GlobalLogic InteliQ

Identifies critical issues and high-risk areas earlier in regression testing through highly effective test case prioritization

Overview

GlobalLogic's InteliQ accelerator applies a machine learning approach to regression testing in order to more effectively prioritize test cases and therefore identify critical issues and high-risk areas earlier. The solution also helps test engineers automate manual processes, identify problematic autotests, and detect any outliers that could create a weakness in the development process. By automating QA and detecting defects earlier, InteliQ can reduce project phase costs by around 11% and accelerate the regression test cycle timeline.

Supported platform

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Industries

Industry Agnostic

Technologies/Works well with

Python, Scikit-learn, Pandas, NumPy, Angular, Flask, GitHub, Terraform, Amazon / compatible with Azure and GCP, Amazon DynamoDB, Amazon S3 , AWS Code Commit, Amazon ECS, AWS Fargate, Amazon Route 53, Amazon CloudFront

Business Needs

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Define the most important and highest risk tests (e.g., areas, features), from the point of criticality to product release

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Find the most important defects at the beginning of regression testing

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Save time and reduce costs for testing without compromising the quality of the product

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Estimate risks in advance of the next development cycle to mitigate risks

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Identify high-risk tests as candidates for automation

Value Proposition

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Creates priority heatmaps for regression to optimize the test run

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Helps define manual test case candidates for automation

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Eliminates failure risks for automated and manual tests

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Highlights risk factors and mitigates project risks

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Detects outliers and potentially unstable autotests

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Reduces the project phase costs by about 11%

Features

Simple Implementation

  • Applicable to any project with a regular regression cycle
  • Can be intgrated into a project with an API or utilized as an independent module
  • Integrates with any bug tracking tool that supports API

Modern Technologies

  • Based on a custom ML-powered solution & history-based test case prioritization approach
  • Uses a smart wizard UI to ensure user-friendly interface
  • Reusable with various projects via customized ETL connectors

Let’s Work Together

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