Guide to Unit Testing: Best Techniques and Practices for Unit Testing?

The process of testing software starts long before the program is finished. Each piece of software typically undergoes four distinct phases of testing. All other types of testing are built on top of the foundation established by unit testing.

Therefore, the effectiveness of additional tests and the software’s overall performance relies heavily on the precision and completeness of unit testing.

What is unit testing?

A unit test is performed on isolated pieces of software to confirm their accuracy. During the coding phase of software development, unit testing is performed to help find bugs, improve code quality, and ensure security.

Why is it Important?

  • Failure to execute unit tests or doing so half-heartedly might cause execution difficulties that cost additional time, money, and people.
  • One can detect errors before they influence the whole program by testing tiny pieces.
  • As units are short, automated unit testing can be conducted in seconds.
  •  After refactoring or extending code, repeat all test suites to ensure no functionality is broken.
  • Unit testing increases code coverage by dividing an application into testable parts.

What are the best practices?

Plan and implement various tests

Before developing a test case, make sure you’ve thought of every potential instance. Remember to avoid unforeseen circumstances, such as dealing with errors.

Create deterministic test cases

As long as the code is intact, the results of a deterministic test will always be the same. Figuring out what’s wrong and applying the appropriate solution is easy. A non-deterministic test can succeed or fail without modifying the source code.

Test One Scenario Per Test

Testing in multiple contexts is part of manual testing, such as verifying that a solved bug does not affect other features. While many tests and variables may be checked, each unit test must concentrate on one use case. When a test fails, finding the offending code with single-case coverage is simpler.

Automating Unit Testing

Regular and automated testing is needed. Set up the system so all team members can access the reports. Code coverage, the number of test runs, updated code coverage, and performance are just some of the metrics that benefit from this open dialogue between team members.

Write isolated tests

To isolate a component’s behavior within a unit test, a “test double” can offer a dummy implementation of the real thing. A fixed or fake item can stand in for the real something during testing.

Try not to rely on dependent tests

When conducting unit tests, it is optional to have complete test coverage. Instead of configuring a large number of unit tests to achieve the required code coverage, it is preferable to set up a smaller number of high-quality tests.

Prevent Making Live API Calls

Sometimes, testing has to skip over database calls, such as those made by APIs or other services. However, if the tests do not activate these calls, they should be disabled. It is best to offer API stubs containing the necessary behavior and answers to keep tests focused on only the relevant components.

Combine unit testing with integration testing

The “testing pyramid” illustrates the optimal allocation of available testing resources. Top-level tests are more complicated to set up and take longer to execute and debug than their lower-level counterparts. Most testing should be unit testing automation, which corresponds to the base of the testing pyramid.

Validate all of the specifics, including edge cases and boundary conditions, with unit tests. To evaluate the general operation of an API or service, use other tests (component, UI, functional, and integration tests) sparingly.

Manual testing should only be used for exploratory and release acceptance purposes and should make up a minimal fraction of your overall testing pyramid. The testing pyramid approach can help you plan for comprehensive test coverage and automation.

It should reduce the time and effort needed to create and execute your test suites at scale.

Tools for unit testing


HeadSpin is a unit testing tool that improves program performance and user experience: AI-based Platform measures and analyzes packet-level network data and device KPIs to give actionable insights.

Issue cards, time series, session recordings, and packet-level information can help enterprises enhance software application performance. HeadSpin’s data-driven Platform will also assist clients in understanding third-party API, SDK, and UX activity.

QA professionals and teams globally may remotely access and do unit testing on actual devices on the natural carrier and Wi-Fi networks in 90+ locations without SDK or local team help. Organizations may pick HeadSpin on-prem, cloud (single tenant), or cloud (multi-tenant) deployment options and construct their lab. Unit tests help testing teams find and repair software faults.


It’s a free, open-source, Java-based unit testing framework. JUnit was initially developed in 1997 by two separate programmers. Since then, it has undergone a steady stream of modifications. Before being integrated into the code, data is tested using JUnit.

It increases developer productivity, guarantees consistent software code, and eliminates time wasted on debugging. In addition to providing assertions for unit testing, JUnit swiftly constructs routines that improve software quality. Cases in testing may be executed rapidly with JUnit.


JMockit is a tool for code coverage. It is a device that provides coverage for lines, paths, and data. It aids with API simulation by recording and validating syntax. It is a free testing application.


This is an open-source toolkit for analyzing and reporting Java source code. EMMA supports coverage kinds such as method, line, and fundamental block. It’s a Java-based application.


Unit tests are troublesome for testing user interface (UI). Suitable for testing business logic but not UI. While both sides of the UT issue are passionate, the middle position suggests utilizing it responsibly.

Using a unit test best practice program that defines constraints and ensures value and correctness makes sense. Bugs and mistakes in programming should be found early. Using the right tool and following best practices in UT should be efficient and beneficial if you know what to avoid.

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