Impact Of ChatGPT on Software Testing Companies

From social media to the world of technology, ChatGPT has become the buzzword.   

And it is very natural to witness all the hype considering the massive potential that the tool holds. From influencers to coders and Software testing companies, ChatGPT has proven to be an aid to sales, operations, app development, and of course, software testing.   

Launched on November 30, 2022, by OpenAI, ChatGPT became an instant hit in its first week of launch, with over 1 million users (about the population of Delaware). The massive potential displayed and experience has made the entire tech industry classify ChatGPT as a Revolution.  

The technology showed the ability to foster human-like conversations, answer questions, identify errors, compose poetry, and have the ability to code in various programming languages.  With all the potential and capabilities that the tool displayed, the entire community of Software testing companies and developers started seeing it as a tool of the future.   

Though the tool has dynamic features and abilities, the software testing industry still needs to find all the possibilities surrounding the use of ChatGPT and explore how its AI could complement the software testing initiatives.   

Let's find it all in detail!  

What Is ChatGPT?  

Based on the GPT-3 or Generative Pre-trained Transformer model, ChatGPT is an NLP chatbot that can do back-and-forth communication. Developed and trained on a large amount of textual data, ChatGPT could showcase varying response tones to different scenarios.   

Some of its key features include understanding and analyzing context for 95 different languages. Also, it can do Chat-like interaction with a highly conversational model while generating creative responses, translating, paraphrasing, summarizing, and analyzing sentiments of the text. Moreover, it can even remember past queries and answers and take human feedback for added coherence in conversations.  

How Could ChatGPT Improve Testing?  

Adding speed to QA (Quality Assurance) helps organizations to deliver products and services faster while maintaining quality.  y speeding up the QA process, companies can identify and fix issues earlier in the development cycle, preventing costly delays and reducing the risk of defects in the final product.  his allows businesses to remain competitive in today's fast-paced market, meet customer demands, and increase overall productivity. 

The effective and relevant use of ChatGPT could offer all the aid needed to speed up the software testing process. From streamlining things to adding speed, here are a few ways in which ChatGPT could be deployed:   

API Testing  

ChatGPT could be deployed to work on generating frameworks like Postman or creating test scripts to work on APIs with popular languages like NodeJS, Java, Python, etc.   

Unit Testing  

For front-end projects that need generating syntax for writing test cases, ChatGPT can be integrated at the front end to work on languages like Javascript, Python, Swift, etc.  

Mobile Testing  

ChatGPT can even be used to work on test scripts for major test frameworks like Appium, which can further be used to test applications based on Swift, Java, etc.   

Integration  Testing  

ChatGPT can be used to assist with tools like Selenium to create test scripts that could support integration testing while giving support for HTML, CSS, etc.   

End-to-end Testing  

For end-to-end testing, QA teams could work together on generating test scripts for frameworks like Puppeteer or Selenium to create effective scenarios.   

Putting ChatGPT to the Use 

ChatGPT is a powerful tool that can be used to work on test case writing by Software testing companies that have no or minimum experience in coding. With the ability to process natural language commands, ChatGPT allows users to write in their own natural way, unlike any template type of model that needs knowledge of structures and key phrases.   

Thus, the use of ChatGPT could allow test teams to streamline tasks like creating test automation scripts, defining classes or functions, and generating positive and negative test cases for automated testing. Apart from these, ChatGPT can be used to work on other low code testing tasks like:  

• Complement behavior-driven development on different programming languages, frameworks, and libraries like Cypress or Cucumber.   
• ChatGPT can use Page Object Model to upgrade the code for any change in the app structure or the element locator.   
• It can separate the code from test cases improving the maintainability part of test script generation. 

ChatGPT and Its Limitations in Software Testing  

Implementing ChatGPT for software testing could showcase or involve various discrepancies. Therefore, depending on ChatGPT completely to automate the tests and test case generation could lead to performance issues. Some of the most significant limitations that Software testing companies may encounter with the use of ChatGPT for software testing include the following:   

Limited Test Case Generation  

When it comes to test case generation, the inputs given to the system play a very important role. The output of the system or operation entirely depends on input which, if not relevant or comprehensive, could affect the quality. Since ChatGPT is an AI tool, it cannot work on edge cases that need more critical understanding, such as user acceptance testing and its challenges.  

Challenge Of Understanding The Code  

The next big issue that Software testing companies working on ChatGPT are likely to face is the inability of the tool to understand the code. Even if we aim to pursue automation testing, limited or no knowledge of code makes it difficult for any tester or tool to locate all the potential issues or defects.   

Limited Execution  

As ChatGPT does not understand the code structure, it cannot execute tests. It can only be used to develop suggestions for test execution, leaving the entire task of implementation and evaluation to the users.   

Missing Contextual Understanding  

Another common problem that Software testing companies aiming to use ChatGPT are likely to face is the inability of the tool to identify the context or purpose, which might cause the generation of inaccurate responses.  

Restricted Domain Knowledge  

Even though ChatGPT has been trained on large amounts of information, it still contains limited expertise when it comes to certain domains. Therefore, it is not always feasible for ChatGPT to provide the most accurate response to test scenarios.   

Test Environment Control  

Originally, ChatGPT was a tool that was designed to power conversations and communication through AI. However, the data fed to its algorithms drive the potential of the tool to code. But being an external tool, it runs independently of any test initiatives or integrations, which not only cuts the control over the test environment but even cuts the scope of simulating the test conditions. Ultimately, it leads to factual mistakes or errors in the training data.   

Identifying Deprecated Methods  

ChatGPT works on the find_element_by_ function to locate elements on display which is an outdated method. Therefore, the user might need to create a command to update the code for the use of the correct method, which further needs ChatGPT's understanding of recognizing issues based on outdated approaches.   

Reduced Flexibility  

As a pre-trained tool that cannot adapt to customer requirements for any specific test situation, it ultimately restricts the freedom to customize. Moreover, it even cuts off the flexibility to automate the tests.   

ChatGPT, Software Testing, and the Collaboration 

All in all, using ChatGPT as a low code testing tool could streamline the whole task of updating and fixing code. This may involve commands that can change the previously created code for any bug fixes or make any precise changes to code with the help of the tool's conversational model.  

Besides, using ChatGPT could redefine the whole task of software testing, offering many significant benefits. These include automation of repetitive tasks to cut off any chances of human error in the test code. Also, effective use of ChatGPT for software testing can improve the speed of test execution, adding more speed to the overall process.   

Above all, ChatGPT, as an AI-powered conversational tool, could minimize or take off the requirement of manual testing, encouraging any experienced software testing company to focus on other complicated issues or other important tasks. More importantly, the accuracy and consistency ChatGPT has to offer with its recent releases and updates could smoothen the entire task of testing.