Challenges in Test Automation [with Tips to Overcome]

Challenges in Test Automation [with Tips to Overcome]

This article will cover all the challenges in test automation that you may face during your software testing journey!

Test automation is a critical component of software testing. We can speed up the software validation process and increase testing coverage by using automated testing. 

However, there are numerous difficulties in implementing test automation. For example, without overcoming these obstacles, testers may face a slew of nightmares that could lead to the failure of automated software testing. 

mobile app automation

The purpose of this topic is to outline the top challenges in test automation that have the most significant impact on the overall test effort and project success. 

Hopefully, the earlier these challenges are recognized, the better-prepared solutions will be to deal with them.

Challenges in Test Automation:

#01 High Implementation Costs 

Automation increases testing velocity but necessitates a significant upfront capital investment. However, it is difficult to sell to management because a “payback” period can be unpredictable or lengthy. In some cases, it may never happen at all. 

This is especially true if best practices aren’t followed, including capturing data that measures the value created by additional internal team productivity and enhanced product performance.

The most important way to ensure a positive ROI after comprehensive testing automation is to execute an automated testing solution it integrates with other products in the ecosystem. End-to-end features, such as robust analytics measured in near real-time, can be enabled as a result. 

The speed index is one such metric that can be derived, and it tells users how long it takes for their application to load, including on-page elements that populate in real-time. 

The ability to test these factors and aggregate performance across all stages of development allows for better changes to be released more quickly.

#02 Ensuring Adequate Test Automation Coverage

One of the most commonly used metrics for measuring test automation success is code coverage. It assesses how source code is executed when a test suite is run. The greater the coverage, the less likely it is that unnoticed bugs will enter production.

Because code is continuously integrated, critical tests for a specific requirement may be missed. Unexpected code changes can also result in inadequate test coverage during automation.

The infrastructure is one factor that can help ensure the appropriate amount of coverage. When testing applications against multiple browsers and operating system combinations, test scripts must run in parallel to run each test against the configuration in a reasonable amount of time. The infrastructure must support the parallelization strategy.

#03 Selecting a Proper Testing Approach

Automation tests necessitate the right tool for creating scripts and the right testing approach. This is one of the most challenging tasks for test automation engineers. Therefore, testers must find an appropriate test automation approach from a technical standpoint. 

To do so, they must answer several critical questions: How can we reduce the time and effort required to implement and maintain test scripts and test suites? For example, will automation test suites last a long time? How can I create useful test reports and metrics? 

With the recent adoption of Agile development, the application under test frequently changes during development cycles.

As a result, how should automation test suites be designed and implemented to correctly identify these changes and keep up-to-date quickly with minimal maintenance effort? 

It is preferable to have a test automation solution to detect these issues and automatically update and re-validate the test without human intervention. However, it is undeniably challenging to address these difficult questions.

#04 Effective Communicating and Collaborating in Team

This may be a challenge not only for test automation teams but also for manual testing teams. It is, however, more complex in test automation than in manual testing because it necessitates more communication and collaboration within the automation team. Test automation is, indeed, an investment. 

To get the entire team involved in identifying test automation objectives and setting targets, we need to spend significant effort on communication, providing massive evidence, historical data, and even doing a proof of concept, just like any other investment. 

Furthermore, to have clear purposes and goals, we must keep the entire team on the same page.

Unlike manual testers, we, automation testers, not only discuss the plan, scope, and timeframe with developers, business analysts, and project managers, but we also discuss what should and should not be automated with manual testers, developers, and technical architects.

Furthermore, we must present the cost and benefit analysis and the Return on Investment (ROI) analysis to the upper management team. 

Without the management team’s support, the entire test automation effort will be jeopardized. As a result, effectively communicating and collaborating among these teams and others is a significant challenge. 

Ineffective communication and collaboration can quickly turn test automation experiences into nightmares.

#05 Test Script Issues

If QA teams lack coding skills, they may encounter various issues with test scripts. For example, teams dealing with these issues can use reusability (reusing test scripts) to solve the problems while maintaining their code. 

For example, they can improve code maintenance by treating test code as production code. Aside from that, periodic testing of the code, scheduling debugging sessions, and identifying critical issues with object identifiers should be performed.

#06 Demanding Skilled Resources

Some argue that test automation can be handled solely by manual or technical testers because many test tools already support easily and quickly recording and replaying test scripts. 

This is a central myth. Indeed, test automation necessitates the technical skills required to accurately design and maintain test automation frameworks, test scripts, build solutions, and resolve technical issues. In addition, automated testing resources must be well-versed in the framework’s design and implementation. 

Moreover, these resources must have strong programming skills and solid test automation tools to meet these job requirements.

However, how developers can write correct test scripts from the perspective of testers and end-users is a significant concern, even though they can quickly develop a piece of code following the test automation framework. 

Indeed, we can better use our resources within our test automation process. But, on the other hand, skilled resources are always crucial in test automation efforts.

