Table Of Contents
- What is smoke testing in software testing?
- What are the features of smoke testing?
- What are the types of smoke tests?
- What is a smoke testing cycle?
- When to perform the QA smoke tests?
- How to plan a QA smoke test
- How to perform a QA smoke test
- Smoke test vs. Sanity test
- What are the advantages of smoke testing?
- What are the tools used for smoke testing?
- QA Smoke test examples
- What are the latest AI trends for smoke tests?
- Conclusion
The phrase “smoke test” was lifted from the construction industry. During this test, water pipelines would be filled with smoke to see if there were any leaks and other underlying issues.
In the tech industry, smoke tests were first used for hardware testing, where hardware boards were tested to see if they would smoke once plugged in and turned on. If they did emit smoke, they would fail the tests and were immediately unplugged. If they didn’t, they’d move on to the next round of testing.
Smoke testing plays a similar role in software development and quality assurance, albeit without the literal smoke. With the rise of Artificial intelligence, smoke tests are now faster and more efficient. AI automates test case selection, optimizes execution, and provides instant analysis, helping detect critical issues early. This streamlines the process, saving time and resources.
What is Smoke Testing in Software Testing?
It is a crucial part of developing applications and quality assurance. It is the first line of defense against faulty code in initial software builds. Smoke tests aren’t used to debug builds; they are used to find out whether the builds are working in the first place.
Unlike other QA tests that are exhaustive and check the overall code, smoke tests are fast and targeted. They are used to test new builds and ensure that the core or critical functions of the written program are working properly.
If any of the key features or functions of the software aren’t working, then the build is immediately rejected or redone. Testing only the main functionalities of the software helps save time, effort, and costs. In short, smoke tests can help improve your return on investment in the product.
After all, if there is an error with the critical areas of the build, it would be a waste of time to check its other, less important functions. It would also be a waste to continue working on the current build.
What if it passes?
- Comprehensive testing can begin.
- Developers can confidently move on to adding features or fixing minor issues.
- The build can be shared with the client or stakeholders for initial feedback.
What if it fails?
- The development team needs to fix the issues promptly.
- Testing on the build is paused to avoid wasting time on faulty code.
- A new build must be generated for retesting before further quality assurance efforts can continue.
What are the Features of Smoke Testing?
It is also called build verification testing or build acceptance testing. The tests verify whether the main functions of the initial build are working accurately. Based on the results, the build may be accepted for the next series of QA tests or rejected altogether.
Smoke tests are sometimes also referred to as intake tests, as they decide the next round of testing. There are several aspects involved in smoke testing. These aspects or features differentiate it from other types of QA tests.
Some of the key features of smoke testing are as follows:
- Scope: A software system's important features and functionalities are the main focus of smoke testing. It tries to rapidly pinpoint significant problems or flaws that can obstruct future testing or production deployment.
- Rapid Execution: Smoke tests are designed to be executed quickly, providing a high-level assessment of the application's stability and readiness for further testing. It helps identify showstopper issues early on.
- Minimal Documentation: It does not require extensive documentation. It typically involves a predefined set of test cases or scenarios that cover the core functionalities of the application without going into detailed testing.
- No Detailed Validation: It does not concentrate on thoroughly validating each feature or scenario. It seeks to rapidly verify the application's overall stability and identify any major issues or failures that require immediate attention.
- Focused on Stability: The main objective of this type of testing is to ensure the overall stability of the software. It helps identify critical defects that might prevent further testing or deployment.
What are the Types of Smoke Tests?
Developers and QA engineers can conduct this type of testing in three ways. The type of smoke test used may depend on the builds you need to test, time constraints, or your preference.
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Manual tests
This is the most common type of testing. This method tests each initial build or any new features added to existing builds. You must modify or update your test scripts based on each requirement using the manual method. In some cases, you may need to create entirely new scripts.
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Automated tests
Automation smoke testing allows you to test batches of initial builds. Using an automation tool for this type of testing is ideal when you have limited time before build deployment.
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Hybrid tests
As their name suggests, hybrid tests are a mix of both manual and automated smoke tests. Combining the two types can boost the overall performance of the testing.
What is a Smoke Testing Cycle?
A smoke testing cycle refers to the entire process that QA teams follow to validate whether a new software build is stable enough for further testing. It involves predefined steps to ensure the build’s most critical functionalities work as expected before more profound and exhaustive testing begins. It involves the following key steps:
- Build Creation: Developers create a new build after implementing features or fixes.
- Test Case Selection: QA teams select a small set of essential test cases targeting core functionalities.
