Quality Intelligence Technology

Challenges

Since software development teams often work rapidly and deploy solutions swiftly, there is often not much time to perform code quality analysis or identify critical programming errors until the testing phase. Typically, such deferrals adversely affect product development velocity and confidence in the product release.

What is needed to combat this problem is a solution that is adept at assessing software release viability by performing real-time analytics on thousands of data items, test executions, insights, builds, code changes, and historical production data. Such a solution should also provide accurate, real-time data to R&D managers so that they can analyze quality trends, assess risks, and refine development sprints to be more efficient.

SeaLights Quality Intelligence Technology enables easy, rapid collation and data analysis from multiple sources. These new abilities provide software development teams with better insight and clearer visibility into factors that affect the velocity, quality, and efficiency of their software engineering processes and deliverables.

The components of software quality intelligence include the following:

  • Data gathering — Collation of data from multiple sources across the software development pipeline, such as code changes, test stages, code execution, CI tools, production data, historical build information, and more.

  • Analytics — Real-time analysis of thousands of data items for each and every build.

  • Insight — Meaningful views and metrics that will guide the software development team to the best decisions.

  • Test Impact Analytics — Identifies which tests need to run when a specific file or method changes.

  • Test Gap Analytics — Directs teams on where to develop the minimal number of tests that will have the greatest benefit in achieving quality improvements.

  • Release Quality Analytics — Determines release readiness, then identifies and prevents untested code changes from reaching production.

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