Comparing Autonomous Testing to Traditional Methods

Typical modern software development lifecycle testing includes large amounts of automated testing and some manual testing. Due to recent advancements in AI and machine learning, autonomous testing is becoming more popular. In this article, we will compare autonomous testing to traditional testing methods in terms of time to test, coverage, cost, effectiveness, and what challenges each has.

Comparing testing methods

Automated testing

Unit Testing

Unit tests form the cornerstone of all automated software testing. Software developers write unit tests to test individual components of the software. Unit tests cover the smallest testable parts of the software, usually functions or methods, UI or backend. Unit tests are highly effective for regression testing because they run quickly and efficiently. Additionally, when a unit test fails, it is typically easy to diagnose and resolve.

Api Testing

API tests are used to test the communication between different parts of the software, they typically test the backend and database. API tests cover higher-level functionality than unit tests, and are still relatively easy to write and maintain. However, API tests can be more difficult to reason and resolve than unit tests, as they cover more complex functionality.

Specialized Testing

Integration, performance, and security tests are specialized tests that cover specific aspects of the software. These tests are typically more complex and time-consuming to write and maintain than unit and API tests.

End-to-end testing

End-to-end tests are used to test the software as a whole, from the user interface to the backend and database. These tests are typically implemented using a tool like Selenium or Cypress, which can simulate user interactions with the software. End-to-end tests cover the highest level of functionality, but are also the most difficult to write and maintain.

Manual testing

Manual testing is usually the last step in the testing process, and is used to test the software as a whole. Often this step is left to the QA team, or domain experts, who are responsible for ensuring the software meets the requirements. Typically manual testing phase is labeled as acceptance testing, as it is used to determine if the software is ready for release.

Autonomous testing

Autonomous testing is a new approach to software testing that uses AI and machine learning to automate the testing process. Autonomous testing agents can work 24/7, and run multiple different testing in parallel. Unlike other testing methods, no test cases are planned before the execution. This makes the approach interesting as the agent can notice issues that were not thought at all during the development process.

Are you finding a high number of issues using manual testing? That might be an indication of issues earlier in the software development process. Autonomous testing can help you find these issues earlier and provide relevant feedback for the R&D team.

At AutoExplore, we are committed to helping R&D teams implement autonomous testing as part of their development processes. Ready to transform your process? Contact us for a demo to learn more.

Sampo Kivistö, Founder & CEO

Sampo Kivistö

Tel. +358 452733080