- Execution of Smoke Tests: These test cases are run to check the basic stability of the build.
- Result Analysis: Results are reviewed to determine if the build is stable or requires fixing.
- Report Generation: A brief report is created to highlight any issues found during testing.
- Build Acceptance or Rejection: If the build passes, it proceeds to more detailed testing; if it fails, it is returned for fixes.
When to Perform the QA Smoke Tests?
Smoke tests are typically performed at specific points in the software development lifecycle to quickly assess whether a build or release is stable enough for further testing or deployment. Here are some common scenarios when you should perform smoke tests:
- After Every Build: In a continuous integration (CI) or continuous delivery (CD) environment, smoke tests can be triggered automatically after each build. This ensures that basic functionality is intact before the build progresses to more extensive testing phases.
- Before Integration Testing: Before integrating new code changes into the main codebase, performing smoke tests can catch any glaring issues early. This ensures that the integration process starts with a stable foundation.
- Before Major Testing Phases: Before starting more comprehensive testing phases such as regression testing, user acceptance testing (UAT), or performance testing, it's a good practice to perform smoke tests. This prevents wasting time on tests if the build is fundamentally broken.
- Before Manual Testing: If manual testers are involved, they can begin their testing efforts with a smoke test. This ensures they are not spending time on deeper testing if the build is unstable.
- Before Deploying to Staging or Pre-production: Before promoting a build to staging or pre-production environments, conducting smoke tests helps verify that the build is stable enough for further testing by different teams.
- Before Critical Releases: When preparing for critical releases or deployments to production, performing smoke tests is essential. It helps prevent major issues from reaching the production environment.
- After Hotfixes or Emergency Changes: After applying hotfixes or emergency patches, running smoke tests can verify that the critical functionality affected by the changes is still working as expected.
- After Environment Changes: If there have been significant changes to the underlying environment, such as infrastructure updates or configuration changes, running smoke tests can ensure that the application functions properly in the new environment.
- After Code Merges: When code branches are merged, especially in version control systems like Git, running smoke tests on the merged codebase can identify any conflicts or issues introduced during the merge.
- Before Demonstrations or Reviews: If you're preparing to showcase the application to stakeholders and clients or during code reviews, conducting smoke tests ensures that obvious bugs will not mar the demo.
The timing of smoke tests depends on your development process, team structure, and application criticality. Ideally, smoke tests should be automated and integrated into your CI/CD pipeline to provide rapid feedback and reduce the risk of faulty code moving forward in the development lifecycle.
How to Plan a QA Smoke Test
A smoke test may be manual, automated, or a mix of the two. Regardless of the type of smoke test you choose, the planning stage remains the same.
Here are some key tips for planning and running a smoke test:
- Prepare for testing: Make sure to set the preferred atmosphere for the smoke test. This involves preparing any files, servers, and licenses you may need for the test. Create copies of your files and build as well, so you have backups in case anything happens.
- Collect all necessary files: Get all the build or code files you will need for the test.
- Write a test script: Use a single script to run the tests. Moreover, ensure that your script is written so that it creates and saves a report after each test. This way, any build failures can be adequately and accurately reported to the developers.
- Clean data: Ensure your test runs in a clean environment. Remove any extraneous files that may affect the smoke test. This also includes stopping the server and emptying database tables.
How to Perform a QA Smoke Test
Step 1: Prepare the Build
Ensure the latest software build is ready for testing, incorporating all new features or fixes.
Step 2: Identify Critical Test Cases
Select a small number of high-priority test cases focusing on the core functionalities of the application (e.g., login, basic navigation).
Step 3: Set Up the Test Environment
Make sure the test environment is configured to match the production environment closely.
Step 4: Execute Smoke Tests
Run the identified smoke test cases to verify that the essential functionalities are working quickly.
Step 5: Analyze Test Results
Review the results to identify any failures or issues with the critical functions of the build.
Step 6: Generate a Report
Create a brief report summarizing the results of the smoke test, highlighting any errors or critical issues.
Step 7: Decide on Build Stability
If the smoke tests pass, proceed with further testing. If they fail, return the build to the development team for fixes.
Smoke Test vs. Sanity Test
Sanity testing is a subset of regression testing. Its features are similar to QA smoke testing, with one key difference.
