What Is Smoke Testing? Your Complete Guide

Time is at a premium for today’s engineering teams. As the industry trends towards smaller teams and faster release cycles, ‘getting it right’ in this day and age involves finding the balance between the two. That isn’t easy. 

Understanding the role of smoke testing in software development, however, will help significantly. Rather than spending hours running full regression suites on a broken build, smoke testing provides a quick confidence check that core functionality still works.

This 101 guide gives you a need-to-know overview of the process. We’ll answer the big questions: ‘what is smoke testing?’, ‘when should I do it’, and more, and provide some tooling tips and best practices too. 

What Is Smoke Testing?

Smoke testing in software development is a quick, initial round of software testing that verifies the most critical functions of your app work after a new deployment. The idea is that, if these functions fail, there is no point continuing with further testing until they are resolved.

So, why ‘smoke’ testing? 

The term actually comes from hardware engineering processes. When engineers turned on a new device, they checked whether any smoke came out of any components before moving on to more detailed tests. 

Smoke testing your app is a similar concept. Smoke tests aren’t designed to uncover every defect; instead, they focus on cornerstone functionality such as: 

• Can the application launch successfully?
• Can users log in?
• Do main navigation menus work?
• Can core forms be submitted?
• Are APIs responding?
• Can transactions be completed?
• Are critical integrations connected?

Smoke tests are usually broad but shallow. They cover many important areas quickly without going into detailed edge cases.

Let’s say you’re releasing a new version of your e-commerce platform. A round of smoke testing should confirm that users can still browse products, add items to the basket, sign in, and complete checkout. If any of these functions fail, the build may be rejected immediately.

What Are the Advantages of Smoke Testing?

Smoke testing is a fast and effective way to quickly test key features, particularly if you’re working in a CI/CD environment, which demands constant iteration and continuous release cycles. 

Smoke Testing Stops You from Wasting Time

Smoke testing saves your team hours of wasted effort performing detailed tests on unstable builds. Checking the foundations first improves the reliability of further testing and ensures that any later effort is well-spent. 

Smoke Testing Supports Faster Delivery

In CI/CD pipelines, smoke tests act as a sort of quality gate, and that’s important when you’re releasing several times per week. Smoke tests allow you to up your release frequency while maintaining control and confidence. 

Smoke Testing Makes Defect Correction Faster and Cheaper

Fixing critical issues earlier is almost always cheaper than discovering them later in system testing or production. Finding and fixing critical defects at the smoke-test stage will save plenty of engineering hours that you can reinvest elsewhere. 

Smoke Testing Encourages Collaboration Across the Business

Smoke testing creates a shared checkpoint between development, QA, and operations teams. It’s an objective measure that allows everyone to agree on whether a release is ready to progress.

Smoke Testing in the Software Development Cycle: Where and Why? 

You should run smoke tests whenever your software changes in any meaningful way. This includes: 

After a New Build Is Created

Whenever engineers create a new build, smoke testing should confirm that the app installs and launches without issue, and that basic functions work correctly.

After Code Merges

When multiple branches are merged into a shared environment, use smoke testing for a quick, meaningful indication of any integration issues. 

Before Detailed Functional Testing

Smoke testing should happen before manual exploratory testing, regression testing, or performance testing so your team doesn’t waste time testing something that’s fundamentally broken. 

After Deployments

Once software is deployed to staging, pre-production, or production environments, a quick round of smoke tests allows you to double check there are no major functionality issues. 

After Infrastructure Changes

Changes to hosting environments, databases, cloud resources, or network configurations can create unexpected failures. Smoke tests help confirm everything still works properly after these updates. 

In CI/CD Pipelines

Many organisations automate smoke testing to run after every commit or deployment for rapid feedback and to prevent major issues from building up further down the line. 

Smoke Testing in Software Development: Comparison With Other Testing Types

Smoke testing is not a replacement for other testing methods; it’s an early checkpoint that helps teams decide whether more detailed testing should proceed.

Here’s how it sits with other types of testing, to give you an idea of the role it plays in the wider software development process.

Smoke Testing Best Practices

Focus on Business-Critical Journeys

Smoke testing should test fundamental, high-priority functions; choose your tests accordingly. You might want to focus on login, authentication, or purchase flows, for example. 

Keep It Fast

Smoke testing is a quick checkpoint, not an hours-long full execution of your test suite. If it takes any more than a few minutes, slim it down by prioritizing cornerstone functions. 

Automate Where Possible

Automating smoke tests in CI/CD pipelines ensures consistency, speed, and repeatability. And, it saves your engineering team time that they can dedicate to other tasks with more business value. 

Maintain Test Cases Regularly

Your test suite should evolve with your app. Set time aside to review your test suite, remove outdated tests, and add new ones for critical functionality. 

Audits take up valuable engineer time and, being blunt, no one enjoys doing them. AI can help – see below for details. 

Use Clear Pass/Fail Criteria

Define exactly what constitutes a failed smoke test. This prevents confusion and helps teams make release decisions quickly.

Run in Realistic Environments

Where possible, execute smoke tests in environments that mirror production to help catch configuration and deployment issues.

Smoke Testing and AI: The Perfect Combo? 

Smoke testing in software development is meant to be quick. It’s a checkpoint that makes sure nothing has really gone wrong before you dive into the details. 

In other words, the faster the better. This is not an area where you should be wasting valuable engineering hours, if you can help it. In other words, it’s the perfect candidate for automation.

Using traditional automation techniques here will save you some time. Using AI, however, will accelerate things much more steeply and nearly eradicate the maintenance burden associated with smoke testing in software development. Here’s how: 

Intelligent Test Selection

AI tools can analyze code changes and identify which smoke tests are most relevant to run on any given release. This cuts execution overheads by adapting your test suite to the release in question. 

Self-Healing Test Automation

Traditional automated tests often fail when UI elements change slightly. If you’ve moved a button a few pixels to the left, then spent valuable time fixing subsequent broken tests, you’ll know the struggle. 

AI-powered testing tools use smart, intent-based locators to update tests automatically, which is an absolute game-changer when it comes to saving engineering hours and reducing bottlenecks. 

Predictive Risk Analysis

AI systems can examine historical defects, deployment data, and code complexity to predict where failures are most likely. Your team can then strengthen smoke coverage in high-risk areas, contributing to better overall software quality. 

Faster Failure Diagnosis

When smoke tests fail, AI can analyze logs, screenshots, and other data to flag probable root causes. Faster failure diagnosis = faster fixes, and faster releases overall. 

Natural Language Test Creation

AI platforms like Momentic allow you to describe smoke scenarios in plain English, then generate automated scripts. This is both much faster than any other method and allows non-technical team members to contribute where needed. 

Continuous Optimization

AI gets smarter the more it tests. Over time, AI testing tools can learn which smoke tests provide the highest value, identify gaps in coverage, and recommend improvements to your smoke testing suite. 

Momentic: Smart, AI-Native Smoke Testing Automation

“With Momentic, we’ve caught bugs that would have eluded even our most diligent internal tests.”
Alex Cui (Co-Founder and CTO at GPT Zero)

Using Momentic, the team at GPT Zero saw an 89% decrease in defect escape rate. 

They also saw an 80% acceleration in release cycles, thanks to time savings realized through natural language test creation and self-healing tests. 

Want to join them? Get a demo today