
How Google Tests Software

importance of the code and the care that engineers take when modifying it.
Jason Arbon • How Google Tests Software
We also automate the submission of bug reports and the routing of manual testing tasks.7 For example, if an automated test breaks, the system determines the last code change that is the most likely culprit, sends email to its authors, and files a bug automatically. The ongoing effort to automate to within the “last inch of the human mind” is curren
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The simple solution to this conundrum is to stop treating development and test as separate disciplines. Testing and development go hand in hand.
Jason Arbon • How Google Tests Software
“quality is not important until the software is important.”
Jason Arbon • How Google Tests Software
Instead of distinguishing between code, integration, and system testing, Google uses the language of small, medium, and large tests
Jason Arbon • How Google Tests Software
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
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“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 mes
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Google tries hard to develop only products that users will find compelling and to get new features out to users as early as possible so they might benefit from them. Plus, we avoid over-investing in features no user wants because we learn this early.
Jason Arbon • How Google Tests Software
One of the key ways Google achieves good results with fewer testers than many companies is that we rarely attempt to ship a large set of features at once. In fact, the exact opposite is the goal: Build the core of a product and release it the moment it is useful to as large a crowd as feasible, and then get their feedback and iterate.