In modern software development, continuous delivery is a must. However, it is important to have a testing infrastructure set up to ensure your existing and main functionality retains normal operations despite new changes introduced.
This is where smoke testing comes in, or sometimes referred to as ‘Build Verification Testing’.
What is smoke testing?
Smoke testing is a software testing technique and form of regression test that helps to verify the stability of the recently deployed software build. It helps determine whether your new code has had any effect on your core functionality.
This type of test is usually carried out by QA engineers, who will determine the most important aspects of the software’s features. Whenever there is a new build, the QA team determines the major functionality in order to perform smoke testing. Then, this team will uncover any faults in the application functionality with the introduction of new code.
Surprisingly enough, the name comes from plumbing where a smoke test is carried out on pipelines to know whether they’re working or not. In this context, smoke is fed into pipes which helps verify that there are no leaks.
It has the same underlying purpose in software development by ensuring the stability of your major functionality whenever a new build is deployed.
In that sense, this test is the first testing method you should implement whenever new changes are introduced to your software to determine whether it is stable enough to go through further testing.
Thus, smoke testing occurs at the beginning of software development testing life cycle.
Implementation methods
Smoke testing can be done manually or through automation.
In the former case, the smoke tests are run manually each time a new feature is introduced while in the latter case, a set of automated tests is used allowing developers to check the build immediately.
However, some organizations may use a combination of manual and automated testing.
The process of smoke testing is pretty straightforward: first, builds are deployed by developers and sent to the testing team for testing.
Then, in the process of testing, if a bug is detected, it would fail the smoke test and this build is rejected; otherwise, if no major issues are uncovered, then the build can go on to further testing.
To build this test, you will need to determine which parts of your application constitute the major functionality. Afterward, automated tests can be set up to test these major parts.
Benefits
Smoke testing helps detect early issues and enables your team to locate any errors or bugs before it reaches your user-base. Thus, this type of testing ensures that any new features you’re releasing do not affect your existing functionality.
This instant feedback means you can make changes quickly before they are accessed by your users so you can fix any issues, saving both time and effort later on.
Smoke tests are usually quick and simple and show that the feature is ready for testing. This means smoke testing is usually done in production just as you’re about to release your new features.
Therefore, the major advantage to this test is the early detection of major errors thereby reducing risks when testing later on on your users. It also saves time and cost which would have been wasted on further testing with a faulty build.
Because this test targets key features, it can be a cost-effective way to detect major errors and software defects by ensuring that high-quality software is being built.
Without this test, major bugs will be left undetected and could prove to be a major obstacle as you go further in the testing process.
Conclusion
After looking at the benefits of smoke testing, it is clear that this type of testing is vital as it locates defects in early stages and so it increases the quality and stability of your application.
Therefore, you should be carrying out this test on any new build or changes to avoid finding these errors when it’s more risky and costly.
To sum up, smoke testing is a must to ensure build stability at an early stage so you can move on to the next stage in testing with less risk.
