This document serves as a comprehensive guide to functional testing in software development, highlighting its importance for ensuring application stability, usability, and performance. It covers various testing types including unit, smoke, sanity, regression, integration, and usability testing, along with examples and tools used in the process. Additionally, it discusses the benefits of automated functional testing and considerations for selecting the right automation tools.

1. A Complete Guide to Functional Testing
Testing is an essential aspect of application development and helps ensure the app that you are
building is stable and works well. It helps you test for usability, accessibility, and performance,
so when your users receive the app's final version, they can be sure that it works seamlessly.
Testing also helps you ensure that users get the desired result when they perform a specific
task; this is crucial because 70% of online shoppers will abandon their carts because of poor
UX. (Kinsta via UXCam).
Functional testing addresses this particular aspect of the user experience. Here's everything you
need to know about it.
Measure multi-channel experience monitoring KPIs on real devices and real
networks around the world. Learn more!
What is Functional Testing?
Introduction To Functional Testing
The functional or requirement specifications help define what QA engineers consider acceptable
while running functional tests. These specifications are a document that tells the QA engineers
what actions they must take to determine the conformance of the software system. This
document can also ask them to run tests on specific business side scenarios for an overall
system picture.
Hence, we understand that QA engineers can carry out functional testing in two ways:

2. ● Requirements-based functional testing: This method contains instructions on
validating the software system's functional aspects.
● Business scenarios-based functional testing: This method contains instructions on
validating the software system based on business scenarios.
Functional testing is software testing that ensures a software system works according to its
given specifications. This test's primary goal is to test the functional aspects of the application's
software by providing the input and verifying the output based on requirements.
This test does not concern itself with the application's source code and mainly involves black
box testing. It checks the APIs, security, client/server communication, database, UI, and other
application functionalities. Testers can run functional tests either by using automation or
manually.
What do you test in Functional Testing?
Testers primarily run functional testing to check the software system's functionalities. The areas
this testing concentrates on are:
● Accessibility: Runs accessibility checks on the system to see if it meets accessibility
requirements.
● Error Conditions: Whenever there is an error, the system usually provides a valuable
error message. This test validates that your system works well and provides the
appropriate error messages to debug.
● Mainline functions: The system has no value if its main functions do not work well. This
testing runs to ensure this does not happen.‍
● Basic Usability: The test runs a usability test to ensure that users navigating your
system can do so seamlessly.
What Are The Different Functional Testing Types?
Functional testing comes in many forms, each designed to validate different aspects of a
software system. Below are some of the key types:
1. Unit Testing
Unit testing focuses on isolating individual components or units of a software system.
Developers typically perform these tests to ensure that each unit behaves as expected. In this
context, a "unit" usually refers to the smallest testable part of an app.
Critical aspects of unit testing:
● Line coverage: Ensures that each line of code in the unit is executed at least once
during testing.

3. ● Code path coverage: Verifies that all potential paths within a unit (e.g., loops,
conditionals) are tested.
● Method coverage: Confirms that all methods or functions within the unit are executed
and tested.
Unit testing is typically automated and forms the first layer of defense in ensuring the
functionality of individual code components before integrating them into larger systems.
2. Smoke Testing
Smoke testing, often called "build verification testing," is a high-level test that ensures the basic
functionality of a software build. It serves as a quick check to verify whether the build is stable
enough for more extensive testing.
Key characteristics:
● It is often executed after creating a new build, focusing on critical functionalities to
ensure the system doesn't "break."
● Smoke tests are typically automated and run in continuous integration environments to
provide fast feedback.
● If the smoke test fails, developers conduct further testing only after fixing the build.
Smoke testing is a gatekeeper for more thorough functional testing, ensuring that essential
functions work before more time-intensive tests are run.
3. Sanity Testing
Sanity testing is a more focused form of testing conducted after smoke testing to verify specific
functionalities or bug fixes. It is usually carried out when there has been a minor code change or
bug fix to ensure the impacted areas are functioning as expected without deep regression
testing.
Key aspects:
● Sanity tests are generally narrow in scope, focusing on a subset of functionalities that
recent changes may impact.
● This type of testing is done when there isn't enough time to run a complete regression
test.
● Sanity testing helps ensure that the critical functions of the software are stable after
small changes or fixes.
Sanity tests provide a quick validation that ensures recent changes do not cause major
disruptions in functionality.
4. Regression Testing

