Developer Tester Quotes

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

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?

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.

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.

English Gingerbread Cake Serves: 12 to 16 Baking Time: 50 to 60 minutes Kyle Cathie, editor for the British version of The Cake Bible (and now a publisher), informed me in no uncertain terms that a book could not be called a cake "bible" in England if it did not contain the beloved gingerbread cake. When I went to England to retest all the cakes using British flour and ingredients, I developed this gingerbread recipe. Now that I have tasted it, I quite agree with Kyle. It is a moist spicy cake with an intriguing blend of buttery, lemony, wheaty, and treacly flavors. Cut into squares and decorated with pumpkin faces, it makes a delightful "treat" for Halloween. Batter Volume Ounce Gram unsalted butter (65° to 75°F/19° to 23°C) 8 tablespoons (1 stick) 4 113 golden syrup or light corn syrup 1¼ cups (10 fluid ounces) 15 425 dark brown sugar, preferably Muscovado ¼ cup, firmly packed 2 60 orange marmalade 1 heaping tablespoon 1.5 40 2 large eggs, at room temperature ¼ cup plus 2 tablespoons (3 fluid ounces) 3.5 100 milk 2/3 cup (5.3 fluid ounces) 5.6 160 cake flour (or bleached all-purpose flour) 1 cup plus 2 tablespoons (or 1 cup), sifted into the cup and leveled off 4 115 whole wheat flour 1 cup minus 1 tablespoon (lightly spooned into the cup) 4 115 baking powder 1½ teaspoons . . cinnamon 1 teaspoon . . ground ginger 1 teaspoon . . baking soda ½ teaspoon . . salt pinch . . Special Equipment One 8 by 2-inch square cake pan or 9 by 2-inch round pan (see Note), wrapped with a cake strip, bottom coated with shortening, topped with a parchment square (or round), then coated with baking spray with flour Preheat the Oven Twenty minutes or more before baking, set an oven rack in the lower third of the oven and preheat the oven to 325°F/160°C. Mix the Liquid Ingredients In a small heavy saucepan, stir together the butter, golden syrup, sugar, and marmalade over medium-low heat until melted and uniform in color. Set aside uncovered until just barely warm, about 10 minutes. Whisk in the eggs and milk. Make the Batter In a large bowl, whisk together the cake flour, whole wheat flour, baking powder, cinnamon, ginger, baking soda, and salt. Add the butter mixture, stirring with a large silicone spatula or spoon just until smooth and the consistency of thick soup. Using the silicone spatula, scrape the batter into the prepared pan. Bake the Cake Bake for 50 to 60 minutes, or until a wire cake tester inserted in the center comes out clean and the cake springs back when pressed lightly in the center. The cake should start to shrink from the sides of the pan only after removal from the oven. Cool the Cake Let the cake cool in the pan on a wire rack for 10 minutes. While the cake is cooling, make the syrup.

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.

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.

In many organizations where automated functional testing is done at all, a common practice is to have a separate team dedicated to the production and maintenance of the test suite. As described at length in Chapter 4, “Implementing a Testing Strategy,” this is a bad idea. The most problematic outcome is that the developers don’t feel as if they own the acceptance tests. As a result, they tend not to pay attention to the failure of this stage of the deployment pipeline, which leads to it being broken for long periods of time. Acceptance tests written without developer involvement also tend to be tightly coupled to the UI and thus brittle and badly factored, because the testers don’t have any insight into the UI’s underlying design and lack the skills to create abstraction layers or run acceptance tests against a public API.

A common pattern for teams that start with test automation, or development groups that start breaking down silos between testers and developers, is to take existing manual tests and automate them. Unless it’s a training exercise for an automation tool, this is almost always a bad idea.

In the AJAX world, a client can make a request, the server responds that it has received the request (so the client can get on with something else), and then at some random time later the actual response to the original request is returned. You see the problem? It becomes a challenge to match requests with the correct responses. From a programming standpoint, the performance tool must spawn a thread that waits for thecorrect response while the rest of the script continues to execute. A deft scripter may be able to code around this, but it may require signifcant changes to a script with the accompanying headache of ongoing maintenance. The reality is that not all testers are bored developers, so it’s better for the performance tool to handle this automatically.

Most software is designed for the development lab or the testers in the Quality Assurance (QA) department.

Developers should get feedback from a more comprehensive suite of acceptance and performance tests every day. Furthermore, current builds should be available to testers for exploratory testing.

Women in technology are stereotyped. Many men—and some women—often assume that a female programmer is not going to be as technically competent. A woman in technology can also be thought of as either not as passionate or dedicated as a man, or seen as a geeky anomaly who isn’t very feminine, but hangs with the guys and plays Zelda. Women are often thought to be good testers, but not taken as seriously in software developer roles.

Cucumber gives the business, developers, and testers a way to collaborate and specify, in plain English, how the system should work.

Specifically, engineering roles that enable developers to do testing efficiently and effectively have to exist. At Google, we have created roles in which some engineers are responsible for making other engineers more productive and more quality-minded. These engineers often identify themselves as testers, but their actual mission is one of productivity. Testers are there to make developers more productive and a large part of that productivity is avoiding re-work because of sloppy development. Quality is thus a large part of that productivity. We are going to spend significant time talking about each of these roles in detail in subsequent

SETs are the engineers involved in enabling testing at all levels of the Google development process we just described. SETs are Software Engineers in Test. First and foremost, SETs are software engineers and the role is touted as a 100 percent coding role in our recruiting literature and internal job promotion ladders. It’s an interesting hybrid approach to testing that enables us to get testers involved early in a way that’s not about touchy-feely “quality models” and “test plans” but as active participants in designing and creating the codebase. It creates an equal footing between feature developers and test developers that is productive and lends credibility to all types of testing, including manual and exploratory testing that occurs later in the process and is performed by a different set of engineers.

In many ways, being a good tester is harder than being a good developer because testing requires not only a very good understanding of of the development process and its products, but it also demands an ability to anticipate likely faults and errors

Quality is a product of a conflict between programmers and testers.

Open-source development breaks this bind, making it far easier for tester and developer to develop a shared representation grounded in the actual source code and to communicate effectively about it.

Developers and testers usually maintain a very healthy India-Pakistan like camaraderie

Business analyst is the one who is adept in confusing the customer, developer and testers simultaneously

Scarcity of resources brings clarity to execution and it creates a strong sense of ownership by those on a project. Imagine raising a child with a large staff of help: one person for feeding, one for diapering, one for entertainment, and so on. None of these people is as vested in the child’s life as a single, overworked parent. It is the scarcity of the parenting resource that brings clarity and efficiency to the process of raising children. When resources are scarce, you are forced to optimize. You are quick to see process inefficiencies and not repeat them. You create a feeding schedule and stick to it. You place the various diapering implements in close proximity to streamline steps in the process. It’s the same concept for software-testing projects at Google. Because you can’t simply throw people at a problem, the tool chain gets streamlined. Automation that serves no real purpose gets deprecated. Tests that find no regressions aren’t written. Developers who demand certain types of activity from testers have to participate in it. There are no make-work tasks. There is no busy work in an attempt to add value where you are not needed.

Hiring highly technical testers was only step one. We still needed to get developers involved. One of the key ways we did this was by a program called Test Certified. In retrospect, the program was instrumental in getting the developer-testing culture ingrained at Google.

If your teams have no visibility into code deployments—that is, if you ask your teams what software deployments are like and the answer is, “I don’t know . . . I’ve never thought about it!”—that’s another warning that software delivery performance could be low, because if developers or testers aren’t aware of the deployment process, there are probably barriers hiding the work from them.