Introduction to Google Software Testing
- Quality ≠ Test
- Organizational Structure
- Crawl, Walk, Run
- Types of Tests
There is one question I get more than any other. Regardless of the country I am visiting or the conference I am attending, this one question never fails to surface. Even Nooglers ask it as soon as they emerge from new-employee orientation: “How does Google test software?”
I am not sure how many times I have answered that question or even how many different versions I have given, but the answer keeps evolving the longer time I spend at Google and the more I learn about the nuances of our various testing practices. I had it in the back of my mind that I would write a book and when Alberto, who likes to threaten to turn testing books into adult diapers to give them a reason for existence, actually suggested I write such a book, I knew it was going to happen.
Still, I waited. My first problem was that I was not the right person to write this book. There were many others who preceded me at Google and I wanted to give them a crack at writing it first. My second problem was that I as test director for Chrome and Chrome OS (a position now occupied by one of my former directs) had insights into only a slice of the Google testing solution. There was so much more to Google testing that I needed to learn.
At Google, software testing is part of a centralized organization called Engineering Productivity that spans the developer and tester tool chain, release engineering, and testing from the unit level all the way to exploratory testing. There are a great deal of shared tools and test infrastructure for web properties such as search, ads, apps, YouTube, and everything else we do on the Web. Google has solved many of the problems of speed and scale and this enables us, despite being a large company, to release software at the pace of a start-up. As Patrick Copeland pointed out in his preface to this book, much of this magic has its roots in the test team.
When Chrome OS released in December 2010 and leadership was successfully passed to one of my directs, I began getting more heavily involved in other products. That was the beginning of this book, and I tested the waters by writing the first blog post,1 “How Google Tests Software,” and the rest is history. Six months later, the book was done and I wish I had not waited so long to write it. I learned more about testing at Google in the last six months than I did my entire first two years, and Nooglers are now reading this book as part of their orientation.
This isn’t the only book about how a big company tests software. I was at Microsoft when Alan Page, BJ Rollison, and Ken Johnston wrote How We Test Software at Microsoft and lived first-hand many of the things they wrote about in that book. Microsoft was on top of the testing world. It had elevated test to a place of honor among the software engineering elite. Microsoft testers were the most sought after conference speakers. Its first director of test, Roger Sherman, attracted test-minded talent from all over the globe to Redmond, Washington. It was a golden age for software testing.
And the company wrote a big book to document it all.
I didn’t get to Microsoft early enough to participate in that book, but I got a second chance. I arrived at Google when testing was on the ascent. Engineering Productivity was rocketing from a couple of hundred people to the 1,200 it has today. The growing pains Pat spoke of in his preface were in their last throes and the organization was in its fastest growth spurt ever. The Google testing blog was drawing hundreds of thousands of page views every month, and GTAC2 had become a staple conference on the industry testing circuit. Patrick was promoted shortly after my arrival and had a dozen or so directors and engineering managers reporting to him. If you were to grant software testing a renaissance, Google was surely its epicenter.
This means the Google testing story merits a big book, too. The problem is, I don’t write big books. But then, Google is known for its simple and straightforward approach to software. Perhaps this book is in line with that reputation.
How Google Tests Software contains the core information about what it means to be a Google tester and how we approach the problems of scale, complexity, and mass usage. There is information here you won’t find anywhere else, but if it is not enough to satisfy your craving for how we test, there is more available on the Web. Just Google it!
There is more to this story, though, and it must be told. I am finally ready to tell it. The way Google tests software might very well become the way many companies test as more software leaves the confines of the desktop for the freedom of the Web. If you’ve read the Microsoft book, don’t expect to find much in common with this one. Beyond the number of authors—both books have three—and the fact that each book documents testing practices at a large software company, the approaches to testing couldn’t be more different.
Patrick Copeland dealt with how the Google methodology came into being in his preface to this book and since those early days, it has continued to evolve organically as the company grew. Google is a melting pot of engineers who used to work somewhere else. Techniques proven ineffective at former employers were either abandoned or improved upon by Google’s culture of innovation. As the ranks of testers swelled, new practices and ideas were tried and those that worked in practice at Google became part of Google and those proven to be baggage were jettisoned. Google testers are willing to try anything once but are quick to abandon techniques that do not prove useful.
Google is a company built on innovation and speed, releasing code the moment it is useful (when there are few users to disappoint) and iterating on features with early adopters (to maximize feedback). Testing in such an environment has to be incredibly nimble and techniques that require too much upfront planning or continuous maintenance simply won’t work. At times, testing is interwoven with development to the point that the two practices are indistinguishable from each other, and at other times, it is so completely independent that developers aren’t even aware it is going on.