Read Also: Myths Vs Facts of Codeless Test Automation

Challenges in test Automation While Using Selenium:

#01 Cross Browser Testing

It’s possible that our web application will respond differently in different browsers and that our website will run properly in Chrome but not in Firefox. Because there are so many browsers on the market currently, test automation on each one may not be practical. 

However, we must verify that the application under test is entirely compatible with the most widely used browsers, including Chrome, Firefox, Safari, Edge, and Internet Explorer. 

Testing on frequently used browsers is currently insufficient, and we may need to test on generally used browser versions and various operating systems and resolutions. Cross Browser Testing results from this method make test automation difficult for testers.

#02 Scalability

The most challenging aspect of automation is test scalability. Running testing on different browsers, operating systems, and resolutions, as mentioned previously, is something essential to do. 

For example, selenium WebDriver allows us to run tests in sequential order, but it does not provide an excellent approach to cross-browser testing. However, with time, an application under test may have many features, resulting in additional test cases, and running several test cases consecutively may become a headache.

To address this, Selenium has developed Selenium Grid, which allows us to test our web application on various browsers and operating systems. 

However, Selenium Grid can only help with Cross Browser Testing on the physical machines or browsers we have, making it difficult for testers to do automated tests on a large scale.

#03 Mobile Testing

Testing mobile operating systems is the next issue in Selenium testing for responsive design testing. This is a problem because many end-users consume material on their mobile devices. 

Appium, a testing framework from the Selenium family, assists developers in testing content on native mobile operating systems. In addition, Appium automates mobile app testing with the WebDriver protocol.

#04 Handling Pop-Ups

Although pop-ups are often discouraged in favor of simpler alternatives, those who do so may find it tiresome to create tests in Selenium to handle pop-ups automatically. 

While the browser can handle pop-ups with WebDriver, OS-based pop-ups are outside the scope of Selenium testing, making it one of the most significant restrictions of the tool. 

Therefore, the request to keep a downloaded executable file is an example of a non-browser-based pop-up.

Selenium does not allow native OS-based dialogue windows; you can utilize extensions to work around this limitation. Selenium, for example, can be combined with AutoIt, a tool for automating Windows-based user interfaces. 

For example, you may need to utilize a bridge between Selenium and AutoIt, such as Jacob COM bridge in Java, depending on the language you’re using to develop the script.

#05 False Positive and False Negative Results

False Positive and False Negative results have always been a headache for automated testers. False Positive refers to errors in our test cases even though the application under test is working correctly. 

But, on the other hand, false-negative findings refer to the situation in which our test cases pass, yet the program under test contains defects. Such ambiguity misleads the testing team and widens the gap in communication between the QA and development teams. 

For automation testers, dealing with flaky tests is a difficult challenge in and of itself. To combat this flakiness, we must ensure that test strategy, test cases, and testing environments are appropriately managed and organized.

#06 Limited Reporting

In the testing phase, reporting is crucial. Reports on tests serve as a link between developers and testers. However, Selenium doesn’t have a lot of reporting tools right now.

Automation testers encounter a significant issue in creating and updating reports.

We typically employ frameworks based on programming languages for improved code designs and reporting. For example, testNG and Gauge are two Java frameworks that generate relevant reports. Similarly, for Python, the Pytest framework can be explored.

#07 Synchronizing Events

One of the most common causes of our automation script’s failure is a lack of sync. When you expect an event to occur, sync difficulties may arise.

 However, it may be delayed or not take place, causing our test case to fail due to some unknown reason. For example, we expect a “accept/decline cookies” message to appear when we execute an automation script shortly after launching a website. 

Still, it may be delayed or not appear at all. This form of synchronization is what causes our test script to fail.

We usually employ waits defined in Selenium, such as Implicit wait and Explicit wait, to deal with this.

#08 Captcha or OTP Handling:

Captcha and OTP, as we all know, cannot be assumed or predicted because their values change every time they are created. 

For example, automation testers find it difficult to automate elements such as payment gateways, new user registration, and other services that require Captcha and OTP. 

This might also be seen as proof that an application cannot be fully automated and that manual testing is unavoidable.

#09 Not Keeping up with Changing Requirements

Developing an effective Agile testing strategy is critical, without question. But, if you think your strategy is foolproof and you’ll never need to change it, think again. Most teams squander a significant amount of time trying to develop the perfect Agile testing strategy.

Regardless of how much we’d like to achieve it, the truth is that there is no such thing as a perfect Agile testing plan. However, it is not possible due to the complex surroundings. You may need to make adjustments on an ad hoc basis at times. 

Alternatively, you may need to disable some programs. Overall, you must be flexible and adjust to changes in the sprint, bearing in mind that everything must match the sprint goal, and you will be ahead of all the Agile Testing issues.

#10 Test Script Issues

If QA teams lack coding skills, they may encounter various issues with test scripts. For example, teams dealing with these issues can use reusability (reusing test scripts) to solve the problems while maintaining their code. 

