Mapping of test cases to test data for computer software testing

Patent metadata

Field	Value
Publication number	US-11544177-B2
Application number	US-202016952721-A
Country	US
Kind code	B2
Filing date	Nov 19, 2020
Priority date	Nov 19, 2020
Publication date	Jan 3, 2023
Grant date	Jan 3, 2023

Abstract

A first test case identifier that indicates a first test case is received. The first test case is indicative of testing one or more features of an application associated with the electronic marketplace. The first test case identifier is compared to a plurality of attributes. The plurality of attributes are associated with one or more listings that describe one or more items for sale in an electronic marketplace. Based at least in part on the comparing, it is determined that a first set of attributes, of the plurality of attributes, are test data candidates to be used as input to the first test case. Based at least in part on the determining, the first test case is caused to be run using at least one of the first set of attributes as test data for input.

First claim

What is claimed is:

1. A computerized system comprising:
one or more processors; and
computer storage memory having computer-executable instructions stored thereon which, when executed by the one or more processors, implement a method comprising:
receiving one or more listings, each listing of the one or more listings describes an item for sale in an electronic marketplace;
extracting a plurality of attributes from the one or more listings, the plurality of attributes include a first set of natural language characters that indicate one or more attributes of the one or more listings;
receiving a first test case identifier that describes, via a second set of natural language characters, a first test case, the first test case is indicative of testing one or more features of an application of the electronic marketplace;
comparing the first set of natural language characters to the second set of natural language characters;
based at least in part on the comparing, tagging a first set of attributes, of the plurality of attributes, as test data candidates to be used as input to the first test case; and
based at least in part on the tagging, causing the first test case to be run using at least one of the first set of attributes as test data for input.

2. The system of claim 1 , wherein the first test case is one of an automated test case or a manual test case.

3. The system of claim 1 , wherein the comparing is based on using natural language processing.

4. The system of claim 1 , wherein the comparing includes using a machine learning model that maps a first feature vector representing the first test case identifier to a second feature vector representing the plurality of attributes and determining a distance between the first feature vector and the second feature vector.

5. The system of claim 1 , wherein the method further comprises copying the one or more listings, as raw data, from a first data store into a staging data store.

6. The system of claim 5 , wherein the method further comprises anonymizing user sensitive data indicated in the first data store such that the staging data store includes the anonymized user sensitive data.

7. The system of claim 1 , wherein the method further comprising generating an index for the plurality of attributes such that the plurality of attributes can be used for a query or command.

8. The system of claim 1 , wherein the method further comprises transmitting the plurality of attributes to a discovery service, wherein the discovery service performs the tagging, and wherein the discovery service corresponds to an entity that is distinct from the electronic marketplace.

9. The system of claim 1 , wherein the first set of attributes include at least one of: tracking flags from the one or more listings, item data from the one or more listings, and seller data from the one or more listings.

10. A computer-implemented method comprising:
receiving a first test case identifier that describes, via a first set of natural language characters, a first test case, the first test case is indicative of testing one or more features of an application of an electronic marketplace;
comparing a representation of the first set of natural language characters to a representation of a second set of natural language characters included in a plurality of attributes, the plurality of attributes being associated with one or more listings that describe one or more items for sale in the electronic marketplace;
based at least in part on the comparing, determining that a first set of attributes, of the plurality of attributes, are test data candidates to be used as input to the first test case; and
based at least in part on the determining, causing the first test case to be run using at least one of the first set of attributes as test data for input.

11. The method of claim 10 , wherein the first test case is one of an automated test case or a manual test case, and wherein the application is not yet deployed.

12. The method of claim 10 , wherein the comparing includes comparing one or more natural language characters within the first test case identifier with other natural language characters within the plurality of attributes using natural language processing.

13. The method of claim 10 , wherein the comparing includes using a machine learning model that maps a first feature vector representing the first test case identifier to a second feature vector representing the plurality of attributes and determining a distance between the first feature vector and the second feature vector.

14. The method of claim 10 , further comprising copying the one or more listings, as raw data, from a first data store into a staging data store.

15. The method of claim 14 , further comprising anonymizing user sensitive data indicated in the first data store such that the staging data store includes the anonymized user sensitive data.

16. The method of claim 10 , further comprising generating a record for the plurality of attributes such that the plurality of attributes can be used for a query or command.

17. The method of claim 10 , wherein the plurality of attributes are structured as one or more records such that the one or more records are configured to be queried by a discovery service, the discovery service corresponds to an entity that is distinct from the electronic marketplace.

18. The method of claim 10 , wherein the first set of attributes include tracking flags from the one or more listings and item data from the one or more listings.

19. One or more computer storage media having computer-executable instructions embodied thereon that, when executed, by one or more processors, cause the one or more processors to perform a method, the method comprising:
receiving a first test case identifier that describes, via a first set of natural language characters, a first test case, the first test case is indicative of testing one or more features of an application of an electronic marketplace;
comparing the first set of natural language characters to a second set of natural language characters included in a plurality of attributes, the plurality of attributes being associated with one or more listings that describe one or more items for sale in the electronic marketplace;
based at least in part on the comparing, determining that a first set of attributes, of the plurality of attributes, are test data candidates to be used as input to the first test case; and
based at least in part on the determining, causing the first test case to be run using at least one of the first set of attributes as test data for input.

20. The one or more computer storage media of claim 19 , wherein the plurality of attributes are structured as one or more records in a different format relative to a format structured by the electronic marketplace.

Assignees

• Ebay Inc

Inventors

• Periyathambi Ramesh
• Lancewicki Tomer
• Padmanabhan Senthil Kumar
• Rentachintala Srikanth
• Doraisamy Kandakumar

Classifications

• G06N3/08

  Learning methods · CPC title

• G06N3/045

  Combinations of networks · CPC title

• G06N20/00

  Machine learning · CPC title

• G06F21/6254

  by anonymising data, e.g. decorrelating personal data from the owner's identification · CPC title

• G06F11/3688 Primary

  for test execution, e.g. scheduling of test suites · CPC title