December 2, 2024

Can AI tools replace Manual Testing ?

Introduction

In the fast faced world there has been rapid increase in needs of people and organizations. As a result more tools and technologies are getting developed to meet the ever increasing needs of people and organizations. Artificial intelligence(AI) is one of the fastest growing widely used technologies which has greatly benefited people from all streams. It has the capability of performing tasks that matches human intelligence. In the field of Software Testing Artificial Intelligence tools have helped testers by effectively testing complex software applications and thus enhancing the software testing process. With the help of AI tools, test scripts are generated quickly which result in better test coverage. They also help to cover those test cases, edge cases which were not covered during traditional testing process. This Blog will talk about whether AI tools can replace manual testing.

Some Commonly Used AI tools

There are various commonly used AI tools which are as follows:

ChatGPT

It is an artificial intelligence tool developed by Open AI in the year 2022 using Python Programming language. In Software Testing Domain it acts as an assistance for software testers in every steps of testing process. It helps in test case generation which involves generating automatically all positive and negative test cases. With the help of ChatGPT various test scripts can be automatically created for automation tools like Cypress,Selenium,Tosca etc. which reduces the efforts of software testers in writing test scripts. Developers and Testers can make use of ChatGPT for bug detection and debugging.

CoPilot

CoPilot is a generative Artificial Intelligence(AI) tool developed by Microsoft in the year 2023 as a replacement for Cortana.It acts as a helping hand for software testers by automating various repetitive scenarios,generating test codes and providing faster feedback. Copilot is an AI powered tool which helps in generating test cases automatically.It also acts as an assistant for developers and testers and help them to write unit tests, integration tests,System tests and UI Tests effectively. Copilot provides suggestions regarding changes in code coverage.Based on current stage of code and tests,copilot detects the untested part of the applications and suggests to write more test cases for those areas.Copilot ensures automated test scripts are integrated with CI/CD pipeline so that the test scripts run automatically after code changes and feedback on test results is immediately given to developers within the pipeline.

MidJourney

MidJourney is a generative AI tool developed by SAn Francisco based independent research laboratory called “MidJourney” in the year 2022. MidJourney plays a significant role in software testing by focusing mostly on Visual Testing and UI Testing. MidJourney generates test designs which is then used for performing UI testing.Testers compare the AI generated design with the actual application ensuring that the UI meets the design requirements.Midjourney helps in Visual Testing by automatically generating visual test scenarios.User needs to provide input of the scenario in text format and after that Midjourney will generate test scenarios based on the inputs given. It also generates automatically visual test reports which displays the test results of visual and UI testing.

AssemblyAI

Assembly AI is an Artificial Intelligence tool developed by US based company in the year 2017.It is used in software testing domain for performing voice based testing.In the present era of speech recognition, Assembly AI helps in testing applications that depend on voice commands like voice assistant,or voice enabled mobile applications.Testers simulate users voice inputs and use Assembly AI to analyze those inputs.Assembly AI checks that the application processes user inputs correctly and provides correct output.Assembly AI supports different languages and as a result it is used for testing voice recognition in multiple languages thus ensuring that the application can handle speech recognition in different languages.

Gemini AI

Gemini is a generative Artificial Intelligence tool developed by Google in the year 2023. Gemini with its Natural Language Processing(NLP) capabilities help in significantly impacting the software testing process.Testers provide the test requirements in plain language like for example “Validate the login functionality with valid credentials” and Gemini interprets these requirements and generate test scripts according to requirements. As a result it reduces human efforts in generating test scripts. Gemini helps in identifying all the redundant and duplicate test cases from complex test suites thus making the test process effective and streamlined. Gemini helps in automating detection of bugs and the areas based on the analysis of code and test data.

How AI tools impact Software Testing

AI tools have great impact on Software Testing, making testing process more efficient,attractive and adaptive. The various impacts on Testing Process are as follows.

Automation of Repetitive Tasks-AI tools help to generate automatically the test cases based on behaviour of applications,user activities thus saving time and energy which would have been spent in manually creating test cases.It also helps in automatically executing the test cases.
Effective Test Coverage- AI tools analyze the codes and test data and based on those parameters it suggests which test cases should be executed ensuring that only the important tests are run,especially when the resources and time is less. This ensures better test coverage. AI also focuses on those areas of application which are potentially prone to defects resulting in focused testing.
Quicker Detection of Defects- AI tools can detect quickly any unexpected behaviour in the application by comparing the current test results with the expected test data.It also identifies those defects which were missed during traditional testing process. AI also help in effective Visual Testing by quickly detecting the anomalies during UI change of application.
Improved Test Maintainance- AI tools can adapt themselves to the changes in the User Interface as well as code changes. If any automation test breaks due to UI changes, AI can automatically modify test scripts thus saving time and energy.AI also helps in performing root cause analysis which involves finding out the root cause of bugs by analyzing the bug logs,application behaviour thus resulting in faster debugging.
Integration with CI/CD tools- AI tools effectively integrates with CI/CD pipeline like Jenkins etc.thus making sure test scripts are executed continuously throughout the entire software development process. It also results in faster and more accurate testing and provides faster feedback to developers thus ensuring quicker debugging and releases.
Cost Effectiveness- With the help of AI tools repeatative test scenarios and more number complex test scenarios can be run seamlessly thus reducing the efforts of manual testers and instead allowing them to focus on other tasks like regression testing,test case design.AI tools ability to quickly detect bugs and provide immediate feedback saves time and cost involved in the software development process and ensure faster delivery of application.

Why Manual Testing is Still important

Inspite of significant contribution towards software testing process AI tools cannot replace Manual testing due to the following reasons

User interaction on complex functionalities

AI tools are not efficient enough for validating user interactions on complex functionalities since they are not able to predict user behaviour especially during interactions with complex functionalities that involve creativity and user perceptions.

For User Experience(UX) Testing

Manual testers can perform actions on software applications based on end users perspective.They also can perform usability,scalability,accessibility and user friendliness of software application more effectively than AI tools.

For Effective Visual Testing

Bugs like layout problems,poor graphics detected through Visual Testing require human eyes for proper identification.Although AI tools help in image recognition,proper and effective visual testing can only be done through human intervention.

Context Based Judgement

Some testing processes need proper understanding of the software organization logic,user requirements and expectations and cultural context which is difficult to for AI tools to fully understand and implement.

Exploratory Testing

Although AI tools can perform exploratory testing,it still cannot fully replace the skills and intelligence of manual testers who thoroughly explore the applications and cover most of the untested scenarios.

Results Interpretation

Although AI tools can detect bugs,but still Manual testers are needed to understand the impact of bugs on users real time tasks, the severity and priority of the bug and to check whether the behaviour is actually a defect or a feature.

Conclusion

AI tools have greatly increased the efficiency and effectiveness of software testing process through immediate detection of bugs,faster feedback and creation of large number of test scenarios in short time. AI tools cannot replace manual testing fully especially in areas involving human judgement,exploratory testing and user experience. So both Manual Testing and AI tools have equal contribution and importance in software testing domain.

Also Read:

Types of Manual testing and its Differences

Is Software Testing a Good Career

Software Development Life Cycle(SDLC)

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