Can mobile regression testing be automated?

Regression testing is an indispensable part of mobile app development. It ensures that updates and bug fixes don’t adversely affect existing functionality, important for maintaining app stability and a good user experience. Regression testing in a nutshell involves re-running tests on every build, to ensure that recent changes integrate well with the existing build and have not broken anything.

Mobile apps and games change and evolve very frequently, and many times in response to user reviews and feedback. However, just inputting regression testing is not really enough – automating it is becoming essential in order to reduce human error and speed up the resolution of issues. Fundamentally this process helps free up your developers from wasting time on bug fixes and allows them to spend their time developing new features and enriching old ones.

If you’re on the fence about automating regression testing, the question you should be asking yourself is not whether you should implement it, but why you haven’t implemented it yet. Throughout this article, you’ll realise that automating is essential for delivering consistent quality to your users; it will help you ensure that excellent and bug-free functionality is a standard feature and not a secondary consideration.

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Table of Contents

Why automate mobile regression testing? 

Mobile regression testing automation does offer compelling benefits if you’re looking to streamline your current testing process. Maybe you have developers coding individual tests – maybe you even have real users on real devices beta testing new releases. Of course, manual testing has it’s place, but automation beings about consistency, efficiency and coverage that manual testing simply can’t guarantee; automated tests are immune to the variability of human input and can be run any number of times with consistent accuracy.

So, let’s touch briefly on some of the most effective and compelling aspects of automating regression testing in your mobile apps and games:

Automation = efficiency. Automated tests breeze through extensive testing cycles in a fraction of the time than manual testers could accomplish. This frees up your developers to innovate and problem-solve, not slave away in front of a device trying the same functionality over and over again and trying to break it.

Automation provides super-consistent accuracy. We’re all human, and unfortunately humans make mistakes, get bored, misunderstand the task, etc. This is a variable you simply can’t eliminate when using human testers – it’s just inevitable. Automated tests always deliver the same input and track the same outcomes, making your results infinitely more dependable.

Automation allows for parallel device testing. A well implemented automated regression test for your mobile app allows you to test across devices and platforms simultaneously, and more importantly, quickly. If you have marketing and launch teams pressuring you for a speedy GTM, automated testing is going to provide you with a much greater chance of your app’s new version shipping on time.

Automated tests integrate seamlessly with CI/CD. Automated testing fits perfectly into CI/CD pipelines, offering real-time insights with each code commit – upholding quality and accelerating the development cycle.

 

Planning for Automation – Choosing the Right Tools and Setting Up the Automation Environment 

Planning 

Successful automation testing begins with detailed planning. You cannot just implement a tool and expect it to provide you with any kind of meaningful output unless you take the time to configure it. You need to consider how to identify which test cases to automate, focusing on those that will yield the most significant benefits. Some criteria you may want to focus on includes:

Areas of high risk: Target tests that exercise parts of the app that are mission-critical or areas that are more susceptible to high-impact failures – for example, user authentication and login pages, data syncing components (specifically if there’s a need to sync data with a cloud service) and any integration with a third-party external service such as social media sharing, mapping services or advertising platforms.

Features that are used frequently: Focus on functionality that users interact with most often, ensuring that these experiences are flawless. For example – extensive testing of search functionality, content feeds, notifications or user profile management would go a long way to ensuring an excellent user experience.

Historical Defects: Prioritise areas with a history of bugs to prevent recurrence. Recurring issues significantly impact user trust, and prioritising these areas for testing helps to maintain user confidence in your app.

Areas key to monetisation: Obviously the last thing you want is someone having trouble making an in-app purchase or subscribing to the premium version of your app. Make sure you allow for significant and thorough testing of these areas of your app or game.

When determining the scope of automation, consider the size of your team and the resources available to them – for example, how would your team cope if you ran a regression test that threw up major issues with payment gateways and user login systems? As the game or app grows, the automation suite should be able to grow with it without requiring rebuilding from the ground up. A well-scoped automation strategy avoids overextension and ensures that the most critical aspects of the app are covered.

 

Selecting the Right Tools 

The tools chosen for automation can make or break the efficiency and effectiveness of your testing efforts. When selecting these tools you should consider:

Language Support: Ensure the tool supports the programming languages and frameworks your teams use. For example if you want to launch on Android AND iOS (most developers do) it’s absolutely pointless to buy a tool off the shelf that can only cope with one. You should pick one (like T-Plan) that can perform regression testing on both versions at the same time.

