Software testing is the foundation of reliable software delivery. However, understanding the terminology can be tricky, especially for beginners. Terms like unit testing and automated testing are often used interchangeably, leading to confusion. The truth is that unit testing and automated testing are not competitors—they complement each other.
By the end of this post, you’ll know:
Unit testing is software testing that focuses on checking the smallest pieces of code – called units. Units usually refer to individual functions or methods.
The purpose? To verify that each unit performs exactly as intended, in complete isolation. This means no dependencies on databases, APIs, or other systems. Unit tests are typically automated and written by developers during the coding process.
Developers primarily perform unit testing as an integral part of the software development process, rather than by dedicated quality assurance (QA) testers. This proactive approach allows developers to write and execute unit tests alongside their code, ensuring each unit functions correctly in isolation.
The main components of a unit test include:
Unit testing typically occurs during the coding phase of the software development lifecycle. It is often associated with test-driven development (TDD), a methodology where tests are written before the actual code implementation.
Let’s consider a banking application where we want to verify the behavior of a function that determines whether a user is eligible for a loan. The function calculates eligibility based on the user’s income and existing loans.
Here is the function in Python:
We can write a unit test to validate the function:
In this example, the unit test verifies various inputs and their expected outputs. If the function does not behave as expected, the test will fail, and immediate feedback will be provided to the developer.
Unit testing ensures that the building blocks of your application are solid, creating a strong foundation for more complex tests.
Integrating unit testing into the development process is essential for ensuring code quality and reliability. Here are some best practices to effectively incorporate unit testing:
1. Write readable and simple tests
Unit tests should be easy to read and understand. Using a clear structure, such as the Arrange-Act-Assert (AAA) pattern, helps maintain simplicity and clarity in test cases. This approach allows developers to quickly identify what the test is doing, making it easier to maintain and refactor over time.
2. Automate Unit tests
Setting up an automated testing process that runs tests regularly—such as daily or with each code commit—ensures that any issues are identified early in the development cycle. This integration into a continuous integration/continuous deployment (CI/CD) pipeline allows all team members to access and review test reports, fostering collaboration and discussion around code quality metrics.
3. Isolate tests
Each unit test should focus on a single unit of functionality without relying on external systems or other tests. This isolation can be achieved using test doubles, such as mocks or stubs, which simulate the behavior of external dependencies. Isolated tests are faster, more reliable, and easier to diagnose when they fail.
4. Avoid test interdependence
Unit tests should be independent to prevent a single failure from cascading through the entire test suite. By ensuring that each test can run in isolation, developers can more easily pinpoint issues and maintain a stable testing environment.
5. Combine Unit and Integration testing
While unit tests validate individual components, integration tests assess how these components work together. Following the testing pyramid model, unit tests should form the base of your testing strategy, with integration tests used sparingly to validate interactions between components.
6. Ensure repeatability and scalability
Unit tests should be repeatable under various conditions and scalable as the application grows. Writing tests alongside application code—especially in methodologies like Test-Driven Development (TDD)—ensures that appropriate tests accompany every new feature or bug fix.
7. Use appropriate tools
Leverage frameworks suited for your programming language to streamline the unit testing process. Popular frameworks include JUnit for Java, NUnit for .NET, and pytest for Python, which provide essential tools for writing, running, and reporting on tests.
8. Focus on critical features
While achieving high test coverage is important, prioritize writing meaningful tests that cover critical functionalities rather than aiming for 100% coverage with low-quality tests.
9. Run tests frequently
Integrate unit testing into your daily development routine by running tests frequently—ideally before merging code changes into the main branch—to catch regressions early.
10. Conduct peer reviews
Encourage peer reviews of code and test cases to identify edge cases and enhance overall test quality.
While unit testing focuses on individual units of code, automated testing is a broader concept that involves automating the execution of test cases using tools, frameworks, or scripts.
Automated testing aims to replace manual testing efforts with automated processes that are faster, repeatable, and less error-prone.
Automated testing covers various types of tests, including:
Let’s build on the banking app example. Imagine we must test the complete user workflow for transferring funds between two accounts.
End-to-end (E2E) test:
Using Selenium, we can automate the entire user process:
This automated E2E test simulates a real user workflow, from logging in to transferring funds and verifying the updated balance. Unlike unit tests, E2E tests involve multiple components, such as the user interface, database, and backend logic.
While unit testing is a subset of automated testing, there are important differences between the two:
Although unit tests provide a strong foundation, they are not sufficient on their own. Unit tests verify that individual functions work but cannot ensure the system behaves correctly.
This is where other automated tests—such as integration and E2E tests—become essential.
Together, unit tests and automated tests create a robust safety net that:
For example:
Combining these tests ensures that individual components and the entire application function reliably.
To implement unit testing and automated testing effectively, developers and testers use a variety of tools:
Popular Unit Testing Tools
Popular Automated Testing Tools
Metrics provide teams with quantifiable insights into their testing efforts, helping them identify gaps, assess test performance, and ensure reliable code delivery:
A high code coverage percentage indicates that most codebase has been tested. This metric highlights untested areas, allowing teams to address potential blind spots in their test suites.
Why it matters:
While a high coverage percentage is desirable, it does not guarantee the quality of tests. For example, executing code without verifying meaningful outputs can create a false sense of security. Achieving 100% coverage is often impractical and does not necessarily indicate bug-free software.
Consistently high pass rates indicate stable and reliable code, while frequent test failures may signal new defects, unstable features, or inadequate test coverage.
Why it matters:
If a new deployment reduces the test pass rate from 98% to 85%, this suggests recent changes introduced bugs or conflicts. Investigating and addressing the failures quickly will prevent defects from reaching production.
A lower defect density typically reflects higher code quality and more effective testing practices. Teams use this metric to assess whether their tests uncover enough issues relative to code growth.
Why it matters:
If defect density increases despite good coverage, it may indicate that tests are missing edge cases or complex scenarios. Addressing this can improve the effectiveness of both unit and automated tests.
Tests that run quickly deliver faster feedback to developers, which is especially important in continuous integration (CI) pipelines. Slow tests can delay deployments and reduce productivity.
Why it matters:
A high rate of flaky tests undermines trust in the testing process, as failures may not indicate real defects.
Why it matters:
This metric helps teams evaluate how effectively their testing processes prevent bugs from reaching production.
Why it matters:
The testing process can be effective if 90% of defects are caught during testing and only 10% surface after release. On the other hand, frequent post-release bugs indicate gaps in the test suite or inadequate coverage of critical paths.
Well-designed tests should validate meaningful scenarios and catch potential errors. Tests that rarely fail or do not identify issues may need to be reviewed or improved.
Why it matters:
At Global App Testing, our flexible crowdtesting solution enhances your automated testing processes, enabling you to make progress where teams traditionally struggle. Here’s how:
1. Instant scalability
Our global network of human testers can execute manual test cases across real devices, physical environments, and geographies – areas that automated scripts often miss. By scaling your manual testing efforts, we allow your team to focus on improving automation coverage.
2. Support for in-house teams
We work alongside your QA and QE teams, providing reliable test execution that addresses immediate gaps in coverage. This approach reduces bottlenecks and creates the time needed to prioritize automation.
3. Execution of automation-queued test cases
Automation queues often become backlogged, particularly when flaky tests or infrastructure challenges arise. Offloading these test cases to our testers ensures critical tests continue running while your engineers address automation setbacks.
What else do we offer
Beyond supporting your test automation efforts, GAT offers a full suite of testing services to enhance software quality at every stage:
Are you curious to see how much of your test suite we can help you automate? Let’s schedule a call to explore the possibilities together.
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