Critical mistakes when automating test cases

With the widespread use of test automation, businesses are increasingly relying on it to test their systems and applications on a regular basis. However, only a small percentage of businesses and test automation professionals are able to profit from test automation. We’ve compiled some of the common errors that testers make, which are the cause of test automation failure and decreased ROI.

What are the critical mistakes while automating test cases?

Companies employ test automation because it automates time-consuming app testing activities. Regardless of its use, automated testing has significant drawbacks. QA teams often make errors that jeopardize overall success. Here’s a rundown of the most typical test automation blunders.

1. Not choosing the correct approach for testing

It is very important to know which type of test technique you need to apply. Test automation is a great way to save time for testing, but it should never be used in place of manual testing. Ineffective testing might stem from not employing manual testing at all. The difference between automation and manual testing is analogous to the difference between driving and walking. 

Driving a vehicle is, in most situations, the most efficient and quickest alternative. There are, however, certain sites that cannot be accessed by automobile due to the lack of a road. Similarly, automated testing is cost-effective and time-saving in certain circumstances, but not others. The most effective technique is to use a mix of automated and manual testing to support one another.

2. Choosing unsuitable tools

The fact that a large selection of instruments is available for any budget does not imply that you should get as many as possible. Indeed, having so many tools might influence your decision-making and lead to incorrect tool selection. Because the sorts of problems that automated testing may address are so diverse, there is no such thing as an all-purpose instrument that can handle all of them. To guarantee that you choose the right tool for the job, start by defining the issues you wish to solve. 

Knowing which tool to pick makes it much simpler to choose the appropriate tools. Analyzing project development processes, whether the emphasis is on quality assurance or quality control, and assessing team member abilities are the best ways to prevent incorrect tool selection. Otherwise, you run the danger of introducing the incorrect tools to the team. It will take extra time to get accustomed to the toolset if it is not suitable for the team’s expertise.

3. Record and playback features

The majority of modern tools include built-in record-and-play features. These capabilities enable testers to create automated scripts for various scenarios in a short amount of time. However, the biggest trap is: these automation algorithms are built on static data. Because the validations are not recorded, the testers must log and examine any change. This may result in the loss of dynamic data. Engineers are unfamiliar with the project’s automation approach at the start of the test automation process.

As a result, they may use the record and playback functions. Record and playback testing should ideally only be used to develop skeleton scripts, with the final level of automated testing carried out without it. The record and playback tool’s primary drawback is that it creates complicated scripts that are difficult to maintain. On the other hand, successful automated testing needs simple scripts that everyone on the team can understand and maintain.

4. Inadequate test validation

Data verification is an important aspect of the testing process. Failure to verify scenarios at various levels is a common blunder made by testing engineers. This may result in a slew of issues with functioning. The most typical issues with test validation are listed below.

• Many teams struggle with the creation and use of scripts that haven’t been validated. To guarantee that all conceivable mistakes are covered, checkpoints should be set in as many locations as feasible. They aid in the detection of any changes in a data source over time. This is particularly critical when working with databases since there are so many variables.
• The user interface (UI) functions may seem to operate pretty well at first sight. However, problems in the database might arise on the other side of the site. Insufficient data integrity, for example, may lead to large-scale system failures. As a result, test automation programs must be written to assess functionality at all levels, not only at the UI level.

5. Inappropriate test cases

Creating a test automation case with clear objectives and financial rewards will assist you in deciding where to focus your efforts. Incorporating defined Return on Investment (ROI) goals into your IT strategy can help both your stakeholders and your company as a whole. In addition, test engineers make errors while creating test cases, resulting in ineffective test cases. As a result, these test cases do not reflect an application’s flow or functionality.

What are some automation testing trends?

Everyone has begun transferring things over to software and applications as the only way to connect with external and internal stakeholders and teams in this era of accelerating digital transformation. As a result, the requirement for automation testing required has grown. Now we will go through the most prevalent automated testing trends, so you can get the most out of this procedure.

1. Cloud-based testing

Cloud-based testing entails evaluating software using cloud-based resources. After migrating to the cloud, cloud software testing is required, and cloud testing is achievable with any public, private, or hybrid cloud. Cloud-based collaborative testing technologies enable testing specialists in different locations to split their work between themselves by establishing tasks and prioritizing them in order to accomplish testing efficiently and on time. Cloud-based automation testing will cover the following topics:

• Cloud testing through a network.
• Includes features, end-to-end functioning, browser compatibility, and production process with cloud testing.
• It examines the coverage of data flow control over a variety of networks with varying bandwidths, as well as the data transfer’s success.
• Cloud testing based on infrastructure.
• Focuses on failure recovery and storage rules and secure network connections.
• Cloud-based application testing.