For example, they can improve code maintenance by treating test code as production code. Aside from that, periodic testing of the code, scheduling debugging sessions, and identifying key issues with object identifiers should be performed.

Read Also: Myths Vs Facts of Codeless Test Automation

What are the challenges faced in API testing?

#01 Initial Setup of API Testing

Manual testing helps confirm whether or not something works. Automated testing along with APIs to determine how well it performs under pressure. 

Getting the testing infrastructure running properly is frequently one of the most challenging parts of the process, not because it is difficult, but because it can be a significant demotivator. 

However, if you can motivate your team to complete the process, it will pay off in the long run.

#02 Updating The Schema of API Testing

Schema is the data formatting that handles requirements and requests for the API and must be maintained throughout the testing procedure. 

Therefore, any changes to the program that add new parameters to the API calls should be reflected in the schema configuration.

#03 Sequencing The API Calls

In many cases, API calls should appear in a specific order to function correctly. For example, the testing team is now faced with a sequencing challenge. 

For instance, the request will fail if a request to return a user’s profile information is made before the profile is created. Instead, a call to create a map must be executed before placing location pins on the map to work correctly. 

When working with multi-threaded applications, this process can become increasingly difficult.

#04 Testing Parameter Combinations

APIs facilitate system communication by assigning data values to parameters and passing those parameters through data requests. To test for problems related to specific configurations, it is necessary to test all possible parameter request combinations in the API. 

For example, two different values could be assigned to the same parameter in a larger project, or numerical values could appear where text values should be. For example, adding a new parameter exponentially increases the number of possible combinations.

#05 Validating Parameters

Validating the parameters sent via API requests may also be difficult for testing teams. However, it can be a daunting task due to many parameters and use cases. 

The team must ensure that all parameter data is of the correct string or numerical data type, fits within length constraints, falls within a specified value range, and meets other validation criteria. 

For example, phone numbers in the United States should be in the 10-digit format, and returning a 5-digit zip code should result in an invalidation error.

#06 Tracking System Integration

It is essential to ensure that the API testing system communicates appropriately with the data tracking system. This is required to get accurate feedback on whether or not a call is working correctly. 

It’s also used to monitor API performance in the background. Because this step may occur late in the process, the team may be too exhausted to give it the attention it requires.

API testing is a critical component of application development in today’s business environment. Contact Apica today if your company is looking for the tools and expertise to thrive with API implementation.

challenges in test autmation

Challenges in Agile Testing: 

#01 Resource Management

The Agile approach necessitates a diverse set of testing skills, such as defining ambiguous scenarios and test cases, conducting manual testing alongside developers, writing automated regression tests, and executing automated regression packages.

More specialized skills will be required to cover additional test areas such as integration and performance testing as the project progresses.

An appropriate mix of domain specialists should plan and gather requirements. The hard part of resource management is locating and allocating test resources with multiple skills.

#02 Selecting The Right Tools

Traditional, test-last tools with record-and-playback capabilities compel teams to wait until the software is complete. 

Furthermore, traditional test automation tools do not work in an Agile context because they solve conventional problems that are not the same as Agile Automation teams’ challenges.

Automation testing is typically tricky in the early stages of an agile project, but as the system grows and evolves, some aspects settle, and it becomes appropriate to deploy automation. As a result, selecting testing tools is critical for reaping agile’s efficiency and quality benefits.

#03 Inadequate Test Coverage

It’s possible to miss crucial tests for any requirement with continuous integration and changing needs. 

Connecting tests can minimize this to user stories to understand test coverage better and monitor specific metrics to find traceability and missing test coverage. Another reason for the lack of test coverage is code changes that were not anticipated. 

To avoid this, source code analysis is required to identify modules that have been modified and to ensure that every modified code has been thoroughly tested.

#04 Inadequate API Testing

Most software now has a service-oriented architecture (SOA) that exposes APIs to the public so that other developers can enhance them. Because of the intricacy of API testing, it’s easy for those of us who create APIs to overlook it. 

Unfortunately, many testers cannot test APIs because they require considerable coding expertise. 

However, some technologies allow testers to test APIs without having coding solid abilities, which is a great approach to verify that these services are thoroughly tested.

#05 Performance Issues

The complexity of software typically grows as it matures. For example, complexity adds more lines of code, which leads to performance issues if the developer is not concerned with how their changes affect end-user performance. 

To solve this problem, you must first understand which parts of your code are causing performance issues and how performance changes over time. 

Load testing tools can assist in identifying slow areas and tracking performance over time to more objectively document performance from release to release.

Conclusion:

Testing automation can be both difficult and costly. However, the outcome may be better products in customers’ hands faster, with improvements delivered more frequently. 

Using value stream mapping and analytics, rather than just automation, can empower an organizational culture where results are constantly improving rather than simply moving faster.

With TestGrid, automation becomes easier and solves most of the problems mentioned in this blog.

Click here to know more about TestGrid.io, and also, to read more articles, you can head over to our blog section.

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