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.

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

The revolution has to be customised

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.

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!

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

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.

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.

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.

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.

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.

Back in my days working in the Bell Labs Software Production Research organization (Production, indeed!) we had some back-of-the-envelope findings that suggested that consistent indentation style was one of the most statistically significant indicators of low bug density.

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.

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?

In general, the longer you wait before fixing a bug, the costlier (in time and money) it is to fix.

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

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

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.

I read books about successful people. In fact, I read every book or magazine I could get my hands on. I would tell myself 1 good idea would pay for the book and could make the difference between me making it or 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 customers or talking 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 haven’t started reading yet.

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.

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.

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. 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.

Software testing is not only ensuring absence of bugs but also ensuring presence of value.

Special cases can result in code that is riddled with if statements, which make the code hard to understand and lead to bugs. Thus, special cases should be eliminated wherever possible. The best way to do this is by designing the normal case in a way that automatically handles the special cases without any extra code.

Cognitive load: The second symptom of complexity is cognitive load, which refers to how much a developer needs to know in order to complete a task. A higher cognitive load means that developers have to spend more time learning the required information, and there is a greater risk of bugs because they have missed something important.

Most programmers approach software development with a mindset I call tactical programming. In the tactical approach, your main focus is to get something working, such as a new feature or a bug fix. At first glance this seems totally reasonable: what could be more important than writing code that works? However, tactical programming makes it nearly impossible to produce a good system design.

With the money they raised, the Ethereum team was also able to test the network before launch in a way that Satoshi and his small group of supporters were not able to. Starting at the end of 2014 and for the first half of 2015, the Ethereum Foundation encouraged battle testing of its network, both in a grassroots bug bounty program and in formal security audits that involved professional third-party software security firms.

The role of a maintainer is evolving. Rather than coordinating with a group of developers, these maintainers are defined by the need for curation: sifting through the noise of interactions, such as user questions, bug reports, and feature requests, which compete for their attention.

it’s tempting to chalk up the two crashes to software bugs that led automatic sensors to malfunction. Idiosyncratic failures in complex technology. But as before, look more closely and you will see some of the usual culprits defining complex failure: multiple causes in a reasonably familiar setting, with its false sense of security; missed signals; and interactive complexity in a shifting business environment.

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

Where was I. Oh yeah. Sometimes it is not worth fixing a bug. Here's another bug that's not worth fixing: If you have a bug that totally crashes your program when you open gigantic files, but it only happens to your single user who has OS/2 and who, for all you know, doesn't even use large files. Well, don't fix it. Worse things have happened at sea. Similarly, I've generally given up caring about people with 16-color screens or people running off-the-shelf Windows 95 with no upgrades in 7 years. People like that don't spend much money on packaged software products. Trust me.

The confidence you get from knowing about every crash, anywhere in the world, is crucial to delivering a high-quality product that needs to be used in the wild. In the consumer software business, you can't rely on your customers to tell you about crashes—many of them may not be technical enough, and most of them won't bother to take time off of their own important work to give you a useful crash report unless you make it completely automatic.

People are inherently imperfect - we like to say that humans are mostly a collection of intermittent bugs. But before you can understand the bugs in your coworkers, you need to understand the bugs in yourself. We’re going to ask you to think about your own reactions, behaviors, and attitudes - and in return, we hope you gain some real insight into how to become a more efficient and successful software engineer who spends less energy dealing with people-related problems and more time writing great code.

The programmer builds from pure thought-stuff: concepts and very flexible representations thereof. Because the medium is tractable, we expect few difficulties in implementation; hence our pervasive optimism. Because our ideas are faulty, we have bugs; hence our optimism is unjustified.

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.

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.

For example, it might be the case that 80 percent of a business’s profits come from just 20 percent of its clients, 80 percent of a nation’s wealth is held by its richest 20 percent of citizens, or 80 percent of computer software crashes come from just 20 percent of the identified bugs.

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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.

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

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.

goes wrong. It saves me a massive amount of time as I start trying to work through the problem as soon as it pops up. Here is a trick that has worked for me over the years and seems to be working for many artists working in the industry today. The next time you’re deep in production, and the software crashes or doesn’t give you the result you’re after, ask yourself, “What did I do wrong?” Don’t assume it is a bug in the software or blame the computer, even if it turns out that

Steve McConnell helped us understand how poorly timed thrashing sabotages every failed software project. It turns out that the problem extends far beyond software. Any project worth doing involves invention, inspiration, and at least a little bit of making stuff up. Traditionally, we start with an inkling, adding more and more detail as we approach the ship date. And the closer we get to shipping, the more thrashing occurs. Thrashing is the apparently productive brainstorming and tweaking we do for a project as it develops. Thrashing might mean changing the user interface or rewriting an introductory paragraph. Sometimes thrashing is merely a tweak; other times it involves major surgery. Thrashing is essential. The question is: when to thrash? In the typical amateur project, all the thrashing is near the end. The closer we get to shipping, the more people get involved, the more meetings we have, the more likely the CEO wants to be involved. And why not? What’s the point of getting involved early when you can’t see what’s already done and your work will probably be redone anyway? The point of getting everyone involved early is simple: thrash late and you won’t ship. Thrash late and you introduce bugs. Professional creators thrash early. The closer the project gets to completion, the fewer people see it and the fewer changes are permitted. Every software project that has missed its target date (every single one) is a victim of late thrashing. The creators didn’t have the discipline to force all the thrashing to the beginning. They fell victim to the resistance.

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At Google, this is exactly our goal: to merge development and testing so that you cannot do one without the other. Build a little and then test it. Build some more and test some more. The key here is who is doing the testing. Because the number of actual dedicated testers at Google is so disproportionately low, the only possible answer has to be the developer. Who better to do all that testing than the people doing the actual coding? Who better to find the bug than the person who wrote it? Who is more incentivized to avoid writing the bug in the first place? The reason Google can get by with so few dedicated testers is because developers own quality. If a product breaks in the field, the first point of escalation is the developer who created the problem, not the tester who didn’t catch it.

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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.

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 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?

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

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.

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

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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.

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.

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.

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.

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.

The idea that schedules can be shortened in order to reduce cost or speed up delivery is a very common misconception. You‘ll commonly see attempts to require overtime or sacrifice ―less important scheduled tasks (like unit-testing) as a way to reduce delivery dates or increase functionality while keeping the delivery dates as is. Avoid this scenario at all costs. Remind those requesting the changes of the following facts: - A rushed design schedule leads to poor design, bad documentation and probable Quality Assurance or User Acceptance problems. - A rushed coding or delivery schedule has a direct relationship to the number of bugs delivered to the users. - A rushed test schedule leads to poorly tested code and has a direct relationship to the number of testing issues encountered. - All of the above lead to Production issues which are much more expensive to fix.

because engineers are so creative, they like to make up new bugs, not use the same old ones.

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.

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.

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.

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.

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.

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.

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.

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?

• 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.