What are the disadvantages of functional testing?

Functional testing can miss critical and logical errors in the system. The probability of conducting redundant testing is high in functional testing. This testing does not guarantee the readiness of the software to go live.

What is non-functional testing?

Non-functional testing verifies the way software works and how well it works. In contrast, functional testing proves what software does. Non-functional testing is just as necessary as functional testing. Both of them ensure that your product is working as it should. But non-functional testing checks things that are not under practical test.

Functional Testing - Naukri Code 360

Introduction

In general, testing means finding out how well something works. Software testing is the process of evaluating and verifying whether a software application works or not. The benefits of testing include preventing bugs, reducing development costs, and improving performance. The main intention of software testing is to detect software failures so that defects may be found and fixed.

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What is Functional Testing?

Functional testing is how QAs determine if a piece of software is acting by pre-determined requirements or not. It uses black-box testing methods, in which the tester does not know the internal system logic. Functional testing is only interested in validating if a system works as planned.

Functional testing checks an application, system, or website to ensure that it is doing exactly its intended purpose. Every project creates a document listing of requirement specifications in the early stages. From a user’s perspective, it lists what the application/system/website should do.

Types of Functional Testing

Source: softwaretestinghelp.com

Unit Testing: Developers who write scripts perform unit testing to test if individual components/units of an application match the requirements. Unit testing usually involves writing tests that call the methods in each division and validate them when they return values that fit the needs. Examining the extent to which the code executes is also necessary for unit testing. Keep in mind that test cases exist to cover the Line coverage, Code path coverage, and Method coverage.
Smoke Testing: It is done after the release of each build to ensure software stability is intact and it is not facing any abnormalities.
Sanity Testing: Run this test to verify that every critical application functionality works perfectly, both by itself and with other elements. We usually do it after smoke testing.
Regression Testing: This test ensures that changes like new code, debugging strategies, etc., to the codebase do not disrupt existing functions or trigger instability.
Integration Testing: Integration testing tests that the end-to-end outcome of the system meets these necessary standards. It ensures that individual modules work as expected when operating in combination.
Usability Testing: At this stage, actual customers test the product in a production environment. This stage is necessary to get feedback to implement further code improvements and see how comfortable a customer is with the interface.

Workflow for Functional Testing

The functional testing process includes the following steps:

Create test data
Execute test cases
Compare actual and expected output

Source: softwaretestinghelp.com

Functional testing in detail follows the following steps:

The first step involves determining the product's functionality that needs to be tested. It includes testing the main functionalities, error conditions, and messages, checking whether the product is user-friendly or not, etc.
Next is to create the input data to test the functionality as per the requirement specification.
Determine the output for the functionality under test from the requirement specification.
Execute the prepared test cases.
Compare the result after executing the test case and the expected outcome to find whether the functionality is performing as expected or not.

Functional Testing Techniques

Following are the techniques for functional testing:-

For example, an online HRMS portal is set upon which the user logs in with their username & password. The login webpage has two text fields and two buttons, i.e., login and Cancel.

End-user based/System Tests

Test the system to determine if all components are working perfectly in combination.

In our example, this would entail testing the customer journey – HRMS application loading, entering correct credentials, leading to the home page, accomplishing tasks, logging out, etc. This test guarantees that this workflow proceeds and finishes without errors or warnings.

Equivalence Tests

Segregate test data into partitions called equivalence data cases. In this test, data in each division must respond similarly. Accordingly, you only need to test one condition across all divisions. If the condition does not function in one section, it won't work in any others.

In the example, since the user-id field can accommodate a maximum of 10 characters, it should behave the same way when entering data > 10.

Boundary Value Tests

These tests check how the system behaves when we implement data limits.

In the example, since the user-id requires a minimum of 6 characters, this test will check how the system responds when entering less than six characters.

Decision-based Tests

Initiate these tests to check for possible system outcomes when we meet a particular condition.

In the example, we can undertake the following decision-based tests:

If someone enters incorrect credentials, the system should inform the user and reload the login page.
When we enter the correct credentials, The system should take the user to the home page UI.
If someone enters valid credentials but wants to cancel the login, the system should not direct to the home page UI.
Instead, it should reload the login page.

Alternate Flow Tests

We run alternate path tests to validate all possible ways to accomplish a function other than the main flow.

Ad-hoc Tests

These tests discover discrepancies that might not have been identified in any other tests. The Ad-hoc test's target is to break the system and check its response.

Best Practices for Functional Testing

Pick the suitable test cases: It is essential to select the test cases you will automate. It is recommended not to automate tests that require some setup and configuration during or before execution. Automate the following kinds of tests:
- Tests that are needed to run regularly.
- Same trials with different data.
- P1, P2 test cases consume much time and effort.
- Prone to human error.
- Test in other OS, browsers, devices, etc.
Dedicated Automation Team: Each team member has varied experience levels, skill sets, interest levels, bandwidth to support automation, etc. Some individuals may be better skilled at executing manual tests, while others know scripting and automation tools. In situations like this, it's good to analyze all the team members and have some members dedicated to doing only automation. Automation is not an easy activity that requires time, effort, knowledge, and a dedicated team that will help achieve the needed results instead of overloading all the team members with manual and automation testing.
Data-Driven Tests: Write automated test cases requiring multiple data sets to be reusable. The data could be written in text or properties files, XML files, or read from a database. Whatever the data source, creating well-structured automation data makes the framework easier to maintain and uses the existing test scripts to their full potential.
Be on the lookout: Your chosen test cases and automation tool must adapt to UI changes. If the UI changes and the elements are no longer at those locations, it can lead to test failures across the board. Therefore, consider writing test cases that enact minimal change in the event of UI changes.
Test frequently: Once you have a primary automation test bucket ready, plan to execute this bucket more regularly. This has two advantages, One is you can enhance the automation framework and make it more rugged, and the second is that you will catch more bugs in operation.

Frequently Asked Questions

What is Functional Testing?
Functional testing is how QAs determine if a piece of software is acting by pre-determined requirements or not. It uses black-box testing methods, in which the tester does not know the internal system logic. Functional testing is only interested in validating if a system works as planned.
What are the disadvantages of functional testing?
Functional testing can miss critical and logical errors in the system. The probability of conducting redundant testing is high in functional testing. This testing does not guarantee the readiness of the software to go live.
What is non-functional testing?
Non-functional testing verifies the way software works and how well it works. In contrast, functional testing proves what software does. Non-functional testing is just as necessary as functional testing. Both of them ensure that your product is working as it should. But non-functional testing checks things that are not under practical test.

Key Takeaways

This article teaches what functional testing is and why it is essential. We saw its types and how we can use them when testing. Click here to read about Non-Functional Testing and Software Testing Strategies.

Recommended Readings:

Sanity Testing vs Smoke Testing

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