Both tests are conducted quickly and efficiently. However, a smoke test is done on an entirely new build. A sanity test is done on an existing build with new features added or corrected functionalities. Sanity tests are often performed on builds that have already passed the initial smoke tests. These builds are then modified or restored after a series of tests. As such, parts of the build are already stable, and only the new functionalities must undergo QA.
| Smoke Testing | Sanity Testing |
|---|---|
|
Checks that critical functionalities or features of new builds are working acceptable |
Checks for new functionalities added to existing builds or corrected bugs |
|
Tests the basic end to end features of the system |
Tests only a specific component in the system |
|
Verifies the build or system stability before more rigorous testing |
Verifies the rationality and originality of the system before more rigorous testing |
|
A subset of acceptance testing |
A subset of regression testing |
|
Often documented and scripted |
Not written and scripted |
|
This may be done on both stable and unstable builds |
Only done on relatively stable builds or applications |
|
Conducted by developers and testers |
Conducted by testers or users |
What are the Advantages of Smoke Testing?
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Early Issue Detection
QA Smoke tests are designed to catch critical issues early in the development cycle. By quickly verifying if the core functionalities of the application work as expected, smoke tests help identify major defects soon after changes are made, reducing the chances of these issues propagating further.
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Quick Feedback
Smoke tests provide immediate feedback to developers after code changes are made. This quick feedback loop accelerates the development process and allows developers to address issues before they become more complex and time-consuming to fix.
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Reduced Regression Risk
Smoke tests help mitigate the risk of introducing regressions when new features or changes are added by ensuring that basic functionalities are intact. This allows development teams to focus on more in-depth testing and innovation.
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Integration Verification
Smoke tests can be used to verify that different modules, components, or services of an application integrate correctly. This is particularly important in complex systems or microservices architectures.
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Streamlined Development Pipeline
Automated smoke tests can seamlessly integrate into the CI/CD pipeline, automatically validating code changes and promoting a more efficient and reliable development process.
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Faster Time-to-Market
Detecting showstopper issues early prevents delays in the development process. With smoke tests, releases can be made more confidently, leading to faster deployment and time-to-market for new features and updates.
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Resource Efficiency
Smoke tests save time and resources compared to running exhaustive test suites by focusing on the most critical functionalities. This is particularly beneficial during the initial stages of testing.
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Quality Assurance
Smoke tests contribute to the overall quality assurance process as a gatekeeper, ensuring that only stable and functional code moves forward in the development lifecycle.
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Documentation of Basic Functionality
Smoke tests serve as documentation by outlining the essential features and behaviors expected to work consistently. This aids in maintaining a clear understanding of the application's core functions.
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Support for Agile Practices
In Agile development environments, where frequent iterations and changes occur, smoke tests align well with the Agile principles of continuous feedback, collaboration, and iterative development.
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Risk Reduction in Production
By catching major issues early, smoke tests help reduce the risk of deploying faulty code to production environments, enhancing the application's stability and reliability.
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Enhanced Communication
Smoke tests provide a common ground for communication between development, testing, and business teams. The tests define a baseline of expected behavior that everyone can agree upon.
What are the Tools Used for Smoke Testing?
Here are some tools that were commonly used for writing smoke tests:
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Selenium
Selenium is a widely used tool for automating web browsers. It supports various programming languages like Java, Python, and C#. You can create smoke tests by automating interactions with web applications and verifying that critical functions are working as expected.
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Cypress
Cypress is a modern end-to-end testing framework specifically designed for web applications. It provides an easy-to-use API for writing smoke and other tests. Cypress offers real-time reloading, time-travel debugging, and an interactive test runner.
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JUnit/TestNG
These are popular testing frameworks for Java applications. They provide a way to write and execute tests, including smoke tests. You can create simple and quick smoke tests using these frameworks.
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PyTest
PyTest is a testing framework for Python applications. It's known for its simplicity and extensibility. You can write smoke tests using PyTest to ensure critical parts of your Python application are working.
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Postman
Postman is widely used for API testing. You can create smoke tests for your APIs by sending requests and verifying responses. Postman offers a user-friendly interface for constructing API calls and assertions.
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Jest
Jest is a JavaScript testing framework commonly used to test JavaScript applications, particularly in the context of React applications. You can write smoke tests to ensure that components render and behave correctly.
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SoapUI
If you're dealing with web services and APIs, SoapUI is a tool that allows you to create and execute smoke tests for SOAP and RESTful APIs. It offers a range of testing features, including assertions and data-driven testing.
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Robot Framework
Robot Framework is a generic automation framework that supports both web and API testing. It uses a keyword-driven approach and supports multiple test libraries. You can use it to create smoke tests for various types of applications.
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Gatling
Gatling is a performance testing tool that can also be used to create smoke tests. It's particularly suited for testing web application performance and load-handling capabilities.
