Unit, Integration, and Functional Testing: 4 main points of difference

Introduction

Unit, integration, and functional testing are crucial components of software application testing. Each of these employs a distinct and unique process to test the application. However, the most important remains functional testing and functional regression testing. Unit or integration testing cannot replace this, either by itself or collectively. While unit testing involves testing individual modules of an application, isolated integration testing checks if different modules are working together as a group. Finally, functional testing checks whether the system operates the way it is supposed to.

Together, these constitute an application that is bug-free and smooth for the end-user. Functionality is related to integration tests. The latter is performed only when the former has yielded desired results. However, successful automated functional testing signifies that the entire app is running smoothly.

Unit testing

Unit testing involves testing applications at a unit level. It checks single components. You can optimize ROI (return on investment) if your codebase runs multiple unit tests with fewer integration tests and even fewer functional tests. Since the unit is the smallest part of an application, they are easier to write and quicker to execute. Usually, these tests are written and performed by software developers themselves. The primary aim here is to match the requirements to the unit's behavior. This kind of testing is usually done before integration testing using white box testing techniques. Some of the most popular unit testing tools used for different languages are JUnit of Java Framework, PHPUnit of PHP framework, and NUnit of .Net framework.

Check out: Different Types of Test Automation Frameworks

Unit testing has several benefits, for instance:

• It checks whether or not there is correct output for valid input. 
• It also checks for failures that occur with invalid input. 
• It finds issues and bugs in the early stages to resolve them faster. It also reduces overall project costs. 
• Since unit testing tests small pieces of code and isolated functions, the issues it spots are independent of other test cases. 
• It makes resolving issues at a later stage easier by simplifying unit test cases and making the very act of testing code easy.
• Unit testing helps to save time and cost and is also easy to maintain.

Integration testing

Integration testing, as mentioned before, tests if the different parts of a system can work together and how well they work in synthesis. Various modules of such an ecosystem are merged to facilitate integration testing procedures. The purpose of this is to check the overall performance and reliability. This is performed on modules that have already undergone unit testing. It then defines if the combination of these elements can provide the desired output or not.

There are three types of approaches to integration testing as are as follows:

The Big Bang Approach

• Here, the modules are integrated and tested as a whole if the entire system is ready for such an integration. This is different from system testing. While system testing is for the ecosystem, integration testing checks only the modules. The Big Bang Approach lets you test everything simultaneously, thereby preserving resources. However, it could be challenging to identify specific errors.   

The Top-Down Approach

• Here, different modules or units are combined is tested using a top-to-bottom approach. First, the units are tested individually by writing test STUBS. Lower levels are then integrated in sequential order until the last one is compiled and tested. Experts believe that it is the most organic way of organizing a test because it is similar to the way things happen in real-life situations. The primary issue is that functionality is constantly tested at the end. It could mean going back and fixing issues through functional regression testing.

The Bottom-Up Approach  

Modules are tested from the bottom to the topmost level in the bottom-up approach. Simulator programs called DRIVERS facilitate this process. The bottom-up approach helps to detect bugs at lower levels. It enables the team to function as expected.

Also check: Functional Test Automation 101 - How & When to Start

Functionality testing 

Automated functional testing is a black-box testing technique that ensures the overall operability of the application. This checks if a desirable output is generated out of a specific input. Test cases are then written based on the requirements and scenarios and then implemented. The number of tests can vary based on the nature of the software. Each test case comprises the test summary, prerequisites, input steps, test data, expected output, and notes (if any).

The two forms of automated functional testing are as follows:

• Requirement-based: The test cases are created based on the app's demands.

• Business scenario-based: The tests are customized to align with the business strategy. 

Functional regression testing tests, or rather re-tests applications when new and improved features are added, and functions are modified for existing applications. It also checks if the older attributes and functionalities work well with the upgrades. While functional testing can assure all operations are working flawlessly, functional regression testing comes into play only when the team has published a new build that aims to fix bugs or debug new updates.

Read: Prioritizing Automated Functional Test Scenarios

The benefits of functional regression testing include the following:

• It plays an integral role in agile environments where every sprint is crucial. Functional regression testing makes sure that previous and current releases all work together seamlessly.
• It helps to identify bugs in the software. Regression tests make software resistant to discrepancies. Such procedures provide support to testing and QA teams to deliver fast results.
•  It helps retain the integrity of an application despite new additions.
• Regressive testing helps to shorten the overall testing lifecycle. 
• These tests help achieve a higher Customer Satisfaction Index (CSI) and can eventually be considered crucial for expanding business. 
• They help reduce calls for incidents in production. Thus, the cost of the overall project reduces.

Also read: Benefits of Using Automated Functional Testing

The main differences between the three 

The differences between unit testing, integration testing, and functionality testing can be divided into the following categories:

• Purpose: Unit testing checks the most basic unit of the application, each module, individually. Integration testing checks two or more modules combined to perform tasks. Functional automation testing tests the behavior of the application when it functions as a whole. 

• Complexity: Unit testing is simple in its language and is easy to write since it includes the smallest of codes. While integration testing is slightly more complex compared to unit tests, functionality testing constitutes the most complicated of the batch.

• Testing techniques: Unit testing involves white box testing techniques. Functionality regression testing consists of only black-box testing techniques. Integration testing uses both black and white box techniques- also called grey-box testing. 

• Errors covered: Unit tests can cover issues that occur with frequency in different modules. It nullifies the chance of any problem going unnoticed. In the case of integration testing, the errors covered include bugs that occur when integrating various modules. Issue escape is a rare occurrence. For automated functionality testing, issues that hinder the performance of an application are identified. Scenario-based problems are also tested here. There is the most chance of issue escape here because the list of tests to be run is infinite.

Also read: How Can You Prioritize Automated Functional Test Scenarios?

Conclusion

To conclude, we must understand that these processes are interconnected and correlated. Unit testing is imperative to ensure that your software is working seamlessly. Unit testing facilitates flawless paths and lines of code. This, in turn, must be followed by integration tests to make sure that separate units can work together cohesively. Finally, all of the above must be followed by functional tests to deliver a polished app. Functional regression testing also needs to be performed if the application in question is an existing software where updates are being implemented. 

FAQs

1. Is integration testing the same as functional testing?

Functional testing is performed to validate all functionalities of an application, while integration testing is performed to validate the interaction across modules and verify that they work well when compiled.

2. Can unit testing be used for Integration testing purposes?

No. Unit testing only tests separate modules in an application at an isolated level, while integration testing tests how the collaboration between all the modules functions together. It is debatable whether unit testing tools will not be sufficient to carry out successful integration testing. 

3. Is Integration testing performed after unit and functional testing?

The order of testing is: 

• Unit testing, 
• Integration testing, and finally- 
• Functionality testing to ensure every development process level is working as desired. 

4. What is mocking in unit testing?

Mocking is used in unit testing when it has external dependencies. Its purpose is to isolate and focus on the code being tested and not on the behavior or state of the mentioned external dependencies.

5. What are the five steps of functional testing?

Functional testing generally follows the following steps:

1. Determining the functionality of the product which needs to be tested.
2. Creating input data for functionalities to be tested according to the particular requirements.
3. Determining acceptable output parameters according to similarly specified requirements. 
4. Executing the test cases.
5. Comparing the actual output of the test with the predetermined desired output values.