The world is continuously amazed by ChatGPT and its applications. Every day multiple people post the applications of ChatGPT in various industries, including marketing, copywriting, sales, operations, and more. While we thought about ChatGPT for software testing, we had mixed opinions.
Although we are confident in its advantages for the community of software technicians, we are also aware of the risks involved with totally adopting all of the software’s output. It is only a useful tool to have on hand, yet judgments are not principles and are naturally open to mistakes. ChatGPT’s output depends extremely on the suggestions; hence the ability of the software tester who delivers the instructions is essential.
ChatGPT won’t replace manual QA engineers
In a number of circumstances, manual testing is the way to go. Let’s look at several scenarios where manual testing is preferable-
1. Problem-solving expertise and experience are offered by QA Manual Engineers – A special set of skills that Manual Engineers have allow them to be great problem-solvers in the workplace. They hold an in-depth understanding of the quality testing process that ChatGPT and other AI technologies are unable to easily develop due to their skill and experience. This deep understanding is essential for quickly and efficiently recognizing and fixing frequent issues. Furthermore, QA manual engineers provide innovative ideas by applying their years of practical knowledge to offer an entirely new viewpoint on their job.
2. QA Manual Engineers identify minor issues that ChatGPT might miss- In manual testing, Quality Assurance engineers play a vital and specialised role. These people are able to pick up on minor problems that ChatGPT and other automatic checking techniques miss. The complicated problem-solving abilities required manual QA engineers to find faults or quality problems that could have hidden patterns or be challenging to discover using automated methods. They also comprehend the product and its commercial goals, which is crucial given that possible effects may not always be obvious when a problem arises. These subtle faults could not be found if manual QA engineers don’t use their knowledge and expertise, which might destroy a product’s development process.
3. QA Engineers working manually can provide user experience feedback that AI lacks – Artificial intelligence (AI) cannot replace the feedback that quality assurance (QA) human engineers may provide on a user’s experience with a good or service. Thanks to the human factor, an engineer may evaluate how user-friendly a program, service, or application is via the eyes of a real user. While AI may be able to spot inconsistencies in coding and faults, it is unable to comprehend the details of how actual consumers would interact with a product. Additionally, as AI lacks empathy, it cannot understand how customers feel about their experiences or whether they are benefiting from them. QA engineers bring these viewpoints to every project, enabling businesses and other organizations to ensure they’re providing the best quality services.
4. Better in debugging than AI, QA Manual Engineers understand the context of errors – When it comes to fixing code, QA Manual Engineers are superior to AI. This is because QA Manual Engineers are better able to identify issues that only occur in specific circumstances since they know how the code works. AI algorithms are great at quickly identifying basic mistakes. They can be trained to analyze code, but they may not always understand why certain circumstances lead to problems or how the system functions. QA Manual Engineers are significantly more capable of troubleshooting problems than AI since they can use their context comprehension.
Manual testing and Chat GPT are the Ultimate QA Dynamic Duo?
In short, manual testing might be an exception in the QA community, but that’s a good thing! It is necessary for a successful testing procedure because of its unique strengths and skills. Having the ability to match user interactions, analyze the user experience, and reduce the effort of human testers, chat GPT bots can be a helpful addition to the manual QA process overall.
Combine AI and machine learning with the benefits of manual testing. Teams working on software development can create a testing method that is more thorough and efficient.
How will ChatGPT make Testing Better?
ChatGPT can be used in a variety of ways to speed up and simplify the work of software testing
1: Testing API: In such a scenario, ChatGPT might help produce test scripts and frameworks for API testing, such as Postman or Rest Assured. With popular programming languages like NodeJS, Java, Python, etc., it could be used to test several compromised APIs.
3: Mobile: ChatGPT helps write test scripts using popular test frameworks like Appium and others, even for mobile testing. Thus, it may be used by the testing team to evaluate various mobile applications that support Swift, Java, etc.
Using ChatGPT for software testing would change overall growth and extend the highest quality assurance standard. Many features, like extensive expertise, advanced language processing skills, and others, offer an effective and natural testing experience. ChatGPT can validate inputs from users, test scenarios, and easily automate manual and routine tasks.