposes that are open to all. Thus, there is a list where code users can report software failures ("bugs") that they encounter during field use of the software. There is also a list where those developing the code can share ideas about what would be good next steps for the project, good features to add, etc. All of these lists are open to all and are also publicly archived,

Your career is stagnating by the minute. You are steadily letting your sedentary computer-programming desk-bound lifestyle turn your body into mush. All of these problems are much bigger and harder to just fix than a bug. They’re all complex, hard to measure, and comprised of many different small solutions—some of which will fail to work!

A lot of development has always been informally subsidized. When a system administrator writes a network analysis tool to help him do his job, then posts it online and gets bug fixes and feature contributions from other system administrators, what’s happened is that an unofficial consortium has been formed.

Any piece of prototype software developed for research purposes will have lots of unforeseen bugs

the real world just won't let us produce much that's truly perfect, particularly not bug-free software. Time, technology, and temperament all conspire against us.

Open-source software shows the potential of social norms. In the case of Linux and other collaborative projects, you can post a problem about a bug on one of the bulletin boards and see how fast someone, or often many people, will react to your request and fix the software-using their own leisure time. Could you pay for this level of service? Most likely. But if you had to hire people of the same caliber they would cost you an arm and a leg. Rather, people in these communities are happy to give their time to society at large (for which they get the same social benefits we all get from helping a friend paint a room). What can we learn from this that is applicable to the business world? There are social rewards that strongly motivate behavior-and one of the least used in corporate life is the encouragement of social rewards and reputation.

According to a study by Carnegie Mellon University, commercial software typically has twenty to thirty bugs for every thousand lines of code—fifty million lines of code means 1 million to 1.5 million potential errors to be exploited. This is the basis for all malware attacks that take advantage of these computer bugs to get the code to do something it was not originally intended to do. As computer code grows more elaborate, software bugs flourish and security suffers, with increasing consequences for society at large.

One of the primary reasons that abstraction is overloved is that a completed program full of the right abstractions is perfectly beautiful. But there are very few completed programs, because programs are written, maintained, bugs are fixed, features are added, performance is tuned, and a whole variety of changes are made both by the original and new programming team members. Thus, the way a program looks in the end is not important because there is rarely an end, and if there is one it isn't planned.

If “ship early, ship often” is interpreted as the willingness to expose not-quite-feature-complete but well-tested products to the healthy pressures of real users, everybody wins. But if it is used as an excuse for shipping half-baked, flaky products; using your customers as unpaid quality-assurance staff—and counting on ever-lowering expectations of quality in a slipshod marketplace numbed by crashing TVs and bug-filled software—it is another matter entirely. Even

Even seasoned code writers could not dismiss the possibility of being trapped in something akin to an infinite loop, wherein fixes spawned their own bugs. It had happened to others. The history of software was littered with projects, large and small, that had been abandoned in disgust, destroying careers.

• Detect bugs as early as possible, and fix them as soon as they come to light. • Act as though bug-free software was an attainable goal, but tem- per perfectionism with pragmatism. • If you find yourself faced with a poor quality codebase, do the following: – Recognize there is no silver bullet. – Make sure that the basics are in place first. – Separate clean code from unclean, and keep it clean. – Use bug triage to keep on top of your bug database. – Incrementally clean up bad code by adding tests and refac- toring.

Kidnapping is a harsh word.” “But accurate. I assume you’re not going to hang around Mars until I fix the software bug, if a problem ever existed. I’m on a one-way voyage to Slakeria, right?

The big challenge is, we have to constrain and mold our ambition level without losing the spark. The stuff I lose sleep over nigh is, how are we doing on this? We want to make progress as fast as possible without exploiting human resources. How do you move faster without killing people? How do you build a community around the project without losing design integrity? And how do we get on an arc that moves from benign dictatorship to more small-group democracy?

Their first task therefore, was to translate the original C# codebase into Java so that it could leverage Google's infrastructure. One of Schillace's co-founders argued that they ought to rewrite the parts of the codebase they didn't like at the same time. After all, why rewrite the codebase to Java only to have to immediately throw parts away? Schillace fought hard against that logic, saying, "We're not doing that because we'll get lost. Step one is translate to Java and get it stood back up on it's feet again ... [O]nce it's working again in Java, step two is ... go refactor and rewrite stuff that's bugging you.

Two factors usually determine how hard a bug is to fix: How reproducible it is. The time between the cause of the bug entering the code, the “software fault” itself — the bad line of code, or faulty integration assumption — and you actually noticing.

