US2021390032A1PendingUtilityA1

Systems, methods and computer readable medium for visual software development quality assurance

Assignee: ENGINEER AI NAYA LTDPriority: Jun 15, 2020Filed: Jun 16, 2021Published: Dec 16, 2021
Est. expiryJun 15, 2040(~13.9 yrs left)· nominal 20-yr term from priority
G06F 1/1601A47B 97/00G06F 18/22A47B 2200/12G06F 11/366G06T 2207/30168G06T 7/001G06T 2200/24G06K 9/6215
59
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Claims

Abstract

A computer-implemented method for identifying discrepancies between a design image of a user interface for an application and a screenshot of the user interface as displayed by the application includes performing a first comparison between the design image and the screenshot to identify one or more discrepancies between the images, excluding from the discrepancies those corresponding to visual elements on the screenshot that include dynamic content, and generating an image of the screenshot, wherein the image includes a visual indication of every discrepancy detected by the second comparison as the identified discrepancies between the design image and the screenshot.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A quality assurance system for visual software development, comprising:
 a quality assurance application implemented on a computer using computer readable software instructions stored in non-transient memory, and configured for identifying discrepancies between a design image of a user interface for an application and a screenshot of the user interface as displayed by the application, wherein the quality assurance application is further configured to perform computer-implemented steps comprising:
 performing a first comparison between the design image and the screenshot to identify one or more discrepancies between the images; 
 excluding from the discrepancies those corresponding to visual elements on the screenshot that include dynamic content, the excluding comprising:
 identifying which of the discrepancies are structural discrepancies; 
 applying a mask to every visual element corresponding to a structural discrepancy on both the design image and the screenshot, wherein the mask is shaped like the visual element; 
 performing a second comparison between the masked design image and masked screenshot, wherein a lack of discrepancies detected by the second comparison between a masked visual element on the design image and the corresponding masked visual element on the screenshot indicates that the visual element on the screenshot includes dynamic content; and 
 
 generating an image of the screenshot, wherein the image includes a visual indication of every discrepancy detected by the second comparison as the identified discrepancies between the design image and the screenshot. 
   
     
     
         2 . The system of  claim 1 , wherein the steps further comprise generating and displaying a discrepancy map showing areas of discrepancy between the design image and the screenshot as shaded areas. 
     
     
         3 . The system of  claim 1 , wherein performing the first or the second comparison comprises traversing the design image and the screenshot using an SSIM analysis on every pixel. 
     
     
         4 . The system of  claim 1 , wherein the one or more discrepancies comprise color patches, missing elements, and structural discrepancies. 
     
     
         5 . The system of  claim 1 , wherein each of color patches, missing elements, and structural discrepancies is identified based on different combinations of local luminance similarity, local contrast similarity, and local structure similarity. 
     
     
         6 . The system of  claim 1 , wherein applying the mask comprises applying a contrast-based mask than applies a shadow to regions of the visual element corresponding to the structural discrepancy where contrast is higher than a small value. 
     
     
         7 . The system of  claim 1 , further comprising generating a bug report that includes an inventory of the identified discrepancies, their location, and measures of the divergence of their corresponding visual elements from the design image. 
     
     
         8 . A computer-implemented method for identifying discrepancies between a design image of a user interface for an application and a screenshot of the user interface as displayed by the application, the method comprising:
 performing a first comparison between the design image and the screenshot to identify one or more discrepancies between the images;   excluding from the discrepancies those corresponding to visual elements on the screenshot that include dynamic content, the excluding comprising:
 identifying which of the discrepancies are structural discrepancies; 
 applying a mask to every visual element corresponding to a structural discrepancy on both the design image and the screenshot, wherein the mask is shaped like the visual element; 
 performing a second comparison between the masked design image and masked screenshot, wherein a lack of discrepancies detected by the second comparison between a masked visual element on the design image and the corresponding masked visual element on the screenshot indicates that the visual element on the screenshot includes dynamic content; and 
   generating an image of the screenshot, wherein the image includes a visual indication of every discrepancy detected by the second comparison as the identified discrepancies between the design image and the screenshot.   
     
     
         9 . The method of  claim 8 , further comprising generating and displaying a discrepancy map showing areas of discrepancy between the design image and the screenshot as shaded areas. 
     
     
         10 . The method of  claim 8 , wherein performing the first or the second comparison comprises traversing the design image and the screenshot using an SSIM analysis on every pixel. 
     
     
         11 . The method of  claim 8 , wherein the one or more discrepancies comprise color patches, missing elements, and structural discrepancies. 
     
     
         12 . The method of  claim 11 , wherein each of color patches, missing elements, and structural discrepancies is identified based on different combinations of local luminance similarity, local contrast similarity, and local structure similarity. 
     
     
         13 . The method of  claim 8 , wherein applying the mask comprises applying a contrast-based mask than applies a shadow to regions of the visual element corresponding to the structural discrepancy where contrast is higher than a small value. 
     
     
         14 . The method of  claim 8 , further comprising generating a bug report that includes an inventory of the identified discrepancies, their location, and measures of the divergence of their corresponding visual elements from the design image.

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