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Sanity testing is a targeted testing activity performed after smoke testing to verify that recent updates have not introduced unexpected issues. Its purpose is to ensure that core functionality still behaves correctly before you move on to deeper, more comprehensive testing.
In this article, you’ll get a clear understanding of what sanity testing is, how it works, and why it plays an important role in maintaining software reliability.
What is Sanity Testing?
Sanity testing is a focused type of software testing performed after smoke testing to confirm that recent changes, bug fixes, or small enhancements have not caused new problems. The goal is to quickly check that the affected functionality still works as expected before you invest time in broader testing.
Also known as surface-level testing, sanity testing is carried out on a stable build that has already passed smoke testing. It involves quick, targeted checks that verify whether the updated or impacted areas of the application function correctly. Because it only evaluates specific parts of the system, sanity testing is considered a subset of regression testing and helps you validate recent modifications without running a full test suite.
Characteristics of Sanity Testing
Here are the key characteristics of sanity testing:
- Targeted validation: Sanity testing lets you focus on the exact features affected by a recent update or fix. Instead of checking the entire system, you look only at the modified areas to confirm the change works correctly and has not caused unintended side effects nearby.
- Quick confirmation: This testing is designed to give you fast reassurance. You run a small number of checks to confirm that the updated feature is stable enough for further testing. It helps you catch obvious issues early without spending unnecessary time on deeper testing cycles.
- Post-fix testing: Sanity testing happens only on a stable build that includes minor updates or bug fixes. Since the build already passed smoke testing, you know the core system is functional. Your job is to confirm that the recent changes behave as expected before broader regression testing begins.
- Stopgate mechanism: If a sanity test fails, you stop immediately. There is no need to continue testing because the build is not ready. You return it to the development team with details, saving the entire team from wasting time testing a broken build.
Sanity Testing vs. Smoke Testing
- Smoke testing checks the most essential and foundational features of the system. If these core features work, the build is considered stable enough for further testing. If they fail, the build is rejected and sent back to the development team.
- Sanity testing works similarly but is far more focused. Instead of checking the entire system, you test only the modules affected by a recent fix or update to make sure the change actually solved the problem and didn’t break anything related.
Here's a more intuitive comparison:
- Smoke testing is like turning on a new device to see if it powers up and shows the main screen. You are only checking the absolute basics. If those basics work, you know the system is stable enough to start deeper testing. If something fails at this stage, there is no point going further, and the build goes straight back to the developers.
- Sanity testing is more like checking whether a specific button works after the developers fix something. Instead of testing the whole system, you look only at the part that was changed. You want to confirm that the fix actually works and did not break anything nearby. It is a quick check that helps you stay confident the system is still behaving correctly after a small update.
Here's a simple comparison table:
| Aspect | Smoke Testing | Sanity Testing |
|---|---|---|
| Objective | Build verification | Fix/enhancement validation |
| Scope | Broad (entire build) | Narrow (specific modules) |
| Timing | After every new build | After targeted fixes or changes |
| Approach | High-level | In-depth for specific changes |
| Execution | Often automated | Typically manual |
Read More: Sanity Testing vs Smoke Testing: A Detailed Comparison
Sanity Testing vs. Regression Testing
The differences between sanity testing and regression testing is even harder to define. They are both tests done after a fix or update happens.
The biggest difference is their scope: sanity testing only targets specific fixes, while regression testing ensures overall application stability after updates. Sanity is quick; regression is comprehensive.
Here's a more intuitive comparison:
- Sanity testing is like checking a single button or feature right after developers fix something. You focus only on the area that was changed. The goal is to make sure the fix works as expected and did not cause any obvious new issues. It is quick, narrow, and meant to give you confidence that the updated feature is stable enough to move forward.
- Regression testing, on the other hand, is like checking the entire control panel to make sure nothing else was affected by the recent change. When developers modify one part of the system, there is always a chance other features might break without anyone noticing. Regression testing helps you look back at previously working functionality and verify it still behaves correctly. It is broader, more thorough, and designed to catch side effects across the full system.
Here's a simple table to compare sanity testing vs regression testing:
| Aspect | Sanity Testing | Regression Testing |
|---|---|---|
| Objective | Validate specific fixes or enhancements | Verify unchanged features after updates |
| Scope | Narrow (focuses on affected modules) | Broad (covers the entire application) |
| Timing | Performed after targeted fixes | Executed after significant code changes |
| Execution | Quick, limited checks | Comprehensive and time-intensive |
| Automation | Rarely automated | Often automated for efficiency |
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Sanity Testing vs. Smoke Testing vs. Regression Testing
Here's a simple Venn diagram to illustrate the relationship between these types of tests.
Here's a quick table comparing the differences between smoke, sanity, and regression testing:
| Aspect | Smoke Testing | Sanity Testing | Regression Testing |
|---|---|---|---|
| Objective | Verify if the build is stable enough for deeper testing | Validate targeted fixes and small updates | Ensure previously working features still work after code changes |
| Scope | Very broad, checks core system stability | Narrow, focuses on affected modules | Wide, covers many or all application features |
| Timing | Performed on every new build | Performed after targeted fixes on a stable build | Performed after major updates, releases, or code merges |
| Depth | Shallow, checks only basic and critical paths | Medium depth, checks specific logic in detail | Deep, covers full functionality and edge cases |
| Execution | Fast and lightweight | Quick but targeted | Time-consuming and extensive |
| Automation | Commonly automated | Rarely automated | Heavily automated in modern pipelines |
The sanity testing process
- Start by reviewing what changed: Look through change logs, Jira tickets, or commit notes so you understand exactly what developers updated or fixed. This helps you stay focused on the right areas and avoids testing irrelevant parts of the application.
- Confirm you have a stable build: Make sure the build has already passed smoke testing. The core system should load properly, basic features should work, and nothing should be fundamentally broken before you begin sanity testing.
- Identify the specific test scenarios: Select a small set of tests that target the updated area. For example, if the login button was fixed, you check logging in with valid credentials, invalid credentials, and basic redirection after login. You skip deeper tests unrelated to the update.
- Execute quick, focused tests: Run the selected scenarios and observe the results closely. Since sanity testing is designed to be fast, you do not run every possible test. If one of the key checks fails, stop immediately and send the build back for fixes.
- Watch for side effects: While testing the updated feature, pay attention to anything nearby that might have been unintentionally affected. You are not doing a full regression pass, but you still look for unexpected issues around the modified area.
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