Artificial Intelligence in Software Testing
October 4, 2018
All software programs released in the market have undergone the certification from testing department from the parent company. In short, the testing process is done to ensure every failure is rectified and then released to the market. Usually, every software program, to become successful, is dependent on the satisfaction of the users. So, in the testing process, every aspect of risks, problems and challenges are conducted in the software program to prevent any type of failure.
In recent times, software is growing by leaps and bounds. The software programmers get very less time to design a software application. Please note, they also have to take care of the recent versions. On the other part, testers have to ensure that the software meets the demands of the customers. So, they have to do the evaluation properly and give perfect feedback to the development teams. In this fast changing times of technology, there is the need to reduce time on testing. Companies are opting for AI technology to test the failures and check bugs in a new software application.
Recent Trend of Usage of Artificial Intelligence in Software Testing
Every software company or web development company is gearing to adapt to the recent trend in the design sought by the users. So, the only way to do smart work is to make use of Artificial Intelligence.
By designing machines and systems which can serve as an alternative to human behavior, the team of manual testers can switch to an automated and accurate testing process.
Let us imagine a situation, where an AI testing platform has got designed. Once the permutations and combinations are uploaded to the machine, AI can identify a change more easily than a human. And now AI systems are developed with such precision, that it can learn new versions on its own. So, it is a case of self-learning from the path of machines.
Testing is more about verification of the product. The only factor, it needs is test data and the ways to do the testing. Have you heard about Google Deep Mind? It has created a program (AI) where deep learning techniques have been used to design this software. Now, this program can play video games on its own. After ten years, an AI program will easily detect flaws as well bugs with ease. In the next following paragraphs, let us check the benefits of Artificial Intelligence in software testing.
1. Improved Accuracy
Humans can err. It is human tendency to do mistakes in the manual testing process. But come automated testing, then the same steps get done in perfect manner. They can never miss out on results. So, testers can focus on other important tasks such as designing new software with excellent features.
2. Going Beyond The Limitations Of Manual Software Testing
Just imagine the possibilities. Let us imagine a situation. New software for image editing is getting developed. The testing team has to conduct at least more than 100 changes in its work features to ascertain its work functions. And till now the tests were done manually. Automated testing can help with the checking of software in all types of applications and various ways of working of the features.
3. Helps Developers/Testers
Automated tests can detect flaws and notify to the user immediately. This saves time of the developer and the QA agent.
4. Increase In Overall Test Coverage
With automated testing, the software quality gets increased. The automation can check in various ways from its memory. It can identify errors and check if the software behaves exactly as needed. Automation can run hundreds of test, whereas in manual methods, many humans have to work on the project.
5. Artificial Intelligence and Software Testing jobs
Does that mean, AI will cause loss of jobs in the testing field? Yes, that is a easy assumption to make. The answer is no. On the other hand, the future will give rise to a new set of testing jobs that are non-existent today.
The same factor is true even in other industries. In the future, humans have to do less of low level jobs. The main reason, why robots have replaced humans in low level jobs in countries such as Japan. Humans will also play their part, but their role will be more tuned to the improvement process.
Testing engineers will need a special set of skills to build and maintain AI based test suites. They should have more knowledge on data science and deep learning.
AI, once loaded with the right information can learn from self learning to identify failure patterns, defect spots, prediction of failures and application stability.
So let us look into some of AI implemented test strategies.
Test suite optimization – has the potential to detect alternative and similar test cases.
Prediction – Based on previous data, the AI will suggest the parameters of software testing.
Log Analytics – The AI can identify hotspots and can check with automation of text cases.
Traceability – The AI can identify complex situations from the RTM or requirement traceability matrix
Defective Analytics – AI can identify high risk spots in the software application before the programmer delivers the product to the QA team.
Let us imagine a situation. You are an entrepreneur and have invested in a company which offer home services in Hyderabad. They specialize in laptop home service in the city of Hyderabad. The business has caught on, and you want to design an app and release it to the market. In other words, you want the customers to have a simplified trendy booking service. Now, you want the app within ten working days. The technical team has given the approval and they are making use of AI to work on it. So, with the use of AI, the app got completed before the scheduled time and best way to measure the success of mobile app. Now it is out in the market, and the business is growing strong.