4. Regression testing is critical to ensuring that new code changes (whether bug fixes, new
features, or improvements) do not negatively impact the software system's existing functionality.
This type of testing is run whenever there is a significant change to the codebase.
Key points:
● Scope: Although regression tests focus on verifying the lack of unintended side effects,
they don't necessarily cover all functionalities in detail as functional tests do.
● Automation: Since regression tests need to be run frequently, they are often automated
for efficiency.
● Stability: Regression testing ensures the system remains stable and meets
requirements despite ongoing development.
By running regression tests, teams can confidently deliver updates without fear of introducing
new defects into previously working features.
5. Integration Testing
Integration testing validates how different modules or components of a system interact with each
other. While unit testing focuses on individual units, integration testing ensures these units work
together seamlessly.
Key aspects:
● Module interaction: Individual modules may function correctly independently, but
integration tests ensure they interact correctly in combination.
● Data flow: Integration tests focus on verifying that data flows correctly between
components and that there are no breaks in the process.
● End-to-end validation: Integration testing simulates real-world scenarios where multiple
modules must collaborate, ensuring smooth functionality across the system.
Integration testing is crucial for identifying issues that may not be apparent when testing
modules in isolation.
6. Usability Testing
Usability testing is a user-centric method for evaluating a product's ease of use and
intuitiveness. This type of testing involves giving real users access to the product and observing
their interactions to locate any areas for improvement.
Key elements:
● User experience: This test evaluates how well users can navigate and use the system,
focusing on ease of use and user satisfaction.

5. ● Real user feedback: Direct feedback from users helps organizations understand how
the software performs in real-world scenarios and can lead to important improvements in
functionality and design.
● Iterative improvement: Based on user feedback, developers refine the product to
enhance its usability.
Functional Testing Tools
Functional testing is critical in the software development lifecycle, ensuring that the software
behaves as expected and meets the specified requirements. Numerous functional testing tools
have been developed to facilitate this process, each with unique features and strengths. This
section explores some of the most popular and effective functional testing tools available to
developers and testers.
1. Selenium
Selenium is an open-source automation testing tool widely used for web applications. It
supports many programming languages, allowing testers to write test scripts in the most
comfortable language. Selenium WebDriver, a component of Selenium, enables automated
testing to be conducted on various web browsers. Its compatibility with numerous browsers and
operating systems makes it a versatile choice for functional testing.
2. TestComplete
TestComplete is a comprehensive automation testing platform that supports desktop, mobile,
and web applications. It offers a powerful interface that allows testers to create automated tests
without deep programming knowledge. TestComplete supports various scripting languages,
including JavaScript, Python, and VBScript, and provides advanced capabilities for recording,
editing, and running tests. Its ability to sync with other tools and frameworks enhances its utility
in a complex testing ecosystem.
3. QTP/UFT (Unified Functional Testing)
Developed by Micro Focus, UFT is a commercial functional and regression testing tool. It
supports various web, desktop, and mobile applications and offers an intuitive visual interface
that simplifies test creation and execution. UFT integrates seamlessly with other Micro Focus
tools, providing a robust solution for continuous testing and integration.
4. JUnit and NUnit
JUnit and NUnit are frameworks used for unit testing in Java and .NET environments. While
they are primarily designed for unit testing, they can also be used for functional testing by
integrating them with other tools. These frameworks facilitate test-driven development (TDD)

6. and behavior-driven development (BDD), promoting a more structured and efficient testing
process.
5. Cucumber
Cucumber allows the specification of application behavior in plain language. This makes it
easier for stakeholders, including those without technical backgrounds, to understand the tests.
Cucumber supports various languages, including Ruby, Java, and .NET, and integrates with
Selenium and other testing frameworks to facilitate comprehensive functional testing.
6. Postman
Postman helps with the functional testing of web services. It provides a user-friendly interface to
send requests to web servers and analyze responses. Postman supports automated testing
through scripting and collection runners, making it a valuable tool for testing the functionality of
RESTful APIs and other web services.
Process Workflow for Functional Testing
The process workflow of a functional test includes three steps. They are:
1. Create input values
2. Execute test cases
3. Compare the actual output with the expected result.
Functional testing generally follows the steps mentioned below:
1. Determine which aspect of the software system the testers need to test. These aspects
or functionalities can vary from error conditions, product usability, messages, or central
functions.
2. Create input data according to specific requirements for the functionalities that need
testing.
3. Based on the outlined requirements, determine which output parameters are acceptable
and which ones are not.
4. Execute test cases.
5. Finally, compare the expected output with the actual result you receive from the test.
Tracking this will reveal if your software system works well.
Example: Use Case Scenario for Functional Testing
Situation:

