Systems | Development | Analytics | API | Testing

Every software engineer dreams of the day when they can simply type English-language sentences into a development platform and out pops a new, production-ready app. The app will be free of bugs because the natural language processing (NLP) functionality of the platform will have automatically created the test cases, run the tests, and self-corrected for changes to the app features. AI researchers in software testing are heavily invested in making testing as autonomous and natural as possible.

The promise of Artificial Intelligence (AI) in software testing is that an intelligent agent will one day replace humans. Instead of the struggle of manual labor involved in the endless unit and integrated proofing of software quality, machines will test computer systems without human intervention.

While ‘Smoke Testing’, ‘Sanity Testing’, and ‘Regression Testing’ are widely practiced in the world of QA, there still exist some misinterpretations or misconceptions around these concepts. For your team to make the most optimal use of the 3 methods, this article will help you to understand and differentiate them from one another.

“If you don’t care about quality, you can meet any other requirement” Gerald M. Weinberg Software testing has never been a walk in the park. It demands expertise in software development, users’ behavior, the software under test architecture, stakeholders’ requirements, and programming knowledge. Quality teams know firsthand how challenging it is to ensure software quality when its architecture is becoming more complex and teams are releasing at a pace faster than ever.

Salesforce is one of the most popular CRM applications globally, used by thousands organizations across all industries and segments. It enables organizations to manage their customer and revenue focused business processes, functions, and data in a central location, thereby improving planning, customer satisfaction, and overall business performance.

Integration Testing (or I&T: Integration & Testing) is a type of software testing in which various units, modules, and components of the software are integrated and tested as a cohesive unit. With Integration Testing, testers want to find defects that surface due to code conflicts between software components when they work together. This level of testing is higher than unit testing, which only validates if software components function well as a single unit.

Katalon’s January release adds Robot Framework integration with Katalon’s AI-enabled Visual Testing. We have also updated our API documentation for those teams needing to create their own custom integrations to the Katalon Platform via API’s.

Robot Automation Framework is a popular open source test automation tool employed by software teams. Katalon’s Robot Framework Integration enables software teams using Robot Framework for test automation to tap into Katalon’s powerful AI enabled Visual Testing capabilities to level up their software quality and release readiness protocols.

Katalon executives and researchers gathered recently to discuss the major trends reshaping the software testing industry. From the transformation of the role of software testers to the greater deployment of AI in testing, Katalon staff discussed the expectations of business leadership, software engineers, consumers, and testers. Here are some of the sweeping themes Katalon sees emerging in the new year.

Java testing frameworks are a collection of rules pre-set up with Java to support the design and creation of test scripts. The general rules include multiple functions such as coding standards, test data handling, object repositories, and libraries. The Java frameworks equip teams with a standardized structure and automation guidelines, which serve as the backbone of an effective testing process, with less manual effort, enhanced testing speed, and efficiency.