Artificial Intelligence (AI) is no more a buzzword for this technology-driven world of the 21st century. It has been in the limelight in recent years with various uses in our daily lives. The experiments on AI started nearly six decades ago and the recent advancements on AI and its subset Machine Learning (ML) have made a strong presence in our lives.
AI is not only making its impact on our daily lives, but the enterprises of different domains are trying to find ways to utilize Assistants to be trained to automate tasks to improve productivity.
Software development is one of those domains where AI and ML have maximum impact. The wave of AI automation has changed the way developers creates software and testers improve the quality of the software designed by the developers. AI in software testing has transformed the manual testing to automated testing that ensures delivery of software that is the best in quality.
AI in Software Testing: Assured quality software at your service
Testing is a vital part of software development process. This procedure ensures customer satisfaction and safeguards the potential failure of the designed software. Software testers or QA engineers generally assess and analyze software under certain conditions to find out the risks and threshold of implementing in the software being developed.
A crucial task of testing to improve the quality of the software can be eased by implementing AI in software testing. AI in software testing is a smarter way to test software in different stages to find any hidden flaws in it.
AI can make the testing task go easier by assimilating machines with the power of AI that can mimic human behavior. The team of testers can increase the workflow by streamlining the testing procedure. The manual software testing can be alternated by an automated and precision-based continuous testing process run by AI assistants AI bots in software testing platforms can perform more efficiently in recognizing changed controls with constant updates to its algorithms. Even the slightest changes can never go unnoticed by AI bots in software development.
3 powerful ways to enhance software Quality with AI
1. AI in Regression Testing
Software testing has ever been one a costly affair. Nearly 50% of the entire cost of software development is used up in testing itself but sadly testing adds no functionality to the application. In the scenarios of revealing a new error, a new cycle of revision begins which is often expensive as well as time-consuming.
Such repetitive software testing occurs as regression testing. This kind of testing ensures that no new bugs were introduced during the most recent cycle of enhancements to the application under test. Current AI methods such as classification and clustering algorithms rely on repetitive data to train models to forecast future outcomes accurately.
It works with a simple method of introducing a set of known inputs and verified outputs to train the model. This set of known inputs are fed to the algorithm and the output is checked against verified outputs. Hence, the accuracy of the software is measured. If the accuracy is at its best, the software is proven to be ready to be used in production.
2. AI-based Machine Vision
Machine vision (MV) is the technology that provides imaging-based automatic inspection and analysis for applications such as process control and robot guidance. Machine vision is primarily used in product-based companies or autonomous vehicles. It is the ability of the computer to see and analyze things with the help of video cameras, analog-to-digital conversion (ADC) and digital signal processing (DSP). The resulting data captured goes to computers for analysis.
Machine Vision plays a great role in enhancing the quality of the software. Machine vision in software development is related to user experience (UX) and how Web pages are rendered. The webpage rendering is an important part of software testing process. The contents of the webpage can become unreadable and controls can be unusable in case of not rendering the web pages well. Even highly trained testers face a challenge to solve issues that may arise because of bad UX and improper webpage rendering.
AI-based machine vision is well suited to analyze complex objects or products with high variability as simply as a human operator can do. It can capture a review-able ‘filmstrip’ of page rendering. It can also segment the pages into regions and can come up with visual processing tools to discover, interrogate, and classify page elements. One of the best examples of AI-based Machine Vision is ALBERT. ALBERT has the ability to learn the characteristics of a product directly from the production line. It can also autonomously assess the quality of the products. ALBERT is very simple to use and does not require complicated programming procedures.
Hence, AI-based Machine Vision improves software quality with enhancing User Experience of the software developed by coders.
3. Finding and fixing More Bugs in QA testing
Quality Assurance (QA) in software testing is a systematic process of determining whether the software meets specified requirements. QA makes sure that the designed software maintains a set of requirements for developing reliable software.
The QA process of software testing detects bugs and eliminates them. Such scenarios are not very rare when some bugs go unnoticed by the testers working on it. Later those unnoticed bugs create bigger issues in the software which takes cost and effort to fix. AI assistants can help the testers in detecting and fixing bugs more efficiently. AI can find better solutions for questions like how, where and when in a matter of minutes or even seconds. The information compiled by AI can be used by testers to find the required solution to prevent the bugs. AI helps testers to decide whether they need to change the code or it is needed to apply other approaches. Hence, AI in QA conducts ongoing analysis of errors at a faster and error-free manner.
Welcome to the Smart Testing Zone
Testing software for enhancing its quality is a critical task in the world of software development. However, such tasks are not only critical but also time-consuming and expensive. Thanks to the technology advancements which has helped the testers by automating some parts of the testing process. It is the Artificial Intelligence which can help testers to improve the quality of the software once it is trained to do so. AI in software testing makes the testing process much faster and easier than manual testing.
So, unlock the door of opportunities that AI holds for the software testers and be the software tester of next decade.