7. Users log in to an Human Resource Management System (HRMS) portal with their login ID and
password. The login page of the HRMS portal has two text fields –one for users to enter their
username and the other for password–and two buttons – cancel and log in.
The action: The user enters their login credentials into the text fields.
The result: The user clicks on the login button and gets directed to the HRMS home page. The
login gets canceled when the user clicks on the login button.
Specifications:
1. User ID field: Users must enter a minimum of 6 characters and a maximum of 10. They
can include numbers from 0-9, letters from A-Z, both upper and lower case, and can only
contain a period, a hyphen, and an underscore for special characters. Users cannot
leave any field blank. Their ID must begin with a number.
2. Password field: Users must enter a minimum of 6 characters and a maximum of 8. The
password must include numbers from 0-9, letters from A-Z, upper and lower cases, and
special characters. Users cannot leave the password field blank.
The above use case is a basic example of functional testing. Many functional testing techniques
can help us to test it. Here are a few:
System Tests
The system test helps check all the system components and understand if they work perfectly
together. In the above example, this would mean testing the customer journey from loading the
HRMS app, the user entering proper credentials, getting redirected to the main page, the user
performing tasks, and eventually logging out of the HRMS app. The test ensures that this entire
journey is seamless and without any bugs.
Equivalence test
Segregation analysts segregate test data into partitions. These partitions are called equivalence
data cases. The equivalence test checks to see if the data in each partition responds similarly.
Therefore testing one condition across all partitions will give you the desired result. Since if the
condition does not work in one, it will not work in any. In the above example, if the user enters
characters > 10, the result must be the same.
Boundary Value Tests
Boundary value tests check the system's behavior when a user does not meet certain data
limits. In the above example, the user must enter a password that requires a minimum of 6
characters. This test helps understand the system's response when the user enters a less than
six characters password.

8. Decision-based tests
The decision-based tests help understand how the system responds when the user meets a
particular condition.
You can undertake the following decision-based tests in the above example:
● When the user enters the wrong credentials, he should get an alert from the user and
reload the page.
● The system should take the user to the home page if he enters the correct credentials.
● If the user cancels the login after entering the correct credentials, he should not get
redirected to the home page but instead to the login page.
Ad-hoc Tests
Ad-hoc tests help uncover issues within the system software that you might not have identified
through other tests. Ad-hoc tests break the system to check its response. In the above example,
an administrator would run an ad-hoc test by deleting a user account while the user is
performing tasks in his account. The test will help the administrator to understand if the system
responds seamlessly in this situation.
Advantages and Disadvantages of Functional Testing
Advantages:
● This test reproduces the product in a live environment, and its focus is on the operating
system, browsers, system specifications, and more.
● It does not work on hypotheticals and deals directly with the system's structure.
● Organizations can deliver high-quality products through this testing methodology. It
enables them to meet customer requirements and ensure customer satisfaction.
● This test helps organizations deliver a bug-free product and one that meets all the
customer's requirements.
● Risk-based testing ensures a decrease in the chances of risk.
Limitations
While this test ensures the product meets the customer requirements, it does not consider the
performance, throughput time, responsiveness, and others. These aspects are essential to test
for the overall health of the product.
Additionally, functional testing fails to account for variables like the time it takes to execute
specific functions, the security of the app, and other essential aspects. While functional testing
is critical, it cannot certify if an application is ready for real-world use.
Disadvantages

