One common practice found in many Scrum teams is the use of a test column on their Scrum board. While the intent behind it good, to streamline the testing phase, there are compelling reasons to reconsider the necessity of this column.
In my last post, I explained the technique of rubber duck debugging, where you can explain your code and testcases to an inanimate object to uncover and resolve issues. This time, i take rubber duck debugging to the next level by using ChatGPT as a virtual rubber duck.
Debugging is an integral part of the software development process. It involves identifying and fixing issues or bugs in a program’s code to ensure that it functions as intended. Developers often employ various techniques and tools to streamline this process, but one unconventional and surprisingly effective approach is rubber duck debugging.
As artificial intelligence (AI) and machine learning (ML) continue to advance, self-learning systems have become increasingly common. These systems can adapt to new data and learn from their own mistakes, making them highly effective in a wide range of applications, from fraud detection to speech recognition.
In the realm of software development, testing plays a huge role in ensuring the quality and reliability of applications. Traditionally, Graphical User Interface (GUI) testing has been a common approach to verify software functionality. However, with the rise of modern architectures and the growing importance of APIs (Application Programming Interfaces), API testing has gained significant prominence, aligning with the principles of the Test Automation Pyramid. I already explained what the the Test Automation Pyramid is in a previous article.
