Challenges

Since software development teams often work rapidly and deploy solutions swiftly, they have little or no time to perform structural quality analysis or identify critical programming errors until the testing phase. This adversely affects the velocity of software development and product release.

Combating this problem requires a solution that can apply real-time analytics to thousands of data items, test executions, insights, builds, code changes, and historical data from production to determine software release readiness. This solution should also provide accurate, real-time data to R&D managers to enable them to assess and plan efficient sprints through the analysis of quality trends and the risks presented by code changes over time.

Quality Intelligence Technology facilitates the collation and analysis of data from multiple sources thus providing software development teams with sufficient insight and visibility into factors affecting 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 — Analysis of thousands of data items in real time for every single build.
Insight — Provision of meaningful views and metrics that will guide the software development team to the right decisions.
Test Impact Analytics — Identifies which tests should be executed when a specific file or method is changed.
Test Quality Analytics — Directs teams on where to develop the minimal number of tests with the highest impact.
Release Quality Analytics — Determines release readiness and identifies and prevents untested code changes from reaching production.

Insert Test Coverage material from https://www.sealights.io/solutions/test-coverage/.