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A critical aspect of the product life cycle evaluates the product before launch and compiles a pre-release customer review. Bots, which are used as Automated testing systems to work as human users, are automatically updated with software products to detect any bugs or other major technical problems.

To ensure that quality goods are provided to consumers, software testing is an essential method for effective testing procedures. The bots testing process is crucial and is taken along with software development to gain customer satisfaction. 

The software testing process has often taken a left-handed switch with agile strategies and DevOps on the way. This test method ensures that the software test and the development both start with the same initial stages.

AI bots and Software testing

Previously, with the existing waterfall model, software testing was done manually, and this was taken at the end of the software development life cycle (SDLC). This type of testing in the final phase of the SDLC has led to many untapped projects and costly costs. However, today with continuous integration, continuous testing, and continuous delivery embedded in DevOps, software testing has taken the left switch as mentioned above and has moved slowly from manual testing to automated testing.

Training AI bots

A common concept of AI is the machine's ability to understand the environment, process the input data to perform an intelligent action, and then learn how to improve it automatically. Voice-enabled searches went down the road a few years ago on Android Auto. By pressing a button on the wheel of my Volkswagen GTI to activate Google Assistant and say, "Play Bryan Adams," Google's assistant uses AI to process input and perform smart action. In a few seconds, Bryan Adams's music plays. 

It adds security to my daily routine and allows me to bring back my favourite music artists quickly.

A lesson here: Most intelligent developers release bugs, and development teams often respond rather than preventing them. If you are an inspector or working with an inspector, you know they like to ask many questions. 

To create AI test bots, we should train bots to process input data by asking intelligent action questions, such as Android Auto Google Assistant. 

Bots will improve as we continue to strengthen our ability to understand input and behaviour patterns.

Bots and AI in Software Testing and Development

Bots and AI are expected to dominate the software testing world soon. They touched on software development and testing technologies in many words.

Scope of Testing and Loading of Work

• It is a common practice to add new features to the software. And following new features, new codes are added. 
• This code also requires software testing to ensure proper operation. These tests sometimes need to create and implement a new set of test cases and sometimes even require duplicating existing test cases to ensure that recent performance has not changed or affected current performance.

The ability to fix bugs

• AI and bots can work tirelessly 24 x 7. Ideal if the list of test cases is long, or when testing on disrupted systems, etc. In short, they are very effective in using time-consuming test cases, which may be troubling inspectors. They explicitly extend the time when test cases can work without the need for human intervention.
• Reduce people's efforts by conducting test cases without human effort and allow testers to only test results and resolve issues, if any.

 Advanced Testing

• Continuous testing can improve the quality of your software. 
• Continuous testing helps report abnormal cleaning details.
• But doing repetitive tests is not a viable option for human testers. But this work can best be done by bots and AI, which has led to improvements in software quality.

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 Benefits of AI Bots on Test Results

• Improves accuracy 
• Testing can be done automatically whenever the source code is changed and notifies testers and developers if they fail.
• It helps to increase the depth and breadth of tests leading to improved quality.
• Used to create auto-check cases
• Used to generate automatic test code
• Use to do code-free tests.
• Improves the default testing process
• Uses test operations
• Quickly analyses test results.
• It makes testing more accessible and faster
• Used to redesign tests to introduce new boundaries and expand test coverage without additional burden on QA
• Ensures that no additional work is offered to teams
• Robotic automation bots are used to perform similar tests and perform auto tune tasks at a higher level.
• Used for a wide range of tests and to perform tasks of monitoring, evaluation and assisting in planning and evaluation program

Challenges with AI-enabled applications

AI test automation still has kinks to be used. The challenges and problems you may encounter when trying to build AI-enabled applications are:

• Identify, upgrade all require algorithms.
• They are collecting more information to install training bots.
• Bots can repeat tasks even if the data input is new.
• The process of training your bot will never end as we continue to develop algorithms.

Conclusion 

AI and bots amaze us enough with their outstanding skills. But what they still have in store for us cannot be predicted yet.

The time is not far when AI and bots will take all the booked efforts in software testing. Software testing will soon be more accessible, more expensive and time-consuming using AI and bots.

If you take a moment to think about all the technologies we use every day, AI has begun to integrate quietly into our lives. Be prepared! The role of automated software testing is on the verge of significant changes due to AI. They may not be here yet, but AI test bots are coming.