Posts

This blog post is about the thirteenth day of the 30-Day AI Testing Challenge event, where participants are required to develop their own testing methods and become pioneers in AI testing. The post may include the author’s thoughts and methodologies on developing new AI testing methods, as well as the experiences and outcomes of applying these methods in practice. By sharing their own process of developing testing methods and the results, readers will learn about the author’s innovative practices and leading position in the field of AI testing, inspiring more people to try and explore the application of AI in testing. This series of events is expected to provide testing professionals with an opportunity to deeply understand and practice the development of AI testing methods and encourage them to become pioneers in the field of AI testing.

This blog post is day eleven of the 30 Days of AI Testing Challenge, focusing on the use of AI to generate test data and evaluating its effectiveness. The post may include the author’s real-world application of AI-generated test data and an assessment of its effectiveness and applicability. By sharing the application and evaluation of AI-generated test data, readers will understand how the author leverages AI technology to generate valid test data and enhance the efficiency of the testing process in real testing environments. This series of events is expected to provide testing professionals with cases of practical application of AI-generated test data and encourage them to experiment with this emerging technology.

This blog post is day eleven of the 30 Days of AI Testing Challenge, focusing on the use of AI to generate test data and evaluating its effectiveness. The post may include the author’s real-world application of AI-generated test data and an assessment of its effectiveness and applicability. By sharing the application and evaluation of AI-generated test data, readers will understand how the author leverages AI technology to generate valid test data and enhance the efficiency of the testing process in real testing environments. This series of events is expected to provide testing professionals with cases of practical application of AI-generated test data and encourage them to experiment with this emerging technology.

This blog post is day ten of the 30 Days of AI Testing Challenge,which calls for participants to critically analyze tests generated by artificial intelligence. The blog post may include the author’s evaluation of AI-generated tests, covering aspects like accuracy, completeness, and coverage. By sharing the results of the critical analysis, readers will gain insight into the author’s deep understanding and views on AI-generated testing. This series of events aims to provide testing professionals with practical cases to deepen their knowledge of AI test generation outcomes and to stimulate further discussions on improving the quality of AI-generated tests.

This blog post is the eighth day of the 30-day AI Testing Challenge, focusing on creating detailed prompts to support the testing activities. The post may include the author’s reflections on how to design and build prompts necessary for the testing activities, as well as insights gained during this process. By sharing detailed prompt designs, readers will be able to understand how the author uses prompts in testing activities and effectively guides AI in tasks related to testing. This series of activities is expected to provide practical examples and experiences for testing professionals applying AI testing.

This blog post is the eighth day of the 30-day AI Testing Challenge, focusing on creating detailed prompts to support the testing activities. The post may include the author’s reflections on how to design and build prompts necessary for the testing activities, as well as insights gained during this process. By sharing detailed prompt designs, readers will be able to understand how the author uses prompts in testing activities and effectively guides AI in tasks related to testing. This series of activities is expected to provide practical examples and experiences for testing professionals applying AI testing.

This blog post is the seventh day of the 30-Days AI Testing Challenge, which requires participants to research and share real-time engineering technology. The post may include a definition of real-time engineering technology, its applications in the testing domain, introductions to relevant tools and technologies, and the author’s perspective on real-time engineering technology. By sharing research on real-time engineering technology, readers will gain insights into its potential value in testing and how to effectively apply this technology. This series of activities aims to provide a platform for testing professionals to deeply understand and discuss emerging technologies.