In any agile development team, test automation is an absolute must as it enables faster and more frequent delivery of software. But, automation has its own set of difficulties. The complexities can be broadly classified into 3 verticals

Technical Complexity

One of the primary sorts of difficulties that testers may run against while adopting test automation is technical complexity. To address technical complexity in test automation, testers may need to invest in training and education to develop their programming and technical skills. They may also need to work closely with developers, DevOps engineers, and other technical stakeholders to ensure that the automation is properly integrated with the application and other systems. Using automation tools and frameworks that simplify technical complexity can also help to make the testing process more efficient and effective. Let us look at some example of what constitutes technical complexity

Object-oriented programming: Test automation often involves writing code in object-oriented programming languages like Java, Python, or Ruby. Object-oriented programming can be complex, especially for testers who are not familiar with programming concepts like classes, inheritance, and polymorphism. Are these concepts mandatory to be learned? The answer is “YES” if you intend to pursue a long-term career in testing. In order to become better at programming, you must dedicate time to understanding all the fundamentals.

Web technologies: Many modern applications are built using web technologies like HTML, CSS, and JavaScript. Test automation often involves interacting with these web technologies, which can be complex and require knowledge of web development.

API testing: Since APIs power, all contemporary apps, failing to prioritize API testing will prevent you from being a successful test engineer. Because there is no fancy UI to visualize or interact with, APIs are inherently boring. Yet, there are several licensed and open-source tools available right now that allow you to visualize how APIs function as a whole.

Integration with other systems: Test automation often involves integrating with other systems, such as databases, web servers, and CI/CD pipelines. Integration can be complex and require expertise in areas like system administration and network configuration.

Test Complexity

Test complexity refers to the level of difficulty involved in testing a particular aspect of an application. Some types of testing are inherently more complex than others due to factors such as the size and complexity of the application, the nature of the testing being performed, and the tools and technologies being used.To address test complexity in test automation, testers may need to invest in specialized tools and expertise for different types of testing, such as load testing or security testing. They may also need to collaborate closely with developers and other stakeholders to ensure that the testing is comprehensive and effective. Using testing frameworks and methodologies that simplify test complexity can also help to make the testing process more efficient and effective.

Let us look at some examples of what constitutes test complexity

Data-driven testing: Data-driven testing involves testing an application with multiple sets of test data to ensure that it functions correctly under a variety of conditions. Data-driven testing can be complex due to the need to generate and manage large amounts of data, as well as the need for specialized tools and expertise

Security testing: Security testing involves identifying and testing potential security vulnerabilities in an application, such as cross-site scripting (XSS) or SQL injection. Security testing can be complex due to the wide range of possible vulnerabilities and the need for specialized tools and expertise.

Load testing: Load testing involves simulating high levels of traffic or users on an application to identify performance bottlenecks and other issues. Load testing can be complex due to a large amount of data and traffic involved, as well as the need for specialized tools and expertise.

Exploratory testing: Exploratory testing involves testing an application with little to no pre-defined test cases or scripts. This type of testing can be complex due to the need for testers to have a deep understanding of the application and its potential use cases, as well as the ability to adapt and respond to unexpected results.

Maintenance Complexity

Maintenance complexity refers to the level of difficulty involved in maintaining and updating automated test scripts over time as the application or testing requirements change. As applications evolve and change, so must the automated test scripts that are used to test them. Maintaining and updating these scripts can be a complex and time-consuming process.To address maintenance complexity in test automation, testers may need to invest in tools and methodologies that make it easier to maintain and update automated test scripts over time. For example, using modular test scripts that can be easily updated and reused can help to reduce maintenance complexity.Additionally, using automation frameworks and tools that are flexible and adaptable can help to make the testing process more efficient and effective.

Some examples of maintenance complexity in test automation:

Changes to the application: As an application evolves and changes over time, the automated test scripts used to test it must also be updated. This can be complex, especially if the changes to the application are significant and require changes to many different parts of the test scripts.

Changes to the testing environment: Changes to the testing environment, such as changes to the hardware, software, or network configurations, can also impact the automated test scripts. Maintaining these scripts can be complex, especially if there are many different testing environments to consider.

Changes to the automation tools: As automation tools and frameworks evolve and change over time, the automated test scripts that use them must also be updated. This can be complex, especially if the changes to the automation tools require changes to many different parts of the test scripts.

Script maintenance overhead: Maintaining test scripts can be a resource-intensive process that requires significant time and effort. This can be complex, especially if the test scripts are not well-organized or well-documented.