Artificial Intelligence and Its uses For Software Testing

Meaning of AI

AI is the concept in which we make it possible for machines to think like humans. Machines can perform tasks like reasoning, planning, learning and understanding language. We can never compete with the human Intelligence but AI has huge implications on the life of humans. The technology behind the Artifucial Intelligence is the Machine Learning which are designed in order to make our lives easier and get more productivity.

We can make use of Artifitial Intelligence by making some devices which are performing the current human needs and should reflect the human nature. More content is required across the devices as people are becoming more and more dependent on machines. But till date, no such pattern as to what are the sequence of usage of these devices, have been found in order to judge the market demand.

AI has the Power to facilitate a more efficient workplace. AI can boost the productivity of marketers by empowering how to channel their time more and more effectively and efficiently. If a CRM kind of platform is used, it reduces the marketer's work and time.

Significance of Artifitial Intelligence is that to know how does ordinary people make sense of mental life. People generally perceives two fundamental components of mental life: experience and agency. According to many studies there are three components of mental life: related to the body, the heart and the mind—with each component encompassing related aspects of both experience and agency. 

AI can be used for a variety of Tasks like: Medical Diagnosis, Electronic Trading, Robot Control, and Remote Sensing. Google's CEO Mr. Sundar Pichai says that Artificial Intelligence can be more profound than electricity or Fire. TESLA and Elon Musk has launched a personal campaign against AI which shows that how technology is a potential threat to human race.

AI for Software Testing

Artificial Intelligence is getting its use nowadays for a number of feilds, one of them is Testing. Companies like Accenture have launched new services for Testing Artificial Intelligence globally that are powered by the “Tech and Test” methodology designed to help companies build, measure and monitor reliable AI systems within their own infrastructure or in the cloud. The situation would be somewhat like: There would be “Tests” with AI-powered visual verifications or a range of possible outcomes. This test would have to be run many times and will have to make sure that the conclusion is statistically correct. The test infra would need to support learning expected test results from same data that trains the decision making AI.

Following points can be used in order to implement AI:

1.Test Suite optimization: First Step is to identify the duplicate/similar and unique test cases.

2.Predicting the next steps: Based on historical data finding out the key parameters of a software testing process.

3.Log Analytics: It should identify the hotspots and automatically should start executing test cases.

4.Traceability: It should identify the complex scenerios from the RTM and extract the keywords to achieve the test cases.

5.Feeback Trends: To get the feedback trends from the market by analysing the data from the social media etc.

6.Defect Analysis: To Identify the high-risk areas in the application which helps in the risk-based prioritization of the regression test cases.

Advantages of Implementing AI for Testing:

1.Traceability: Missing Test Coverage against requirement as well as identifying dead test cases for changed or redundant requirement.

2.Improved Quality: Self Learning Algorithms which will update themselves according to the needs.

3.Cognitivity: Use of science for defect localization, helps in getting early feedback.

4.One Platform which is Integrated: The code is made on the open sourse stack and which is adaptable to the client technology landscape.

5.Faster: With the use of AI the time is being reduced many folds.