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software testing

Recent advancements of technology like AI and Machine Learning have widened the surface area of software testing. The testing surface of an application refers to the collective area surrounded by the public properties, methods and developers of that application (its Application Programming Interface, or API). It needs to be considered that Software Testing is a crucial step in the development process though it may not be receive much exposure.

“Software Testing helps identify errors, gaps or missing requirements in contrary to the actual requirements. That is, it enables developers to verify if the resulting software has all the features and functions that were originally planned”.

 

This is crucial! There will be no point in investing a lot of funds, resources and time in developing a software application if it doesn’t meets its purpose. Software Testing is currently manual and conducted by experienced software testers. But there are always chances of errors and certain aspects may be overlooked by the human eye. A good solution for this would be the integration of AI technologies on software testing. Specifically, this is done through problem solving and machine learning.

Systems can be taught to learn and apply the knowledge gained in the future. In simpler words, Machine Learning can teach systems patterns on identifying bugs or discrepancies. Machines and operating systems can use this information in future to immediately identify bugs in the application, perhaps even in the course of development. Artificial Intelligence helps fix these errors without the need of human intervention! These concepts are already dominating other industries and predicted to also have an impact on software testing in 2020.

Artificial Intelligence

Artificial Intelligence removes the chances human error probability while testing software applications. It can teach systems to learn analyze sources and apply knowledge in the future. Hence AI testers can deliver more accurate results. It can also be noted that AI shortens the time to run a test and find possible defects. Hence, the QA team will not be overloaded with large data volumes. It should also be noted 2020 will witness additional roles for QA engineers.

AI Test Experts: In addition to the traditional testing skills, these testers will have to develop machine learning algorithms, understand math models, and work on natural language processing paradigms.

AI QA Strategists: In 2020 the Quality Team will have to accommodate AI’s role in business processes. The team will need to have a broad understanding of data flow, math optimization, and robotics techniques.

Data Scientists: These members will also be a part of the QA team but will have individual responsibilities of using statistics and conducting predictive analysis to build the needed models for AI-based QA strategy.

Machine Learning

Machine learning (ML) can be defined as a technological concept that is based on pattern-recognition. Algorithms analyze tones of information and identify predictive patterns. With Machine Learning, a user interface is not required for software testing.  It automates the phase of Quality Analysis through back-end-focused processes. The specific areas where Machine Learning can help Software Testing include:

UI Tests: ML bots can be specifically useful for working on user experience. Many applications these days have patterns that are similar in design, functionality or interface. ML bots can be trained for a particular software area to run more test cases than regression testing would do. Moreover, QA engineers can develop a simple machine learning test which could automatically find visual defects in software.

APIs: The API layer of a software application can be rigorously tested with assistance from Machine Learning. Algorithms can handle the analysis of test scripts ensuring that testers aren’t stuck with making a lot of API calls.

These are the predictions that we have for the rise on Artificial Intelligence and Machine Learning in 2020. SGS Technologie is an experienced software testing company in Jacksonville Florida with nearly two decades of experience in the domain. We have adopted AI and Machine Learning in our Software Testing processes. Reach out to us to discuss how you will benefit with this expertise.

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Impact AI & Machine Learning on Software Testing in 2020


Recent advancements of technology like AI and Machine Learning have widened the surface area of software testing. The testing surface of an application refers to the collective area surrounded by the public properties, methods and developers of that application (its Application Programming Interface, or API). It needs to be considered that Software Testing is a crucial step in the development process though it may not be receive much exposure.

“Software Testing helps identify errors, gaps or missing requirements in contrary to the actual requirements. That is, it enables developers to verify if the resulting software has all the features and functions that were originally planned”.

 

This is crucial! There will be no point in investing a lot of funds, resources and time in developing a software application if it doesn’t meets its purpose. Software Testing is currently manual and conducted by experienced software testers. But there are always chances of errors and certain aspects may be overlooked by the human eye. A good solution for this would be the integration of AI technologies on software testing. Specifically, this is done through problem solving and machine learning.

Systems can be taught to learn and apply the knowledge gained in the future. In simpler words, Machine Learning can teach systems patterns on identifying bugs or discrepancies. Machines and operating systems can use this information in future to immediately identify bugs in the application, perhaps even in the course of development. Artificial Intelligence helps fix these errors without the need of human intervention! These concepts are already dominating other industries and predicted to also have an impact on software testing in 2020.

Artificial Intelligence

Artificial Intelligence removes the chances human error probability while testing software applications. It can teach systems to learn analyze sources and apply knowledge in the future. Hence AI testers can deliver more accurate results. It can also be noted that AI shortens the time to run a test and find possible defects. Hence, the QA team will not be overloaded with large data volumes. It should also be noted 2020 will witness additional roles for QA engineers.

AI Test Experts: In addition to the traditional testing skills, these testers will have to develop machine learning algorithms, understand math models, and work on natural language processing paradigms.

AI QA Strategists: In 2020 the Quality Team will have to accommodate AI’s role in business processes. The team will need to have a broad understanding of data flow, math optimization, and robotics techniques.

Data Scientists: These members will also be a part of the QA team but will have individual responsibilities of using statistics and conducting predictive analysis to build the needed models for AI-based QA strategy.

Machine Learning

Machine learning (ML) can be defined as a technological concept that is based on pattern-recognition. Algorithms analyze tones of information and identify predictive patterns. With Machine Learning, a user interface is not required for software testing.  It automates the phase of Quality Analysis through back-end-focused processes. The specific areas where Machine Learning can help Software Testing include:

UI Tests: ML bots can be specifically useful for working on user experience. Many applications these days have patterns that are similar in design, functionality or interface. ML bots can be trained for a particular software area to run more test cases than regression testing would do. Moreover, QA engineers can develop a simple machine learning test which could automatically find visual defects in software.

APIs: The API layer of a software application can be rigorously tested with assistance from Machine Learning. Algorithms can handle the analysis of test scripts ensuring that testers aren’t stuck with making a lot of API calls.

These are the predictions that we have for the rise on Artificial Intelligence and Machine Learning in 2020. SGS Technologie is an experienced software testing company in Jacksonville Florida with nearly two decades of experience in the domain. We have adopted AI and Machine Learning in our Software Testing processes. Reach out to us to discuss how you will benefit with this expertise.

Category : Software Testing

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