Throughout Google’s growth, this fast pace has slowed only a little. We can nearly produce an operating system within the boundaries of a single calendar year; we release client applications such as Chrome every few weeks; and web applications change daily—all this despite the fact that our start-up credentials have long ago expired. In this environment, it is almost easier to describe what testing is not—dogmatic, process-heavy, labor-intensive, and time-consuming—than what it is, although this book is an attempt to do exactly that. One thing is for sure: Testing must not create friction that slows down innovation and development. At least it will not do it twice.
Google’s success at testing cannot be written off as owing to a small or simple software portfolio. The size and complexity of Google’s software testing problem are as large as any company’s out there. From client operating systems, to web apps, to mobile, to enterprise, to commerce and social, Google operates in pretty much every industry vertical. Our software is big; it’s complex; it has hundreds of millions of users; it’s a target for hackers; much of our source code is open to external scrutiny; lots of it is legacy; we face regulatory reviews; our code runs in hundreds of countries and in many different languages, and on top of this, users expect software from Google to be simple to use and to “just work.” What Google testers accomplish on a daily basis cannot be credited to working on easy problems. Google testers face nearly every testing challenge that exists every single day.
Whether Google has it right (probably not) is up for debate, but one thing is certain: The approach to testing at Google is different from any other company I know, and with the inexorable movement of software away from the desktop and toward the cloud, it seems possible that Google-like practices will become increasingly common across the industry. It is my and my co-authors’ hope that this book sheds enough light on the Google formula to create a debate over just how the industry should be facing the important task of producing reliable software that the world can rely on. Google’s approach might have its shortcomings, but we’re willing to publish it and open it to the scrutiny of the international testing community so that it can continue to improve and evolve.
Google’s approach is more than a little counterintuitive: We have fewer dedicated testers in our entire company than many of our competitors have on a single product team. Google Test is no million-man army. We are small and elite Special Forces that have to depend on superior tactics and advanced weaponry to stand a fighting chance at success. As with military Special Forces, it is this scarcity of resources that forms the base of our secret sauce. The absence of plenty forces us to get good at prioritizing, or as Larry Page puts it: “Scarcity brings clarity.” From features to test techniques, we’ve learned to create high impact, low-drag activities in our pursuit of quality. Scarcity also makes testing resources highly valued, and thus, well regarded, keeping smart people actively and energetically involved in the discipline. The first piece of advice I give people when they ask for the keys to our success: Don’t hire too many testers.
How does Google get by with such small ranks of test folks? If I had to put it simply, I would say that at Google, the burden of quality is on the shoulders of those writing the code. Quality is never “some tester’s” problem. Everyone who writes code at Google is a tester, and quality is literally the problem of this collective (see Figure 1.1). Talking about dev to test ratios at Google is like talking about air quality on the surface of the sun. It’s not a concept that even makes sense. If you are an engineer, you are a tester. If you are an engineer with the word test in your title, then you are an enabler of good testing for those other engineers who do not.
Figure 1.1 Google engineers prefer quality over features.
The fact that we produce world-class software is evidence that our particular formula deserves some study. Perhaps there are parts of it that will work in other organizations. Certainly there are parts of it that can be improved. What follows is a summary of our formula. In later chapters, we dig into specifics and show details of just how we put together a test practice in a developer-centric culture.
Quality ≠ Test
“Quality cannot be tested in” is so cliché it has to be true. From automobiles to software, if it isn’t built right in the first place, then it is never going to be right. Ask any car company that has ever had to do a mass recall how expensive it is to bolt on quality after the fact. Get it right from the beginning or you’ve created a permanent mess.
However, this is neither as simple nor as accurate as it sounds. Although it is true that quality cannot be tested in, it is equally evident that without testing, it is impossible to develop anything of quality. How does one decide if what you built is high quality without testing it?
The simple solution to this conundrum is to stop treating development and test as separate disciplines. Testing and development go hand in hand. Code a little and test what you built. Then code some more and test some more. Test isn’t a separate practice; it’s part and parcel of the development process itself. Quality is not equal to test. Quality is achieved by putting development and testing into a blender and mixing them until one is indistinguishable from the other.
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.
This means that quality is more an act of prevention than it is detection. Quality is a development issue, not a testing issue. To the extent that we are able to embed testing practice inside development, we have created a process that is hyper-incremental where mistakes can be rolled back if any one increment turns out to be too buggy. We’ve not only prevented a lot of customer issues, we have greatly reduced the number of dedicated testers necessary to ensure the absence of recall-class bugs. At Google, testing is aimed at determining how well this prevention method works.
Manifestations of this blending of development and testing are inseparable from the Google development mindset, from code review notes asking “where are your tests?” to posters in the bathrooms reminding developers about best-testing practices.3 Testing must be an unavoidable aspect of development, and the marriage of development and testing is where quality is achieved.