Software test case maintenance

Abstract

Provided herein is technology relating to selecting an element in a software application and particularly, but not exclusively, to systems and methods for identifying a target element for testing a software application using artificial intelligence.

We claim: 
     
         1 . A method for identifying an element of a user interface that is a target element of a test case action, the method comprising:
 producing element definitions for elements of a user interface;   producing element match scores for said elements by comparing each element definition to a target element definition;   identifying the element having the highest element match score as the target element.   
     
     
         2 . The method of  claim 1  wherein producing said element definitions comprises determining attribute values of each element. 
     
     
         3 . The method of  claim 2  wherein determining attribute values comprises evaluating one or more of the element visual render, the element text, the element code, and/or the element context. 
     
     
         4 . The method of  claim 1  further comprising performing a test case action on the target element. 
     
     
         5 . The method of  claim 4  further comprising validating the result of performing the test case action on the target element. 
     
     
         6 . The method of  claim 5  wherein validating the result comprises producing a “test success” or “test failure” value. 
     
     
         7 . The method of  claim 6  wherein said “test success” or “test failure” value is used to train a neural net for identifying target elements. 
     
     
         8 . The method of  claim 1  further comprising validating page loading prior to producing element definitions for elements of said user interface. 
     
     
         9 . The method of  claim 6  further comprising alerting a user of a failed test when validating the result comprises producing a “test failure” value. 
     
     
         10 . The method of  claim 1  further comprising determining test case intent comprising an intended target and an intended action. 
     
     
         11 . The method of  claim 10  wherein determining test case intent comprises use of natural language processing. 
     
     
         12 . The method of  claim 10  comprising comparing the element having the highest element match score and the intended target. 
     
     
         13 . The method of  claim 10  comprising performing the intended action on the intended target. 
     
     
         14 . The method of  claim 1  wherein producing element match scores comprises use of a neural net. 
     
     
         15 . The method of  claim 3  wherein evaluating one or more of the element visual render, the element text, the element code, and/or the element context comprises element visual scoring, element language scoring, element code scoring, and/or element context scoring using a neural net. 
     
     
         16 . The method of  claim 3  wherein evaluating element context comprises producing a linear combination of a generative model and a discriminative model. 
     
     
         17 . The method of  claim 3  wherein evaluating element context comprises relative location of elements, element attributes weighted by stability scores, and/or high information elements. 
     
     
         18 . A system for identifying an element of a user interface that is a target element of a test case action, the system comprising:
 a component configured to produce element definitions for elements of a user interface;   a component configured to produce element match scores for said elements by comparing each element definition to a target element definition;   a component configured to identify the element having the highest element match score as the target element.   
     
     
         19 . The system of  claim 18  wherein said component configured to produce element definitions is configured to determine attribute values of each element. 
     
     
         20 . The system of  claim 19  wherein said component configured to determine attribute values is configured to evaluate one or more of the element visual render, the element text, the element code, and/or the element context. 
     
     
         21 . The system of  claim 18  further comprising a component configured to perform a test case action on the target element. 
     
     
         22 . The system of  claim 21  further comprising a component configured to validate the result of performing the test case action on the target element. 
     
     
         23 . The system of  claim 22  wherein said component configured to validate the result of performing the test case action on the target element is configured to produce a “test success” or “test failure” value. 
     
     
         24 . The system of  claim 23  wherein said “test success” or “test failure” value is used to train a neural net for identifying target elements. 
     
     
         25 . The system of  claim 18  further comprising a component configured to validate page loading prior to producing element definitions for elements of said user interface. 
     
     
         26 . The system of  claim 24  further comprising a component configured to alert a user of a failed test when validating the result comprises producing a “test failure” value. 
     
     
         27 . The system of  claim 18  further comprising a component configured to determine test case intent comprising an intended target and an intended action. 
     
     
         28 . The system of  claim 27  wherein said component configured to determine test case intent is configured to use natural language processing. 
     
     
         29 . The system of  claim 17  further comprising a neural net. 
     
     
         30 . The system of  claim 20  wherein said component configured to determine attribute values is configured to perform element visual scoring, element language scoring, element code scoring, and/or element context scoring using a neural net. 
     
     
         31 . The system of  claim 20  wherein said component configured to perform element context scoring is configured to produce a linear combination of a generative model and a discriminative model. 
     
     
         32 . The system of  claim 20  wherein said component configured to perform element context scoring is configured to determine relative location of elements, element attributes weighted by stability scores, and/or high information elements. 
     
     
         33 . Use of a method according to  claim 1  or a system according to  claim 18  to identify a target element of a software application UI.