Just like failing tests, flaky tests indicate that something might be wrong with the user-facing behavior of your product. It is important to track and fix them as soon as possible. Develocity 2020.2 features test analysis improvements that streamline test debugging and root cause identification.
Minimizing software build and test feedback cycles has several obvious positive effect on engineering behaviors. This article untangles the cause and effect relationship with other indirect benefits you may have not considered.
For most organizations, developer productivity engineering should no longer be viewed as an informal, reactive, and opportunistic job to be done by developers in their spare time. Here are the top 3 reasons why many high-profile dev organizations have long ago established dedicated DPE teams.
Dependency issues are frustrating. The rules are complex and without the right data, determining exactly what caused the issue can take time and energy. The new dependency visualization feature in build scans can help.
The Most Important Development in Software Engineering Since the Introduction Agile, Lean Software Development, and DevOps methodologies and Tools.
Does your team suffer from long feedback times because of slow running tests? Does your CI pipeline spend several hours executing integration and system tests?
Having these tests is important but once running them takes longer than a few minutes, developers will push execution to later stages of the development cycle leading to longer feedback times. Shortening feedback cycles can save teams lots of time because there are fewer interruptions to the creative process, developers spend less time waiting for each individual build, and they spend less time debugging problems that occur from compounding changesets.
Like many companies, the software development experience at Elastic was starting to become negatively impacted under the increasing strain of slowing builds and inefficient process for testing and debugging. And, the pain was only expected to increase in line with the growth of development teams, code bases, and repositories. The cost of inaction was projected to soon become unbearable.
In this webcast, Mark Vieira, Senior Software Engineer at Elastic discusses with Gradle, Inc. CEO, Hans Dockter, how Elastic overcame the natural resistance to change their process and toolset by quantifying the Cost of Inaction and blazing a new path toward build engineering excellence.
Do you hate flaky tests? If your application interacts with browsers, external services, or has asynchronous behavior, it’s likely your team has suffered from flaky tests.
Non-deterministic tests are a ruinous infection that wastes developer time and reduces confidence in your test suite.
A fast and efficient CI pipeline can make or break your team’s developer experience and productivity. But what are the biggest determinants of CI pipeline performance? How do CI platform infrastructure and build/test performance impact each other and where should you focus your efforts?
Flaky, or non-deterministic, tests are a serious and prevalent problem in modern software development. If your application interacts with browsers, external devices or services, or has asynchronous behavior, it’s likely you have suffered from flaky tests. Martin Fowler has this to say about flaky tests:
Non-deterministic tests have two problems, firstly they are useless, secondly they are a virulent infection that can completely ruin your entire test suite. As a result they need to be dealt with as soon as you can, before your entire deployment pipeline is compromised. — Martin Fowler on Eradicating Non-Determinism in Tests
Flaky tests compromise deployment pipelines by slowing them down and decreasing confidence in the correctness of changes. When changes regularly fail due to unrelated flaky tests, time is wasted, features are delayed, and developers are demotivated to make changes.
Accelerate
Troubleshoot
Observe
