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Quality Analyst, Not Quality Assurance.

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30 Days of AI in Testing Challenge: Day 20: Learn about AI self-healing tests and evaluate how effective they are

nao.deng ·

30 Days of AI in Testing Challenge: Day 20: Learn about AI self-healing tests and evaluate how effective they are

This blog post is about Day 20 of the 30-Day AI Testing Challenge,exploring the effectiveness of AI self-healing tests. The article may include the author's definition, purpose, and methods of AI self-healing testing, as well as an evaluation of its effectiveness and practical experience. By sharing explorations and evaluations of AI self-healing testing, readers will understand the author's views and insights on this emerging testing method, as well as its application effects in real testing environments. This series of activities hopes to provide testing professionals with an opportunity to understand and explore the potential and limitations of AI in self-healing testing, and to promote further research and application of AI testing in the industry.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 19: Experiment with AI for test prioritisation and evaluate the benefits and risks

nao.deng ·

30 Days of AI in Testing Challenge: Day 19: Experiment with AI for test prioritisation and evaluate the benefits and risks

This blog post is about Day 19 of the 30-Day AI Testing Challenge, focusing on exploring the role of AI in test priority sorting and evaluating its pros and cons. The article may include the author's practical application cases of AI in test priority sorting, as well as the benefits and challenges brought by using AI. By sharing experiences and evaluations of applying AI in test priority sorting, readers will gain insights into the author's views on the actual effects and impacts of AI in the testing process. This series of activities hopes to provide testing professionals with an opportunity to understand and explore the role of AI in test priority sorting, and to promote further discussions about the application of AI in testing.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 18: Share your greatest frustration with AI in Testing

nao.deng ·

30 Days of AI in Testing Challenge: Day 18: Share your greatest frustration with AI in Testing

This blog post is about Day 18 of the 30-Day AI Testing Challenge, aimed at sharing the biggest challenges participants face in AI testing. The article may include difficulties, challenges, and obstacles encountered by the author in practice, as well as corresponding solutions or coping strategies. By sharing the difficulties and challenges encountered, readers can understand the problems others may face in AI testing and gain inspiration and assistance from them. This series of activities hopes to provide a platform for testing professionals to exchange, learn, and solve problems together, promoting progress and development in the field of AI testing.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 17: Automate bug reporting with AI and share your process and evaluation

nao.deng ·

30 Days of AI in Testing Challenge: Day 17: Automate bug reporting with AI and share your process and evaluation

This blog post is about Day 17 of the 30-Day AI Testing Challenge, looking at automating bug reporting with AI and sharing your personal process and evaluation results. The article may cover the author's process for automating defect reporting using AI technology, including tool selection, implementation methodology, benefits of automating the process, and evaluation results. By sharing the process and evaluation results of automated defect reporting, readers will learn about the authors' experiences and lessons learned in practice, as well as the potential of AI technologies to improve the efficiency of defect management. This series promises to provide an opportunity for testing professionals to understand and explore the use of AI to automate defect reporting and to promote technological advancement and innovation in the industry.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 16: Evaluate adopting AI for accessibility testing and share your findings

nao.deng ·

30 Days of AI in Testing Challenge: Day 16: Evaluate adopting AI for accessibility testing and share your findings

This blog post is about Day 16 of the 30-Day AI Testing Challenge to evaluate the adoption of AI for accessibility testing and share personal findings. The article may cover the author's experience with the practical application of accessibility testing with AI, including the selection of AI tools, improvement of testing methods, and validity of test results. By sharing evaluations and findings on accessibility testing with AI, readers will learn about the authors' applications in real-world testing scenarios and learn from their experiences and lessons learned. This series promises to provide an opportunity for testing professionals to learn about and explore the use of AI in the field of accessibility testing, and to foster industry dialog and technological innovation.
#AI in Testing #30 Days of AI in Testing #Accessibility Testing

Postman API Automation Testing Tutorial Advance Usage AI Assistant Postbot Trial Introduction

nao.deng ·

Postman API Automation Testing Tutorial Advance Usage AI Assistant Postbot Trial Introduction

This blog post is about the advanced usage of the Postman API Automation Testing tutorial, focusing on the trial of the AI assistant Postbot. The article may include the author's introduction to Postbot's features, how to use it, advantages and scenarios. By sharing the trial experience of Postbot, readers can learn how to optimize the API automation testing process with the help of AI technology to improve testing efficiency and accuracy. This tutorial is expected to provide Postman users with an opportunity to learn more about and try out the AI assistant, as well as provide guidance and inspiration for applying new technologies in API testing.
#Postman #API Testing #Automated Testing

30 Days of AI in Testing Challenge: Day 15: Gauge your short-term AI in testing plans

nao.deng ·

30 Days of AI in Testing Challenge: Day 15: Gauge your short-term AI in testing plans

This blog post is Day 15 of the 30 Day AI Testing Challenge and looks at measuring short-term AI in test programs. The article may include criteria for evaluating short-term AI applications in a test program, as well as methods on how to determine their success. By sharing methods and hands-on experience in measuring short-term AI applications, readers will gain insights and guidance from the authors on practical applications of using AI in test programs. This series promises to provide a platform for testing professionals to understand how to measure and evaluate short-term AI applications and to foster broader industry discussions.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 14: Generate AI test code and share your experience

nao.deng ·

30 Days of AI in Testing Challenge: Day 14: Generate AI test code and share your experience

This blog post is about the 14th day of the 30-Day AI Testing Challenge event, aimed at generating AI test code and sharing experiences. The post may include the author's process of using AI tools to generate test code, the choice of tools, the quality assessment of the generated code, and the application experience in actual testing. By sharing the process and experience of generating AI test code, readers will learn about examples of AI application in the field of testing, as well as the author's views on the effectiveness and reliability of AI-generated code. This series of events is expected to provide an opportunity for testing professionals to understand and try using AI testing tools and to share their experiences and insights.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 13: Develop a testing approach and become an AI in testing champion!

nao.deng ·

30 Days of AI in Testing Challenge: Day 13: Develop a testing approach and become an AI in testing champion!

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.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 12: Evaluate whether you trust AI to support testing and share your thoughts

nao.deng ·

30 Days of AI in Testing Challenge: Day 12: Evaluate whether you trust AI to support testing and share your thoughts

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.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 11: Generate test data using AI and evaluate its efficacy

nao.deng ·

30 Days of AI in Testing Challenge: Day 11: Generate test data using AI and evaluate its efficacy

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.
#AI in Testing #30 Days of AI in Testing

30 Days of AI in Testing Challenge: Day 10: Critically Analyse AI-Generated Tests

nao.deng ·

30 Days of AI in Testing Challenge: Day 10: Critically Analyse AI-Generated Tests

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.
#AI in Testing #30 Days of AI in Testing
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