Image-based testing (IBT) is an alternative automation approach that relies on images rather than objects. It allows testing applications where objects are not recognized by traditional tools. IBT interacts directly with the visual display by finding and interacting with graphics. Tests are developed by capturing images, mapping logical names, and writing scripts similar to object-based testing but using image recognition strings instead of object properties. Challenges include needing images for all variations in display configurations and themes.
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Image Based Testing-IndicThreads-Q11
1. Image Based Testing- application technology independent automation Girish Kolapkar SAS R&D (India)
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6. What exactly IS Image-Based Testing? Image Based Testing Tool Operating System Application Under Test Display Buffer Mouse pointer events/ keyboard events queue
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17. Enhancements BitTolerance|BT= Optional. Specifies the integer percentage (1-100) of image bits or pixels that must match for an image to be considered a successful match. The default is, of course, 100. This means ALL pixels must match unless some other BitTolerance is specified. Samples: IExplorer="Image=<imagepath>;BitTolerance=70" IExplorer="Image=<imagepath>;ImageR=<imagepath>;BT=75"
19. Sample Test Records C SetApplicationMap Demo.MAP C LaunchApplication SampleApplication "c:afsamplesotnetotNetAppinDemo.exe" C WaitForGUI SampleApplication SampleApplication 15 T SampleApplication SampleApplication GetGUIImage c:utputImage1.jpg T SampleApplication SampleApplication RightClick T SampleApp SampleApp InputKeys "x" T SampleApplication SampleApplication GetGUIImage c:utputImage2.jpg T SampleApplication ButtonClose Click
Explain how IBT is all about graphics on screen and its all about images. There might be many other challenging UI technologies which are prevalent in market but do not have good tool support for testing. IBTs score a point here.
As automation inputs and outputs are produced and consumed on the OS level, the application technology becomes irrelevant and it can automate any GUI application which is displayed on screen.
Along with this, the ease associated with doing trivial operations like reading a text, verifying enabled/disabled state, selecting from a dropdown or grid etc. helps OBT score a good point when compared to IBT. IBTs offer an alternative here since they are UI technology neutral.
When seeking a &quot;window&quot; mapping the entire screen is searched for this image. When seeking a &quot;component&quot; mapping the search area is limited to the area of interest found for the &quot;window&quot; mapping. The bounds of the area of interest can be expanded by using the optional ImageR and ImageB items described below.
It is important to note that images must be saved in a format that provides no-loss of pixel information. Stored images must be able to match with 100% picture quality the image snapshots that will be retrieved from the screen. While &quot;BitTolerance&quot; discussed above allows for some degree of comparison fuzziness, it will usually not be able to compensate for stored images that cannot reproduce 100% picture quality due to excessive compression or intentional loss of pixel information.
Images stored for a particular Display typically work for most or all screen resolutions on that Display. This is an issue that each Display is configured for different levels of data compression. Bitmaps stored for the Normal Display have no data compression and no loss of image information. The displayed image for the Remote displays is usually compressed--intentionally removing image information. Because of this, Normal Display images usually will not match Remote Display images. To compensate for this, it is highly recommended that recognition images always be captured in the display mode that will be used for runtime testing. For example, if you know all testing will be done via Remote Desktop sessions, then it is best to have all recognition images captured and prepared during Remote Desktop sessions.
It is important to note that images must be saved in a format that provides no-loss of pixel information. Stored images must be able to match with 100% picture quality the image snapshots that will be retrieved from the screen. While &quot;BitTolerance&quot; discussed above allows for some degree of comparison fuzziness, it will usually not be able to compensate for stored images that cannot reproduce 100% picture quality due to excessive compression or intentional loss of pixel information.
It is important to note that images must be saved in a format that provides no-loss of pixel information. Stored images must be able to match with 100% picture quality the image snapshots that will be retrieved from the screen. While &quot;BitTolerance&quot; discussed above allows for some degree of comparison fuzziness, it will usually not be able to compensate for stored images that cannot reproduce 100% picture quality due to excessive compression or intentional loss of pixel information.
It is important to note that images must be saved in a format that provides no-loss of pixel information. Stored images must be able to match with 100% picture quality the image snapshots that will be retrieved from the screen. While &quot;BitTolerance&quot; discussed above allows for some degree of comparison fuzziness, it will usually not be able to compensate for stored images that cannot reproduce 100% picture quality due to excessive compression or intentional loss of pixel information.
imagepath can be the full path to a single image or to a directory containing multiple images. Multiple images are necessary if the target image is different in different environments. For example, on different platforms, or different versions of the application or operating system. The framework will search the screen for each of the images in the directory until it finds the match.