Main aim of any application or software testing is to build a high quality product. Functional testing and unit testing are the foundation of the testing process. Both software testing types have their own importance in software development. Functional testing is performed by the tester during system testing whereas unit testing is performed by the developer during the development cycle. Utility of functional testing is understood by users, developers and QA alike. Here we will understand the various aspects of unit testing vs functional testing. Before digging to the comparison, let us see what is unit testing and what is functional testing.
Unit testing is a popular testing that helps to eliminate the risk of having bugs in codes. And so it is adopted by many organizations. In this type of testing all individual units or components are tested. Main purpose is to validate each unit of software code and check whether they are performing as expected or not. It isolates the code section, verifies correctness of code, test each function and procedure, finds early bugs and fixes in the development cycle to save costs, helps developers to understand the code base and enable them to make changes quickly, and helps for code reuse.
This software testing process validates software systems against functional requirements. Main goal of functional testing is to test functionality of software application by providing input, output verification according to the functional requirements. It finds defects that programmer may have ignored while developing software, provides information about the level of quality, prevents defects, and ensures that the result meets the business and user’s requirements.
You can also know the difference between Alpha, Beta and Gamma Testing at- Alpha, Beta and Gamma Testing- What is the difference?
Individual units of code are tested separately with unit testing. Main purpose of unit testing is to separate the smallest testable parts of API and verify if it functions properly in isolation. This testing verifies the different behavioral aspects of system under testing, whereas mainly it verifies whether the system under testing produces the correct results or not. From the developer’s point of view, the goal of unit testing is to create strong codebase with less cost. Also the important purpose of unit testing is to provide documentation for high-level testing like integration testing and functional testing.
Main goal of functional testing is to check the functionalities of a system. In this type of testing, a tester is not worried about the core code, rather they have to verify the output based on the user requirements with expected output. Functional tests check the whole software, its software, and networking infrastructure – from the front end to the back end database systems. It is form of integration testing which ensures that all components are working together as needed. Functional testing don’t enlighten you about the errors or its location. It just notifies you that something is broken, it can be the browser, test or race condition. As it follows end-to-end testing, there is no way to tell.
Unit tests are a solid foundation on which the rest of the testing process should be built. It is good to write tests from the start of code writing. A popular software development practice Test Driven Development advocates writing tests before coding. You can refactor your code and unit tests will tell you if you broke anything.
It starts when two modules interact with each other and then testers perform functional testing on the feature. You can use unit test to test an individual function and integration test to verify how two parts performing nicely. Functional test are on a complete another level, however you can have hundreds of unit tests, you usually want to have just a small amount of functional tests.
Through writing a test to drive your new code, you essentially capture that work. For instance, if in six months the programmer breaks the code, you can use that test to fix the code. Defects in objects are identified very quickly, so it needs less re-work and re-test dependency on other code. Generally complex apps has many variables to clearly test practically. Breaking it into manageable unit tests is less expensive to develop and maintain. It generates decent bug report with the answer of questions like- What is the expected behavior?, What was the actual result?, What is expected result, which component is under test?
It verifies whether the app or system works as expected or not. Generally have detailed tests for “happy paths”- that ensures the critical app capabilities like signups, purchase workflows, logins etc. and all the critical user workflows all behave as expected. There are lots of functional testing types and each has its own set of advantages. For instance, Smoke testing checks the critical feature of build and saves time and reduce regressions, integration testing verifies that all the integration are working together, system testing validates the whole software/application with regards to real user scenarios. End to End tests increase test coverage and reduces the risk with integrating new code into an app.
Test coverage is important in software testing and it serves different purpose for unit testing and functional testing. Test coverage tool tracks which code is executed or which is not. In case of unit testing, we can call it a code coverage. There’s a belief that high code coverage improves the code quality. If unit tests are poorly written with high test coverage, then it can’t assure the better code quality.
For this testing, test converge can establish traceability between test cases and requirements. Functional test coverage must indicate what features are done and what are still in progress. Such information is more accessible to product owners than exercised code lines.
In TDD, you have to write unit tests prior to production code writing. Here you have to think about design of code upfront according to the requirements. Sometimes at starting, design is not clear and expands as you go further – at such cases you need to redo your test and this is very time consuming. For instance, frequently changing algorithms takes more time. It will be better to postponed unit cases until you get clear design idea. In some of the cases, you have to deal with other dependencies and integrations like database, user interface etc. Here TDD becomes hard and it includes many abstractions like mock objects, programming to an interface, MVC/MVP patterns etc. It needs detailed knowledge and developers have to write many unit tests, some of the times, more than actual code.
Regardless of dependencies, unit testing becomes very complex when you test trivial code. With unit testing, we can mock out all dependencies, however for functional testing it is different. A good example is- testing a simple screen that loads network data – it will fail every time you run it while disconnected. Such scenarios make functional testing complex.
Most of the time, developers divide their time of developing new features and fixing defects. Some part of release is spent on functionality testing that was already released and used. While the main effort of designing and writing test plans for this functionality is investing in past releases, each new feature developed requires a test plan and a maintenance effort for tests that are existing. Main objective of QA managers is to reduce efforts. Teams that succeed to create clear and reusable tests simplify the maintenance and can optimize the test registration time.
Unit TestingFunctional Testing1. It is performed by developer while coding1. It is performed by Functional tester in lined with user/business document2. Testing happens within system structure2. No System Structure Assumptions.3. This testing happens while coding, one code at a time.3. This testing happens after the development is complete.4. White Box testing method4. Black box testing method5. Third-party tool or created within the development group.5. Test conditions created from business requirements6. Helps in Debugging-process simplification by isolation the code that’s bad.6. Helps to eliminate functional errors.