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How a Test Strategy Helped to Increase Deployment Maturity and Product Quality
Implementing a test strategy helped an organization to move away from push and pray deployment toward continuous and confident deployment to production. The organization mapped their test strategy in a framework with different enablers, which has helped them align on quality metrics for the whole product together with a strong safety net of tests before moving to production.
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The Manual Regression Testing Manifesto
Automating regression tests isn’t always the best solution, argued Brendan Connolly at the 2018 fall Online Testing Conference. He presented the “manual regression testing manifesto” and showed how it can be used to differentiate feature testing from regression testing and to decide when to automate or not automate tests.
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Continuous Integration at Intel for the Mesa Graphics Library
Mesa CI is a continuous integration system at Intel for running builds and compliance test suites for the Mesa graphics library. It runs across more than 200 systems and runs tens of millions of tests per day.
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Continuous Deployment at Coolblue
Continuous deployment results in a higher sense of responsibility and better quality of deployments, argues Paul de Raaij, technical pathfinder at Coolblue. Coding standards prevent your code base from becoming a mess, automated inspections are great for tedious and boring checks, and manual checks are great for checking if the logic or use of code actually makes sense.
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Improving Quality and Delivery Speed with DevOps Teams
You can increase the quality of products by constantly increasing the level of automation of the delivery process and working with DevOps teams who constantly deliver small features to get quick customer feedback. A case story from ING Lease explaining the problems they had, experiences from the first steps of their agile and DevOps journey and exploring what they want to achieve in the future.
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Failure Injection Testing: Controlling Failure in Production
Netflix's Failure Injection Testing bridges the gap between isolated testing and unmitigated chaos testing by controlling the impact of the test. FIT establishes a context which other components of Netflix's production testing and infrastructure systems interpret and adjust the behavior of the system accordingly.