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Sunday, March 30, 2025

Maximize Software Test Coverage with Advanced Reporting


When your product is under test, you want to see results quickly. With Keysight’s Eggplant Test, you have at-a-glance reporting of all your modeling and testing activities.

Your dashboard offers fast answers to questions such as:

  • How much longer do I have to test before I hit my coverage targets?
  • How many bugs do 112 test failures correspond to?
  • Which types of UI elements have been failing?

A screenshot of the Eggplant software interface, displaying various data visualizations and metrics related to software testing. It includes automated actions, test cases, bug hunting details, and coverage statistics, providing a comprehensive overview of software application performance and issues through visual data representations.

Your main dashboard shows your project’s status, so you can easily:

  • check whether your test cases have all been hit
  • see the percentage of passed vs. failed test cases
  • spot any trending failures
  • and much more!

Maximize Test Coverage with AI

Test coverage is an important measure of software quality and an essential part of software maintenance. With AI, test teams can increase test coverage to ultimately deliver better software faster.

The Coverage Heatmap (see below) visualizes the coverage percentages of states and actions within a model.

A screenshot of the Eggplant software interface, displaying the coverage heatmap for a specific software model where the areas most tested are in dark blue and the areas the least tested are in gray.

One of the key benefits of the model-based approach to software testing is that you can test all possible user journeys of your application. The heatmap is a great way to visualize which parts of your application are being tested, and which parts are being missed.

The heatmap shows not only which actions and states have been tested, but also which combinations of paths have been tested and how much.

In the figure below, the Coverage Overview shows the pass/fail rate of your total number of test runs and the coverage percentages against the number of runs. In this example, you can see that out of 26 total test runs, 25 passed and just 1 failed. (That’s pretty good!)

A graphical representation of test results, featuring a line graph that tracks the total coverage percentage against the number of runs for different testing types. The sections detail the history, outcomes, and coverage prediction, offering a visual insight into the efficiency and coverage of various testing methods over time.

The Coverage Prediction Table estimates how long it will take to reach 90% coverage, based on the actual historical results plotted in the graph.

If 90% coverage has been achieved, the values will display “Done”, otherwise, the number of hours remaining will be indicated.

A coverage prediction table where the overall coverage prediction is 90%. Testing of all nodes is done. Testing of all pairs is done. Extended Testing is estimated to have 0.23 hours remaining and Full Exploratory Testing is estimated to have 1.75 hours remaining.

This is especially helpful for release managers, who need to know exactly how much more testing is required until the application is ready and robustly tested.

Find Bugs Before They Spread

Every new update or feature can introduce bugs that impact user experiences. Intelligent automated testing expands test coverage to parts of your application with known issues.

By analyzing failure patterns across test runs, Eggplant helps teams find defects quickly.

To get a full tour of Eggplant advanced reporting capabilities, take a fully self-guided tour of the dashboard today!

Take the tour



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