Artificial Intelligence (AI) and its subset technologies is used across industries to leverage the advantages of speed, accuracy, and lower human effort, all in the pursuit of advancing innovation. Software development and testing also use AI in several processes, especially in spaces where manual effort can be significantly reduced and directed elsewhere.
The use of AI based tools and processes in software testing makes the QA process smarter and more efficient. Changing consumer needs and demands and a shift to a more digital-first economy has created massive scope for software development, and in turn, software testing. With improved business outcome and customer satisfaction, there is growth of business.
Software testing is the process of subjecting a new software or a new version of its release to various functional and non-functional tests to ensure that it performs the way it is supposed to. The use of Artificial Intelligence in software testing greatly aids this QA procedure.
Software testing is a rigorous procedure, and with most technology organizations adopting agile methodologies in their software testing life cycles, QA has become a continuous, constant process. Therefore, manual testing by humans, which can take a lot of time may not be an optimal use of resources to meet delivery deadline. This is where automation comes into play, and has been in use for a while now. Automation is a process that uses pre-programmed rules to test software, but the rules need to be changed every time the software requirements change. However, incorporation of Artificial Intelligence in test automation makes the process highly efficient and seamless.
Artificial Intelligence enables a machine to develop thinking and understanding similar to human beings. It uses pre-programmed data sets to solve new problems intelligently. A subset of this technology, known as Machine Learning (ML) uses algorithms to understand problem solving by learning from the data and be able to solve problems that may be similar. Yet another subset of AI is Deep Learning which strives to mimic human thinking through a concept called neural networks, much similar to those in the human brain.
AI/ML in software testing:
Artificial Intelligence based algorithms are able to mimic human intelligence and Machine Learning helps the system to learn from given data sets. The primary way in which Artificial Intelligence in software testing is used is through pattern recognition and decision making based on the same.
- AI based data analytics in software testing: Software testing is a meticulous and continuous process with a large amount of test cases being deployed for each new version of a software to ensure that there is no error after release. This leads to the generation of a large amount of data that has to be analyzed to make sense of the test results and to share feedback with the development team. AI tools can help in data categorizing, and even in identifying testing errors like false negatives, aiding the analysis and decision making process of the testers.
- Visual validation: In case of UI testing, if there are changes in the visual aspects of the software or application, AI tools can quickly recognize changes without human aid and detect visual bugs. With the help of pattern and image recognition abilities, AI tools can map the application and verify elements without the need for further coding by human testers.
- Self-healing tests: Increasing number of objects and identifiers on application pages requires constantly updating object locators for testers to ensure that the testing goes smoothly. AI tools with self healing capabilities are able to automatically detect the changes in objects and update with new attributes to ensure that the design test cases function properly. Automating such processes with the help of AI greatly saves on time and improves efficiency.
Benefits of AI in software testing
AI based tools have brought about a host of benefits in software testing and supporting QA excellence. It supports software testing life cycles at almost all stages and is only improving in efficiency as testing needs elevate. Technology enterprises across the globe adopt some or other form of AI tools in their software testing processes.
- Quicker launch and time-to-market: AI tools extensively used in the continuous software development and testing cycles. Supporting a large number or QA processes ensures quicker releases to end users.
- Low errors: In software testing processes, AI tools detect bugs quickly, and helps testers correct defects easily, and release error-free products.
- Time and resource efficiency: AI tools easily conduct large number of repetitive tests in a shorter amount of time, preserving the energy and effort of human resources to be used productively elsewhere.
AI testing for software has a large number of benefits and has a large number of advantages compared to manual or even automation testing. However, it is important for testers to have the right set of skills and experience to make use of AI tools for software testing in the most optimal way.
With an in-house team of skilled software testers well versed in the latest QA practices, Qualitrix can support all your software testing requirements for your mobile or computer software. To know more, visit – www.qualitrix.com
