EyeAutomate is a visual script runner. A visual script contains images that are located using the Eye image recognition algorithm. Edit the visual scripts in EyeStudio or using a text editor.

Three Generations of Tools

There are three generations of automated GUI test tools:

  • Position based. Record and replay using fixed coordinates. Worked fine for old command line applications since the screen resolution was fixed and all applications operated in full screen mode.
  • Widget based. Window based applications can have any screen size and location. The GUI widgets are encapsulated to be able to record scripts that are tolerant to changes in the user interface. This fixes the problem with the first generation tools but widget based automation tools are very sensitive to third party or customized widgets. This makes them really inefficient to use unless the application under test was designed with test automation, and the selected test automation tool, in mind.
  • Visual GUI Testing (VGT). Based on image recognition, the test tool can actually visually identify (see) the position on the screen to interact with just like a manual tester. This makes the third generation test automation tools insensitive to both fixed coordinates and implementation details of the user interface. A Visual GUI Testing tool can automate any type of application regardless of framework and operating system used.

EyeAutomate support techniques from all the three generations.

Pure Java

EyeAutomate is 100% pure Java and contains no native code. This means that you will be able to create and run scripts on any platform that supports Java. EyeAutomate can also be used for automating any type of application that has a user interface regardless of how it is implemented.

All commands are provided with both binary and source code in the “custom” folder. Adjust existing commands or create your own. All commands are loaded dynamically from the “custom” folder.

The Eye

EyeAutomate is built around the Eye that contains the image recognition algorithm. The image recognition needs to be both fast and tolerant to be efficient for test automation.

The Eye can locate images on any number of displays and uses all CPU’s available. A higher screen resolution will reduce the detection speed while the number of available CPU’s will increase the detection speed.