CI/CD Integration: This is crucial and will help streamline your development process – look for a tool (like T-Plan) which is able to integrate into your existing continuous development pipeline.

Customer Support: Robust customer support can be invaluable for resolving issues and learning best practices. What you don’t want is your developers scouring StackOverflow or using ChatGPT when something goes wrong – you need to be able to speak with someone with the required knowledge immediately.

Tools like Selenium or Appium (there are lots of others out there) are known for their wide adoption and flexibility, while T-Plan Robot stands out for its suitability in mobile environments. T-Plan Robot, in particular, is designed to alleviate much of the heavy lifting associated with mobile test automation, backed by exemplary customer support to assist teams in achieving their testing objectives.

 

Setting Up Your Test Environment 

A test environment that accurately reflects the production environment is crucial for reliable automation. This setup ensures that tests can anticipate and mimic the conditions under which end-users will operate the app.

Production Parity: Aim for parity with the production environment in your test setup. Including configuring backend services, databases, and networking to match the live settings as closely as possible.

Device and OS Diversity: Encompass a wide array of devices and operating systems. This reflects the fragmented nature of the mobile landscape and is critical for validating app performance across the spectrum of user conditions.

Emulators vs Simulators vs Real Devices: It’s important to understand the difference between these three different types of testing environment.

Emulators are all about mimicking the hardware and the software. It’s extremely difficult to do this on an Apple environment, and while emulation is very true to life and offers an accurate testing playground, it can be difficult and time-consuming to set up. Emulators provide a great first line of testing particularly for UI and functionality checks.

Simulators mimic the device and the environment, but not the actual hardware. It’s again very difficult to simulate on an Apple environment, and as mentioned it does nothing to imitate the hardware environment of an Apple device.

Real devices are just that – real Android or Apple devices that allow you to see how your app functions on the device just like a user would. Real device testing is indispensable for performance and user experience validations, but can be tricky to scale up.

On-Premise vs Cloud Testing: On premise testing environments provide control and security, making them ideal for sensitive or advanced testing scenarios. Cloud-based testing services can complement this by offering scalability and access to a vast selection of devices and OS versions.

Curious to see how an on-premise testing environment can automate your app’s regression testing, saving you time and money? Check out a completely free demo of T-Plan using the link below.

 

Best Practices in Scripting – Writing Automated Test Scripts 

Writing effecting automated test scripts is crucial for ensuring the reliability and robustness of mobile applications. Below are some of the best practises in scripting that can help enhance the efficiency and effectiveness of your automation tests.

Modular Scripting. Break down your test scripts into smaller, reusable modules or functions that perform specific tasks. This approach not only make the scripts easier to maintain but also allows for greater flexibility in test design.

Code Reuse. Aim to reuse code as much as possible. This reduces redundancy and helps in maintaining consistency across different test scripts. Common functions like login, navigate, and cleanup should be written once and called as needed.

Data-Driven Testing. Implement data-drive testing techniques where test data and parameters are externalised from the script. This allows for easy updates to test cases without modifying the code and enables running the same scenario with different data sets. This approach enhances the test coverage and minimises the effort required to manage test cases, as data can be pulled from databases, files or even generated on the fly.

Utilising AI. Leverage AI capabilities to optimise test scripts and identify potential areas of improvement. AI can help in predictive analysis, predicating future failures based on historical data. It can also be employed to dynamically adjust test scripts based on the applications behaviour during runtime, resulting in improved accuracy and relevance of the tests.

T-Plan Robot: A GUI-Driven Tool

Let’s visit a hypothetical testing scenario. Let’s say you were using a Selenium WebDriver test using the ‘unittest’ framework in Python to automate browser interactions for your web app. Here’s an example script that you would have to code up, test and implement to, for example, test the login function of your app. from selenium import webdriver
				
					import unittest

class LoginTest(unittest.TestCase):

def setUp(self):
self.driver = webdriver.Chrome()
self.driver.get("https://example.com/login")

def test_login(self):
driver = self.driver
username_field = driver.find_element_by_id("username")
password_field = driver.find_element_by_id("password")
login_button = driver.find_element_by_id("submit")

# Data-driven part
username_field.send_keys("testuser")
password_field.send_keys("testpass")
login_button.click()

# Verify login success
assert "Dashboard" in driver.title

def tearDown(self):
self.driver.quit()

if __name__ == "__main__":
unittest.main()
				
			

This is only an example script – depending on your specific app, this might need to be much more detailed and involved. And, consider that this is only a test of the login function on one page – every test case and criteria would have to be defined, tested and manually coded in order to be able to successfully test each individual component of your app.