2. Machine Learning (ML) and Artificial Intelligence (AI)

Artificial Intelligence (AI) is a computer science methodology that employs intelligent computers to perform activities without the need for human intervention, using various and huge datasets to learn about the software. It has several advantages in the realm of software automation testing, including.

• It aids unit testing by collaborating with RPA, an AI-based technology that allows users to develop automated processes for any job.
• By interpreting the application’s observation and generating the data set to train the model for the application’s behavior in particular instances, ML/AI algorithms assist in the creation of the most often used test cases and scenarios.
• According to studies, machines are better at remembering visual patterns. As a result, ML/AI machines will aid in the development of GUI and visual testing jobs.

3. IoT and Big Data Testing

The Internet of Things is commonly referred to as the IoT. It is a branch of science that connects internet connectivity to everyday objects like voice controllers, air quality monitors, wireless high-speed internet, electric farming equipment, connected appliances,  smart factory equipment, wearable health equipment, smart home security systems,  biometric cyber-security scanners, wireless inventory trackers, and more. The following are the most significant tests in IoTs:

• Testing for security and connection.
• Testing of the network.
• Integration testing.

4. Risk Compliance Testing and Cybersecurity

As people’s digital skills improve, so do the number of cyber threats they face. Security encompasses not just transaction security but also the privacy of end-to-end users. Because the digital world is growing at a rapid pace, cyber-attacks will become more common in the future years. Enhancements to security testing methodologies will continue to be a hot issue for many more years.

5. Autoscaling CI/CD

The monolithic method of the CI/CD pipeline build is implemented using just one development branch. Assume a flaw or glitch creates delays in delivering a product or application, necessitating extra application modifications to remedy the problem. To address this problem, autoscaling of CI/CD parallels the execution of numerous feature branches with a developed branch. The grid-scale hub raises the number of nodes in use and activates the hub’s connection based on the number of tests running under the pipeline. Such pipeline autoscaling will result in a significant boost in the testing results for a given application.

Tips to improve test cases

Software testing requires a well-thought-out set of organizational activities. These activities comprise a test plan that may be modified based on the work and the deadline. Here are some ideas to make significant progress in your software testing procedures in order to get the most out of software testing:

1. Allow someone to run the team. Having someone in charge also implies that the rest of the test team is responsible to that person. This QA manager should be in charge of monitoring test data, having frequent meetings, and advising the agile team on how to proceed. They may be the point of contact for software developers, stakeholders, and the QA testing team if and when issues occur.
2. Enhance the integration in your QA team through effective communication. Look for ways to include the team in the development process as soon as feasible. This is especially crucial for teams that use agile and continuous integration approaches.
3. Automation makes a difference in terms of workflow and efficiency. Find techniques to automate the repetitious tests and don’t need the use of a human eye. You do not have to spend money automating everything. That would be a massive project, requiring much too much time to create scripts and tests, as well as continual monitoring. Concentrate on tiny, rapid victories and functional testing instead. Remember to hire a test automation engineer and buy extra servers later.
4. Using crowdsourced testers to enhance your testing resources is not very intelligent. You don’t have to recruit new staff since you have direct access to individuals who can do functional exploratory testing. As a result, you won’t require a huge crew in the early stages, but you’ll be able to easily expand up as you come closer to product delivery. It’s a terrific approach to quickly receive a large number of test results. Finally, this may assist in enhancing your software’s usability and functionality for end-users.
5. A shorter release cycle necessitates regression testing and management. You don’t want to get to the end of a project only to discover that the most recent few modifications have damaged something vital. You and your team may take concrete measures, such as upgrading test design, if you and your team have a strong knowledge of the product that potentially encounters regression. It’s time to conduct another set of regression tests whenever new features are implemented. Your QA team won’t need to conduct a complete test to achieve appropriate test coverage since you’ve identified the software components that potentially encounter regression.

It’s important to note that automation can only save time on specific kinds of tests. Automating all of the tests without a strategy or sequence will result in large scripts that are difficult to maintain, often fail, and need a lot of human intervention. Furthermore, automation scripts may become outdated as goods evolve, necessitating periodic reviews.