It’s open season; a season that lasts all year round. There are no permits required, no restrictions levied. Grab yourself a shotgun and head out into the open software fields to root out those pesky varmints, the elusive bugs, and squash them, dead. OK, reality is not as saccharin as that.

A staggering $312 billion per year is spent on the wage bills for programmers debugging their software. To put that in perspective, that’s two times all Eurozone bailouts since 2008! This huge, but realistic, figure comes from research carried out by Cambridge University’s Judge Business School.[9] You have a responsibility to fix bugs faster: to save the global economy. The state of the world is in your hands.

Software bugs are like cockroaches; there are probably dozens hiding in difficult to reach places for every one you find and fix.

Bug fixes were for the customers, the soft, lazy civilians who only got the software after it was finished and boring and safe. Real game developers worked with real software, the kind that broke a third of the time unless you knew exactly what you were doing.

Doctors troubleshoot the human body—they never got a chance to debug it. (It took God one day to design, prototype, and release that product; talk about schedule pressure! I guess we can forgive priority-two bugs like bunions and male pattern baldness.)

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I was enraptured by the brain and how it could misfire, but it wasn’t just the hardware that intrigued me, it was the software with the bugs.

Reusability is key in reducing bugs and coding quickly. The more I use a piece of code, the more confident and familiar I become with it, which in turn significantly speeds up my development time.

The Core Debugging Process The core of the debugging process consists of four steps: Reproduce: Find a way to reliably and conveniently reproduce the problem on demand. Report erratum Prepared exclusively for castLabs GmbH this copy is (P2.0 printing, February 2010) FIRST THINGS FIRST 18 Diagnose: Construct hypotheses, and test them by performing experiments until you are confident that you have identified the underlying cause of the bug. Fix: Design and implement changes that fix the problem, avoid intro- ducing regressions, and maintain or improve the overall quality of the software. Reflect: Learn the lessons of the bug. Where did things go wrong? Are there any other examples of the same problem that will also need fixing? What can you do to ensure that the same problem doesn’t happen again?

it is pretty much impossible to come up with perfect code first time around. It is only when people are using the software, putting it under strain, that you see the bugs and deficiencies you could never have anticipated. By putting the code out there and subjecting it to trial and error you learn the insights that create progress. Why, he asked Vanier, would you try to answer every question before you have a single user?

Systems Test No parts of the schedule are so thoroughly affected by sequential constraints as component debugging and system test. Furthermore, the time required depends on the number and subtlety of the errors encountered. Theoretically this number should be zero. Because of optimism, we usually expect the number of bugs to be smaller than it turns out to be. Therefore testing is usually the most mis-scheduled part of programming. For some years I have been successfully using the following rule of thumb for scheduling a software task: l /3 planning l/6 coding l/4 component test and early system test l/4 system test, all components in hand.

Your team may be called “quality assurance.” Don’t let that go to your head. Your test results and bug reports provide information that facilitates the assurance of quality on the project, but that assurance results from the effort of the entire team.

Writing and repairing software generally takes far more time and is far more expensive than initially anticipated. “Every feature that is added and every bug that is fixed,” Edward Tenner points out, “adds the possibility of some new and unexpected interaction between parts of the program.”19 De Jager concurs: “If people have learned anything about large software projects, it is that many of them miss their deadlines, and those that are on time seldom work perfectly. … Indeed, on-time error-free installations of complex computer systems are rare.”20 Even small changes to code can require wholesale retesting of entire software systems. While at MIT in the 1980s, I helped develop some moderately complex software. I learned then that the biggest problems arise from bugs that creep into programs during early stages of design. They become deeply embedded in the software’s interdependent network of logic, and if left unfixed can have cascading repercussions throughout the software. But fixing them often requires tracing out consequences that have metastasized in every direction from the original error. As the amount of computer code in our world soars (doubling every two years in consumer products alone), we need practical ways to minimize the number of bugs. But software development is still at a preindustrial stage—it remains more craft than engineering. Programmers resemble artisans: they handcraft computer code out of basic programming languages using logic, intuition, and pattern-recognition skills honed over years of experience.

When the handwritten guidance program was transcribed in Florida, a superscript bar was mistakenly left off the program. That one mistake meant that the program wasn’t able to correct the rocket’s course. Both the hardware failure of the Atlas antenna and the software bug in its guidance system meant that Mariner was completely out of control.