November 2025 Summaries

In Amsterdam, a JetBrains office meetup provided a warm and engaging environment for over 40 attendees passionate about software testing, featuring three insightful talks. Ivan addressed the challenges of testing AI systems, highlighting the inadequacy of traditional deterministic methods in non-deterministic environments and the need for innovative approaches. Roman discussed JetBrains' strategies for testing IntelliJ-based IDEs, emphasizing the creation of a DOM-like abstraction to facilitate stable integration testing. Margarita shared her experience using the Jobs To Be Done framework to manage her QA responsibilities effectively, focusing on addressing process fragility rather than resorting to overwork. The event underscored the value of community, with attendees both returning and new, some expressing interest in speaking at future events or organizing their own meetups.

Qase's Sleep Profiler is a tool designed to enhance the efficiency and stability of end-to-end (E2E) tests by addressing the drawbacks associated with using fixed delays, such as time.sleep(), which can unnecessarily prolong test execution times and lead to test instability. Instead of relying on fixed delays, developers are encouraged to use conditional waits like Playwright's page.wait_for_selector() or Selenium's WebDriverWait with expected_conditions, which complete as soon as conditions are met, thus speeding up the tests. Sleep Profiler automatically logs time.sleep() calls in tests, allowing developers to identify and replace them with smarter waiting strategies, reducing execution times and improving performance. It achieves this through Monkey Patching, intercepting the standard time.sleep function to log its usage and duration, and providing detailed reports in Qase for analysis and optimization. The tool can be enabled via the command line or a configuration file, and it supports the transition to smart waits by recommending the use of methods like wait_for_selector() and setting reasonable timeouts, ultimately leading to faster and more reliable test results.

In October, Qase focused on enhancing the confidence and efficiency of quality assurance (QA) engineers by introducing several new features aimed at reducing repetitive tasks and improving workflow. The updates include AI-powered bulk conversion, which automates manual test cases with intelligent analysis to minimize errors, and the ability to clone test plans to save time on setup. AIDEN, the AI sidekick, now automates over 60% of manual tasks, freeing up significant time for QA teams to concentrate on higher-impact initiatives. The new Data Retention Add-on allows teams to extend their test data history for compliance and trend analysis, while linked shared steps provide clarity on the impact of code changes. Additional improvements include expanded framework support, flexible logging, and the ability to make test runs public, all designed to streamline QA processes and integrate seamlessly into existing workflows. These enhancements aim to transform Qase into a more empowered and intuitive QA platform, helping teams achieve a state of flow by replacing uncertainty with confidence.

In modern software development, the Qase Network Profiler enhances testing by intercepting and logging all HTTP requests and responses, providing full visibility into network interactions. It utilizes Monkey Patching to override standard HTTP request methods in the requests and urllib3 libraries, allowing for automatic logging without manual intervention. This approach simplifies debugging and analysis by capturing detailed logs of network activities, making it easier to identify and resolve errors when requests fail. Additionally, the profiler facilitates performance analysis by tracking request execution times. When integrated with Pytest, the Network Profiler logs each HTTP call as a separate step in the Qase report, enabling developers to view comprehensive request and response details, including headers and bodies. This tool supports libraries like requests and urllib3, offering developers and testers an efficient means to improve the quality and reliability of their test scenarios.