Application Programming Interface (API) is the backbone of the modern world. A lot of the activities you do on digital platforms leverage APIs, and testing those APIs is key to delivering good User Experience in software and applications. If you are trying to test APIs and don’t know where to start, read on and discover 60 test cases for API testing that you can use for references.
Welcome to our latest Product Roundup featuring Katalon software! This roundup will cover updates and new features released in July and August. This is the blog companion to our Product Roundup Webinar. Read on or if you prefer you can view the webinar here: This roundup includes an AI reporting analyst, QoL updates for managing your Test cases/suites, and TestCloud updates that allow you to test your private server URLs or locally hosted web-apps or websites more comprehensively.
API testing is easier said than done. When trying to do API testing we often find ourselves in the land of “what-ifs”—what if the third-party services we rely on are down? What if the APIs we need are still under construction? The solution, a Mock API. While this is a powerful approach, to unleash its full potential it is important to implement it correctly. That’s where Katalon steps in.
Having a good test case template comes with tons of benefits. Not having to re-invent the wheel is one of them. Drawing from years of experience in the software testing industry, we have created a detailed template for you to note down your test case in the most organized manner, so that you can dedicate your time and effort to other high-value tasks. Scroll down and download your template, and if you want to get some tips on how to best write a test case, read on, we got you covered!
Cigniti is a global digital assurance and engineering company that manages and implements enterprise digital transformation projects. One of its premier clients, a large cruise line headquartered in Florida, rolled out a fleet of the three most modern ships in the world. The cruise line commissioned Cigniti to develop web, mobile, and tablet automation supporting the back office, onboard staff, and customers.
Database testing is the process of evaluating the accuracy, reliability, and performance of a database system. Its purpose is to ensure that the data stored there is consistent, valid, and can be correctly manipulated for business needs. The components to be tested are usually database schema, tables, and database triggers. Testers leverage SQL queries, data comparison tools, automation frameworks, or load testing tools to examine the data integrity, validity, security, performance, and structure.
There is no doubt about it: Artificial Intelligence (AI) and Machine Learning (ML) has changed the way we think about software testing. Ever since the introduction of the disruptive AI-powered language model ChatGPT, a wide range of AI-augmented technologies have also emerged, and the benefits they brought surely can’t be ignored. In this article, we will guide you to leverage AI/ML in software testing to bring your QA game to the next level.
In the complex and rapidly evolving landscape of software development, the ability to make swift, well-informed decisions can be the dividing line between success and missed opportunity. As development cycles shrink and user demands grow, navigating the waters of software testing requires not just precision, but also clarity. This is where Katalon TestOps steps in with its game-changing feature: Virtual Data Analyst (VDA), powered by GPT technology.
We live in a highly interconnected world, and that interconnectedness couldn’t have existed without the tremendous contributions from the telecommunications industry. With 5G technology finally becoming mainstream, IoT growing at a rapid rate, and AI tech gaining prominence, the telecom industry is surely up for an exciting future. This faster-than-ever growth comes with the need for robust, continuous telecom testing to always maintain a high standard of service quality.