9. ● Many times testers can end up performing redundant tests.
● Testers can miss out on logical errors present in the product.
● Since testers run this test based on requirements, it can be time-consuming if the testing
requirements are not precise or complicated.
Automated Functional Testing
Why Automate Functional Testing?
Automating functional tests helps improve efficiency. It lets you take simple tasks away from
manual workers and give them to AI; this allows the company a chance to save money. It also
helps save time as testers no longer have to run tests repeatedly, thus optimizing all your
processes.
With automated functional testing, you will not have to worry about test efficiency as automation
tools will ensure effective and efficient ways of testing. Automation processes are extensively
scalable and don't require sourcing or paying new hires, making them an excellent investment.
The aspect of scaling is vital for enterprises liable to rapid growth since they will need to invest
in highly scalable solutions. Startups also must consider this since they have the prospect of
moving from a small to a large scale business quickly.
Benefits Of Automated Functional Testing
Automated functional testing has many benefits. Here are a few of them:
● Automation affects the testing process: Automated functional testing helps speed up
the testing process meaning developers will have more time to focus on bugs. With more
time, the chances of developers addressing bugs through quick fixes will reduce. Quick
fixes only address the superficial and do not fix the root cause. With faster testing
processes in place, developers have all the time to address core concerns and solve
issues. The HeadSpin platform provides actionable insights that your developers can
use to their benefit.
● Automation lets you add several test cases: Manual testing can limit the use of test
cases based on the capacity of the tester. However, the number of test cases you can
add with automation is endless. Organizations can identify their needs and accordingly
increase the test cases.
● Automation sticks to the timeline: Another reason automation is effective is that it
sticks to the timeline. With automation meeting its timelines, developers can organize
more tests, address issues, and continue to improve the app.
Automation helps improve app quality: With automation in place, you have the means to run
tests often. The more often you run tests, the better the quality of your final product. The
increase in product quality will surely help your company grow.

10. What to Consider When Going for Automation
Automation Tool Selection
There are many automation tools you can choose from; however, the best way to select the one
that works for you is by creating a list of requirements. Here's what you can add to the list.
● The tool you select should be easy to use by all the members of the QA team.
● Testers can use the tool across various environments.
● The automation functional testing tool should have all the features you need, like support
for automated build tests, logging, specific reporting, and more.
● The tool should support the reusability of test cases.
Here are some of the automation tools that you can choose from:
● Appium
● Selenium
● QTP
● Junit
● SoapUI
● TestComplete
Know which test cases need automation
Knowing which test cases you need to automate to get the best out of automation is essential.
For example, manual testers are best for handling test cases that require adjustments in setup
or configurations during test execution. Here are some that you can automate:
● Tests that need to run repeatedly
● Tests that run with various kinds of data
● Error-prone tests
● Tests that need to run in multiple browsers, and environments
Have a team dedicated to automation
Many organizations overlook this point and have all members of the QA team learn automation.
While internal training is excellent, it is essential to understand that each member has different
experience levels, interests, and skills. In such cases, it is good to understand each team
member's skills and have selected members doing automation. A dedicated team of individuals
with the right drive will focus on automation and bring out the best results.
If you’re looking for a way to do this, the HeadSpin University can help you. It offers courses on
Appium and connects you with leaders in the test automation industry. A core Appium
contributor, the project lead for the Appium Mobile Automation Platform, and the Director of

11. Automation Technologies at HeadSpin, Jonathan Lipps, instructs students with walkthroughs on
using automation and building apps.
Data-driven tests
Developers need to write automated test cases requiring multiple sets of data well. A
well-written test case is reusable. They can write this data in configuration files or read them
from a database. Creating a well-structured data source will make it easier for you to maintain
the framework allowing you to use the test cases to their full potential.
Changes to the UI should not affect your test cases
UI changes must not affect the test cases that you create. For example, earlier versions of
Selenium identified page elements through a location. So a change in UI meant that those
elements would suggest that you could no longer find those locations, leading to failed tests.
Understanding the tool and writing test cases to ensure minimal changes to the UI will help.
Test Frequently
Having an automation device pool ready is the first step. Ensuring that this bucket has frequent
executions is the next; this helps in two ways; first, it enhances the test automation framework,
and second, it enables you to catch more bugs.
Functional testing with HeadSpin
The HeadSpin Platform allows you to connect to real devices from around the world. You can
run multiple tests in tandem. It integrates seamlessly with your CI/CD workflows, enabling
functional testing both pre and post-release.
Our machine learning provides detailed insights, automatically highlighting issues and pointing
out the underlying root cause; this enables developers to get straight to the problem and fix it,
thus significantly improving time to market.
Article Source:
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