The T-Plan Robot differentiates itself by being primarily GUI-driven, significantly reducing the need for script coding like the above. It is ideal for teams looking to automate their testing processes without extensive coding.

T-Plan Robot’s approach allows testers to create automated test scripts through a more visual interface, where actions are defined by what is seen on the screen rather than through code. This speeds up the script creation and makes it more accessible to team members with less extensive coding skills.

Running Automated Testing Tools, Managing and Analysing the Test Results

The true value of automated testing is realised when it becomes an integral part of your CI/CD pipeline, providing continuous feedback and validation as developers integrate new code. Automated tests can be triggered by various events, such as new commits or merging of branches. Continuous testing within CI/CD pipelines ensures that each change is validated for functionality, performance and security and also reinforces a proactive culture of testing within the development team.

The frequency of automated tests should be aligned with the development pace and project needs. High-frequency deployments benefit from per-commit testing, whereas nightly builds might be more appropriate for projects with longer release cycles. Setting up a schedule for automated testes ensures a consistent and regular cadence of testing.

Test Data Management and Interpreting Results

Creating realistic and scalable test data is critical for simulating real-world scenarios and validating application performance under various conditions. Handling sensitive information within testing data raises data privacy concerns so it is imperative to anonymise personal data and comply with data protection regulations to maintain user trust and meet legal requirements

Analysis and interpreting test results goes beyond pass or fail statuses. It requires a detailed examination to understand the root cause of failures and the implications for the application. Using the insights from test results you are able to refine and improve test scripts and approaches. This continuous process involves adjusting test parameters, enhancing test coverage, and optimising scripts for efficiency and effectiveness.

Challenges and Solutions

Like in all things, teams often encounter common yet difficult challenges when it comes to automating mobile regressing testing.

One of the biggest pitfalls many developers fall into is seeing inconsistent results from their testing tool, leading them to waste time investigating false alarms (we call this “flaky testing”. A lot of this can be avoided by adding appropriate wait times, using more reliable locators and assertions and regularly cleaning up test scripts to remove anything outdated or redundant.

Another huge consideration is device fragmentation. The huge range of mobile devices out there means developers have much to consider to ensure their tests are as comprehensive as possible. You can get around this by using a combination of real devices and emulators – real devices for final validation, and emulators for coverage across different OS versions and screen sizes.

Test execution time can be a problem – to the point where testing may have been pretty rapid to begin with, but several hundred commits or nightly builds later and the test automation takes several hours to run. Tests should be run in parallel – breaking down tests into smaller independent units can run concurrently allowing faster feedback. You should also be prioritising tests based on the risk and impact of changes, helping focus your team’s efforts where they’re needed most.

Adopting Automated Regression Testing with Your App Using T-Plan Robot

The integration of tools like T-Plan Robot into your development process represents far more than a mere upgrade in your testing capabilities. It’s a shift towards more efficient workflows, resource optimisation, and a commitment to product quality.

T-Plan Robot will help you reduce development cycles and free up valuable resources, allowing focus on strategic activities like feature development and product enhancement – which is fundamentally what all development teams should really be striving for.

T-Plan is also capable of being integrated into CI/CD pipelines and running tests in parallel for seamless automation. As we’ve discussed, this reduces variability in human input and increases development speed of growth. Additionally, the user-friendly interface is accessible for testers of varying backgrounds, allowing broader collaboration and understanding across the team.

Further resources

  1. Understand the capabilities, features and how to get started with T-Plan Robot: T-Plan Robot Documentation
  2. Automated Testing Best Practices: Continuous Testing in DevOps, Best Practices for Automated Testing
  3. Mobile Testing Strategy: 5 Best Practises to Master Mobile App Test Automation
  4. Books on Automated Testing: “Experiences of Test Automation: Case Studies of Software Test Automation” by Dorothy Graham and Mark Fewster” “Continuous Delivery: Reliable Software Released through Build, Test, and Deployment Automation” by Jez Humble and David Farley.

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