15 Jan 2019
Published: 24 Mar 2020
Role Of AI bots and Artificial Intelligence in Software Testing
Last Updated: 27 Jul 2020
Software testing is an important process that follows effective testing practices to ensure quality products are delivered to customers. The testing process is crucial and be taken up along with software development to deliver customer satisfaction by enabling flawless applications. Typically, with the agile and DevOps practices on the go, the process of software testing has taken a shift-left approach. This method of testing ensures software testing to be taken up along with the development and both run in parallel from the initial stages.
1. AI bots and Software Testing
2. The Evolution of Artificial Intelligence in Software Testing
3. What is a bot and what is special about AI Bot in software testing?
4. How AI powered bots can be used in software testing
Earlier, with waterfall model in place, software testing was mostly done manually and this it was taken up at the end of the software development life cycle (SDLC). This sort of testing at the last phase of SDLC led to many missed project timelines and adversely affected cost also. But, today with continuous integration, continuous testing and continuous delivery embedded in DevOps, software testing has taken a shift-left approach as stated above and slowly moved from manual testing towards test automation. In order to get effective test automation, the QA team uses both open source and paid machine learning test automation tools that are widely available.
It has also been observed that, though enterprises could get many benefits by leveraging test automation such as faster and continuous releases and quality products. But, still their quest for quicker ROI and need for complete automation without human intervention has led to the innovation of AI.
Subsequently, today the era of Intelligent AI driven software testing has come into place. This AI can be considered as an umbrella term for the set of algorithms and technologies that enable computer systems to perfectly mimic human intelligence. The broad range of these algorithms have been developed using Robotics, Machine learning (ML), Natural Language Processing (NLP), Computer Vision, Cognitive computing, etc. and interestingly all of these form a part of the AI technology.
Specifically, today’s automation testing deals with AI and Machine Learning (ML) wherein the usage of ML allows computers to learn automatically without any human intervention. Interestingly, AI machine learning involves the development of unique and specific algorithms that can access data, learn from that data by extracting patterns to make decisions and predictions and seemingly these patterns form the inputs for the AI chat bots.
Forbes in one of its Article on AI bots says that, “Development teams no longer have the luxury of time they had when monthly product launches were the gold standard. Today’s enterprises demand weekly releases and updates that trickle in even more frequently. In this context of tightening deadlines where the bar is always set higher, the only real alternative is to test faster and smarter using AI. Machine learning and other branches of AI will significantly alter the way software testing is conducted.
It is important to note that with respect to software testing, most of the activities are repetitive as the product or application features need to be tested many times. It is all about giving different inputs and checking the expected outputs. This process stands out to be the best and effective candidate for applying AI machine learning and invariably these inputs and the expected outcomes are the main criteria that are needed to train an AI Bot.
AI bot is nothing but a shortcut for an AI Chat bot named as Bot and it is being used to simulate human conversation or chat with users enabled through AI. These AI bots work like humans and ensure automation of tasks to save lot of time and costs.
Significantly for the AI bots to work in software testing you need to define the specific goals for which they can be used. QA team should know how AI works to take the complete advantage of using these AI bots in the process of software testing. These intelligent bots need to act independently and an AI bot autonomy is the result of using control loops. The AI bot technology is built around ML and NLP algorithms and delivers many benefits when used in software testing.
– Improves accuracy as errors are more with human interference
– Tests can be run automatically whenever source code changes are checked in and notifies the testers and developers if they fail
– Helps to increase depth and scope of tests resulting in improvement of quality
– Used in creating test cases automatically
– Used to generate test code automatically
– Use to perform codeless tests
– Enhances test automation process effectively
– Automates the execution of tests
– Used to write test cases easily and quickly with automation
– Quickly analyses test results
– Makes testing easier and faster
– Used to re-construct the tests to incorporate new parameters and increase testing coverage without extra workload to QA
– Ensures no extra workload is given to the teams
– Robotic automation bots can be used to run parallel tests and auto tune tasks at an advanced level
– Used to run a wide scope of tests and make tasks to oversee, examine, and assist in programming testing procedures
– Effectively used to run time consuming test cases which otherwise would consume testers time and effort
– Reduces human effort as tasks are automated and performed by bots
– AI chat bots can be used 24×7 and can perform debugging adequately
– They can be used anytime and anywhere without human intervention
– Effectively used to expand the amount of time that tests can be able to run without requiring human information
– Bot automated testing helps to consequently change code to resolve bugs or anticipate potential issues if any based on historical testing outcomes
– AI bots in software testing also helps in continuous testing
– Helps to enhance testing quality and enable the testing team to work more viably on various projects
– Though initial costs are high, but saves lot of time and efforts of team and becomes cost effective with usage
– Delivers quicker ROI as bots perform activities that automate more quickly and ensure quality outcomes
As a final thought, as today’s software applications are more complex and interact with each other through a myriad of APIs, IoT devices and other connected systems, it is essential to embed and use AI enabled test automation. This increased complexity of applications also leads to many challenges during testing process that can be overcome by using AI test automation using bots that support machine-based intelligence and perform intelligent, uninterrupted testing.
AI has been embraced by all industries such as healthcare, Pharmaceuticals, Banking and many so as to make life easier. Recently AI has also been used in software testing along with automation to make the process of software testing quicker, efficient and deliver quality without any human intervention.
There are many benefits of using AI bots in software testing as they deliver continuous, faster releases and quality product without human dependency. Software testing tasks become easier and quicker with AI bots. Hence, enterprises and businesses should embrace these new AI based technologies and AI bots to ensure quicker return on investment and get quality products without much human intervention in software testing. As next-gen testing services provider, talk to our in-house AI experts to know more about our services.
Ans. Automated testing programs use bots to act as real users and automatically run through software products to find any bugs or other major functional issues.
Ans. A Turing Test is a method of inquiry in artificial intelligence (AI) for determining whether or not a computer is capable of thinking like a human being.
Ans. The application of AI in software testing tools is focused on making the software development lifecycle easier. Through the application of reasoning, problem solving, and, in some cases, machine learning, AI can be used to help automate and reduce the amount of mundane and tedious tasks in development and testing.
Ans. List of AI Tools & Frameworks ( Scikit learn, TensorFlow, Theano, Caffe, MxNet, Keras, Pytorch)
1. INSURTECH: HOW AI IS ADDRESSING THE INDUSTRY’S KEY CHALLENGES/a>
2. How AI Can Be Leveraged In All Aspects Of Testing
3. Artificial Intelligence and its Impact on the Software Testing Industry
4. 70+ Software Testing Tools List You Must Know in 2020
5. User Testing Guide – What, Types and How to Perform Testing
6. A Beginner’s Guide to Test Automation (2020)