Given the fast-paced world of software development, it can be difficult to know what is essential and what is just nice to have.
The pressures to ship software faster and meet deadlines are real, so it’s important for coders to find ways to streamline their process and cut down on wasted time.
If you’re working on a piece of software that uses artificial intelligence (AI) or machine learning, there are some additional considerations you’ll want to plan for. AI and ML both require different types of testing that may not be familiar if you haven’t worked with these concepts before.
In this blog post, we’ll go over the differences between smoke and sanity testing, what they each involve, and why they’re both important for your project moving forward.
What is Smoke Testing?
Smoke testing is a type of software testing that is used to identify major issues with software functionality as quickly as possible.
It is a general type of software testing used as a preliminary testing method during software development. A software smoke test is usually designed to exercise major functionality of an application, including critical software components and business processes, to determine if the application is even capable of working at all.
It is often the first type of testing applied when a new software product is in development, before more specific testing methods are developed.
A smoke test is typically high-level, checklist-based, and focused on the application’s requirements or specifications.
It is often used as an initial form of software quality assurance (QA) testing. Smoke testing is an important part of the software development life cycle because it identifies major issues with the software functionality that would otherwise go unnoticed until later in the development process when more thorough testing methods are applied.
What is Sanity Testing?
Sanity testing is a type of software testing used to ensure that the software being developed functions as expected and will be ready for more thorough testing.
A software sanity test is usually conducted during the early stages of software development and is meant to be low-level, checklist-based testing of the application’s critical features to ensure they are functioning as they should be before more specific testing methods are applied.
Sanity testing is often used as an initial form of software testing when there is a short timeframe to develop the application, and a limited amount of time to complete thorough, high-level testing. It is also used to determine if there are any major issues with the application that should be addressed before other more thorough testing methods are applied.
Why You Need Both
Even when you’re working with AI and ML, you’ll want to do some basic smoke and sanity testing to ensure that the coding is correct.
You’ll obviously want to make sure your algorithms are sound, but you also want to make sure all the smaller pieces are working correctly.
Because these types of testing are simpler and require less time to conduct, you’ll be able to catch issues early on and make adjustments before you move on to the more thorough testing methods.
If you skip the smoke and sanity testing steps, you risk unknowingly introducing errors into your code that could cause it to malfunction or produce incorrect results.
When you’re dealing with AI and ML algorithms, you also need to make sure that your testing scenarios are correct. If you use the wrong data, you may not get the results you want.
How to Perform Both Types of Testing
If you’re working with smoke and sanity testing on your AI or ML project, here are some tips on how best to proceed. – Choose Your Testing Scenarios Wisely – When you’re building your testing scenarios, be sure to include a wide variety of samples that cover many different situations.
For example, if you’re building a self-driving car, you’ll want to include samples from sunny days, rainy days, and foggy days.
If you’re designing a system that relies on ML to identify people in photos, you’ll want to include samples from people of different races, ages, and genders. – Use the Right Tools – If you’re building a system that relies on AI or ML, you’re probably testing your code in a programming language like Python or C++. So it’s important that you use testing tools that are designed for programming languages like these.
If you’re using Visual Studio, for example, you can use the built-in unit testing tools to create smoke and sanity tests that are tailored to your system.
Conclusion
Even when you’re working with AI and ML, you’ll want to do some basic smoke and sanity testing to ensure that the coding is correct.
It’s important to choose your testing scenarios wisely and use the right tools for the job. If you skip the smoke and sanity testing steps, you risk unknowingly introducing errors into your code that could cause it to malfunction or produce incorrect results.