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Jenkins/Travis CI/CircleCI
While not directly for writing smoke tests, these continuous integration (CI) tools can be used to automate the execution of your smoke tests as part of your development pipeline.
The "best" tool can vary based on your specific use case, programming language, and technology stack. Always evaluate the tool's features, community support, and compatibility with your project before making a choice.
QA Smoke Test Examples
Here are a few common scenarios where smoke testing is used to validate the critical functionalities of software builds:
Example 1: eCommerce Application
Scenario: A new build of an e-commerce website is released with updates to the checkout process.
Smoke Test: Verify that users can:
- Add items to the shopping cart.
- Proceed to checkout.
- Make payments successfully.
Purpose: To ensure the critical path (shopping and payment) functions before running in-depth tests on features like product search or user profile management.
Example 2: Mobile Banking App
Scenario: A mobile banking app has received a new build with updates to the login process and fund transfer feature.
Smoke Test: Check that:
- Users can log in securely with their credentials.
- Funds can be transferred between accounts.
Purpose: Validate core financial functions before testing less critical features like viewing transaction history or updating contact details.
Example 3: SaaS Platform
Scenario: A SaaS platform releases a new version with updates to user authentication and file upload features.
Smoke Test: Confirm that:
- Users can sign up and log in successfully.
- Files can be uploaded without errors.
Purpose: To ensure key functionality (user access and file handling) works correctly before moving on to more detailed performance or security testing.
Example 4: Healthcare Management System
Scenario: A healthcare management system has a new build that includes updates to patient data entry and appointment scheduling features.
Smoke Test: Test that:
- Patient records can be created and saved.
- Appointments can be scheduled without issues.
Purpose: Validate the system’s ability to handle core functions before checking features like report generation or analytics.
What are the Latest AI Trends for Smoke Tests?
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Shift-left Testing and DevOps
The shift-left approach has been further enhanced by AI integration, allowing smoke tests to be embedded even earlier in the development pipeline. AI helps identify which tests to run at which stages, optimizing the development workflow and ensuring critical bugs are detected as early as possible.
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Microservices and API Testing
With the rise of microservices and API-driven architectures, AI tools are helping to automate and optimize API smoke tests. AI assists in generating test cases, ensuring robust coverage of API endpoints, and quickly identifying issues within individual services without needing to test the entire system.
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Automation and Continuous Integration
AI helps automate smoke tests within CI/CD pipelines by dynamically adjusting the testing scope based on changes made to the codebase. This ensures that every code push is immediately tested, with AI highlighting areas that may need further investigation, reducing manual intervention.
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Containerization and Kubernetes
As containerization and orchestration platforms like Kubernetes gained popularity, testing strategies needed to adapt. Smoke testing of containerized applications and their deployment pipelines became crucial.
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Shift to Headless and Cross-Browser Testing
AI can significantly improve headless and cross-browser smoke testing by identifying patterns across different platforms and environments. AI-based tools automate the selection of key test cases and adapt them for different devices and browsers, ensuring comprehensive smoke tests across a variety of scenarios.
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Focus on Performance and Security
AI is now integrated into smoke testing tools to perform essential performance and security checks during initial tests. AI-driven performance monitoring tools analyze system responsiveness during smoke tests, while AI security tools flag potential vulnerabilities that could disrupt core functionalities.
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AI and Test Automation
AI transforms how smoke tests are automated, enabling smarter test selection, execution, and analysis. AI-driven tools can prioritize test cases based on historical data, predicting which areas are most likely to fail, thus reducing unnecessary tests and accelerating the smoke testing process.
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Collaboration and Communication
AI tools streamline team communication by generating detailed, actionable insights from smoke tests. These AI-generated reports are concise, highlighting areas of concern for developers and offering automated suggestions for addressing issues.
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Cloud Testing Services
AI-driven cloud testing services are growing in popularity, allowing teams to execute smoke tests on multiple environments simultaneously. AI tools help distribute the tests across different cloud platforms, ensuring faster, more scalable testing without requiring extensive local infrastructure.
Conclusion
Quality assurance is a vital step during the software development life cycle. You can’t put just anybody in charge if you want to get favorable results and high-quality builds. The people in control of your QA process need more than training — experience and dedication.
That is precisely what QASource offers. We deliver high-quality QA outsourcing services to all our clients. Our team consists of the top technical talent with years of experience. We work closely with our clients to provide customized solutions, time-bound delivery, and an extensive range of quality assurance services — all at affordable costs.
