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AI Enabled Testing Services

Use of AI or ML in Testing is niche and needs expertise. QA Mentor has extensive industry experience in this area for decades now.

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In the last few decades, the software industry evolved a lot. Earlier, both the development and testing cycles used to be prolonged and as a result, digital businesses used to lose the competitive advantages in the market. But now, thanks to AI and ML – these are revolutionizing software testing, making it faster, more accurate and efficient.

While Automation reduces the repetitive cycles of human centric testing, AI aims at minimizing the repetitive work but with added intelligence. If you have similar problem statements in your business, you are at the right place!

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AI Testing Framework:

We are specialized in studying our customer’s ecosystems and developing custom made AI testing framework for their businesses. All the frameworks are based on a centralized base framework which has been curated with the KPIs achieved from the projects we have successfully delivered over the past 2 decades.

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Key Activities involved in the Framework:

  1. Analysis of the requirements of customer’s digital ecosystem and mapping of them with the QA Mentor’s in-house methods and algorithms available in the AI test lab.
  2. Identification of various metrics available in the customer’s ecosystem.
  3. Defining the optimal ranges using the statistical methods and adding the method to the AI Test Lab repository.
  4. Validation and assessment of the system design with the newly added method by integrating it with AI Test Lab.
  5. Utilization of APIfication to build the tested digital ecosystem enabled by AI.

Leveraging AI to Enhance Test Automation and its importance to your Business:

AI transformed Test Automation in many aspects. AI can generate a huge amount of test data automatically using business driven algorithms without depending on the manual preparation of test data. It can automatically create test scripts from the existing sets as well. Using the AI driven algorithms, test scripts can be generated with more coverage and accuracy.

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Utilization of AI has endless possibilities and over time it’s growing with more sophistication. Test automation driven by AI ensures more accuracy and productivity, which in turn means more savings for our customers. Beside that, a quicker testing cycle will ensure a faster market readiness of our customers’ businesses and services they are offering.

How AI based algorithms are playing a key role in our success?

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Supervised Learning based Algorithms: This algorithm enables the machine to receive datasets with correct answers. This set contains the test results, code coverage, test releases, fixed defects etc. It is often used to measure the potential risks of a system.

Unsupervised Learning based Algorithms: In this approach, decisions are being made by taking the demarcated inputs. These algorithms help to identify the possible errors and analyze if the data in the same group are similar in nature. It then simplifies the data for further processing.

‍Reinforced Learning based Algorithms: Our test engineers train the neural network on the reward and fallback mechanism. For any error, the function is corrected to ensure that it doesn’t appear again. The more it’s being taught, the less error it will cause.

Our AI experts derive research based techniques from the above algorithms and use them to enhance and improve different areas of software test processes.

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These derived techniques help our customers in
achieving high value testing through the following:

By using the Bayesian logic, reusability of test cases can be improved by incorporating historical data, adapting testing strategies, and making informed decisions about test case selection and prioritization.

Our AI experts use the Visual Regression algorithms to enable the AI-powered visual UI testing and monitoring by automating the detection of visual discrepancies in graphical user interfaces. Some of the lab derived parameters we use are baseline image capture, image comparison, monitoring of tolerance and thresholds etc.

We leverage the use of Random Forest algorithm to enable the effective exploratory test cycles through data analysis and prioritization, bug prediction, defect clustering, feedback loop, test data generation etc. Random Forest technique helps in the data validation testing process as well through the process of – anomaly detection, feature importance and complex rule detection.

Through the intelligent use of Decision Tree algorithm, our AI experts help our customers in reducing the duration of test cycles by – test case prioritization, predictive test analysis, data driven mechanism, defect clustering, risk based tree generation etc.

We utilize the Neural Network algorithm to enhance the intelligent requirement analysis by automating and improving certain aspects of the process: NLP based tasks, Automated Classification and Categorization, Requirement Prioritization, Pattern Recognition and adaptive learning.

Through our AI lab driven approach, we leverage the use of the Sentiment Analyzer to enable smart error detection. It is designed to determine the sentiment expressed in a piece of text, such as positive, negative, or neutral. It adds values to the test process by quickly identifying areas of concern where further investigation or testing might be needed.

QA Mentor’s AI research team has introduced ultra-advanced techniques to ensure the best possible test coverage. We use Genetic Algorithm (GA) to optimize test case selection, prioritization, and generation to achieve maximum coverage. And in addition, we utilize the Particle Swarm Optimization (PSO) technique to optimize solutions by simulating the movement of particles in a multidimensional space. It can be applied to select test cases that maximize coverage of different code paths and scenarios.

QA Mentor’s AI Test Lab:

QA Mentor built a dedicated State-of-the-Art AI Test Lab with enhanced infrastructures to support the ongoing research activities in this space. The lab is equipped with advanced AI technologies and tools which ensures the success of pilot projects, enterprise projects and produces new in-house methodologies. Our dedicated research team works in the AI Test Lab to support the project deliveries.

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Key components of our AI Test Lab:

  • Dedicated research team comprising of AI skilled engineers with industry expertise and exposure.
  • Virtual Machines (VMs) with different configurations to support the ever changing needs of IT.
  • The lab is supported by an independent cost center which is an investment made by QA Mentor for the greater benefits of their customers.
  • The AI Test Lab is equipped with some of the globally accepted and strong set of tools that enable the AI driven test deliverables for our clients.

AI Testing Services Offered by QA Mentor:

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  •  Managed AI Testing: End – to – End testing delivery model to support all the testing activities driven by our AI framework.
  • Test Transformation: Designing a transformation roadmap by identifying the pain areas and recommending the way forward enabled by POCs hosted in our AI Test Lab.
  • Automated Test Results: Custom made AI framework to integrate the Automation Test Suite with the Test Execution Logs which helps in generation of Automated Test Results.
  • Automated Test Data Generation: Using the AI engine to generate bulk test data with defined keywords.
  • Validation of Test Case and Test Data: Custom made algorithms to validate the accuracy of test cases and the test data.
  • Test Coverage Metrics: ML driven algorithms to measure the test coverage and to identify the gaps with respect to the RTM (Requirement Traceability Matrix).

Why QA Mentor?

  • More than 2 decades of experience of implementing AI in businesses.
  • Specialized AI and ML enabled testing services executed by highly skilled engineers.
  • Dedicated team of AI consultants from different industry domains.
  • State of the Art AI Test Lab curated by QA Mentor technical experts.
  • Custom made AI framework to respond to the business needs.
  • Reduced maintenance and faster troubleshooting in large scale enterprises with increased accuracy.

We’re here when you need us. If you have further questions regarding AI Enabled Testing Services, or if you are ready to start a consultation, we want you to contact us so we’ve tried to make it easy.

Awards & Recognitions in Software Testing Services

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