System and method for dynamic translation code optimization

• US 10,809,986 B2
• Filed: 06/04/2018
• Issued: 10/20/2020
• Est. Priority Date: 04/16/2018
• Status: Active Grant

• Current Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Original Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Inventors: Ramachandra, Madhavan Kalkunte, Sharma, Siddharth
• Primary Examiner(s): Nguyen, Mongbao
• Application Number:
  US15/997,065
• Publication Number:
  US 20190317745A1
• Time in Patent Office: 869 Days
• CPC Class Codes: G06F 40/154 Tree transformation for tree-structured or markup documents, e.g. XSLT, XSL-FO or stylesheets
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 8/443 Optimisation
• CPC Class Codes: G06F 8/447 Target code generation
• CPC Class Codes: G06F 8/77 Software metrics

Abstract

An system and a method for the optimization of dynamic code translation is disclosed. A cloud-based front-end application receives an input module, rule specification and a translation definition. The cloud-based front-end application transmits the input module, rule specification and translation definition to a back-end processing module. The back-end processing module parses the three inputs and stores them in separate data structures. The back-end processing module performs a non-executing analysis of the translation definition based on the rule specification, generating a set of defects. The back-end processing module performs an execution of the translation definition with the input module, generating a report of system metrics. The set of defects and the system metrics are transmitted back to a GUI running on the cloud-based front-end application.

Claims

1. A method for the optimization of information translation comprising:

receiving an input module, translation definition, and rules specification at a back-end processing module from a computing device rendering a graphical user interface of a cloud-based front-end application, wherein the input module corresponds to an input data set to be translated from one format to another format, the rules specification is a user-defined set of rules, and the translation definition provides a syntax for translations of elements in the input module,

parsing the rules specification and the translation definition into a first data structure and a second data structure, respectively, wherein the first data structure is interoperable with the second data structure,

applying the first data structure to the second data structure, wherein the cloud-based front-end application of the first data structure to the second data structure identifies defects in the translation definition,

generating a set of defects based on the cloud-based front-end application and displayable in a tabular form, each defect within the set of defects associated within the tabular form with an identification for a file associated with the defect, a rule, a line, and a message,

parsing the input module into a third data structure,

processing the third data structure according to the second data structure,

recording system metrics based on the processing of the third data structure,

generating a report based on the system metrics,

transmitting an analysis to the cloud-based front-end application, wherein the analysis comprises the set of defects and the report,

receiving the analysis from the back-end processing module, and

displaying the analysis in a graphical user interface, wherein the graphical user interface correlates a relative data within the analysis with the input module, translation definition and the rules specification.

2. The method of claim 1, wherein the set of defects comprise instances of an identified coding practice.

3. The method of claim 1, wherein the system metrics comprise a system level summary of utilized resources based on the applying of the third data structure to the second data structure.

4. The method of claim 1, wherein the system metrics comprise a granular level summary of the utilized resources based on the applying of the third data structure to the second data structure.

5. The method of claim 1, wherein the input module corresponds to a extensible markup language (XML) input file, the translation definition corresponds to a extensible stylesheet language transformation (XSLT) file, and the rules specification corresponds to a extensible markup language (XML) file.

6. The method of claim 1, the applying the third data structure to the second data structure comprises inputting the third data structure and the second data structure to a translation execution library.

7. The method of claim 1, wherein the applying the first data structure to the second data structure comprises a non-executing static analysis of the rules specification and the translation definition.

8. A non-transitory computer readable medium for the optimization of information translation, having stored thereon, instructions that when executed in a computing system, cause the computing system to perform operations comprising:

receiving an input module, translation definition, and rules specification at a back-end processing module from a computing device rendering a graphical user interface of a cloud-based front-end application, wherein the input module corresponds to an input data set to be translated from one format to another format, the rules specification is a user-defined set of rules, and the translation definition provides a syntax for translations of elements in the input module,

parsing the rules specification in to a first data structure and the translation definition into a second data structure wherein the first data structure is interoperable with the second data structure,

applying the first data structure to the second data structure, wherein the cloud-based front-end application of the first data structure to the second data structure identifies defects in the translation definition,

generating a set of defects based on the cloud-based front-end application and displayable in a tabular form, each defect within the set of defects associated within the tabular form with an identification for a file associated with the defect, a rule, a line, and a message,

parsing the input module into a third data structure,

processing the third data structure according to the second data structure,

recording system metrics based on the processing of the third data structure to the second data structure,

generating a report based on the system metrics,

transmitting an analysis to the cloud-based front-end application wherein the analysis comprises the set of defects and the report, and

displaying the analysis in a graphical user interface, wherein the graphical user interface correlates a relative data within the analysis with the input module, translation definition and the rules specification.

9. The computer readable medium of claim 8, wherein the set of defects comprise instances of an identified coding practice.

10. The computer readable medium of claim 8, wherein the system metrics comprise a system level summary of utilized resources based on the applying of the third data structure to the second data structure.

11. The computer readable medium of claim 8, wherein the system metrics comprise a granular level summary of the utilized resources based on the applying of the third data structure to the second data structure.

12. The computer readable medium of claim 8, the applying the third data structure to the second data structure comprises inputting the third data structure and the second data structure to a translation execution library.

13. The computer readable medium of claim 8, wherein the applying the first data structure to the second data structure comprises a non-executing static analysis of the rules specification and the translation definition.

14. A system for optimization of information translation comprising:

one or more servers executing a back-end processing module communicatively coupled to a computing device rendering a graphical user interface of a cloud-based front-end application configured to;

receive an input module, a translation definition and a rules specification from the cloud-based front-end application, wherein the input module corresponds to an input data set to be translated from one format to another format, the rules specification is a user-defined set of rules, and the translation definition provides a syntax for translations of elements in the input module,

parse the rules specification and the translation definition into a first data structure and a second data structure, respectively, wherein the first data structure is interoperable with the second data structure,

apply the first data structure to the second data structure, wherein the cloud-based front-end application of the first data structure to the second data structure identifies defects in the translation definition,

generate a set of defects based on the cloud-based front-end application and displayable in a tabular form, each defect within the set of defects associated within the tabular form with an identification for a file associated with the defect, a rule, a line, and a message,

parse the input module into a third data structure,

process the third data structure according to the second data structure,

record system metrics based on the processing of the third data structure,

generate a report based on the system metrics, and

transmit an analysis to the cloud-based front-end application wherein the analysis comprises the set of defects and the report; and

wherein the cloud-based front-end application receives the analysis from the back-end processing module and displays the analysis in the graphical user interface, wherein the graphical user interface correlates a relative data within the analysis with the input module, translation definition and the rules specification.

15. The system of claim 14, wherein the set of defects comprise instances of an identified coding practice.

16. The system of claim 14, wherein the system metrics comprise a system level summary of utilized resources based on the applying of the third data structure to the second data structure.

17. The system of claim 14, wherein the system metrics comprise a granular level summary of the utilized resources based on the applying of the third data structure to the second data structure.

18. The system of claim 14, wherein the input module corresponds to a extensible markup language (XML) input file, the translation definition corresponds to a extensible stylesheet language transformation (XSLT) file, and the rules specification corresponds to a extensible markup language (XML) file.

19. The system of claim 14, the applying the third data structure to the second data structure comprises inputting the third data structure and the second data structure to a translation execution library.

20. The system of claim 14, wherein the applying the first data structure to the second data structure comprises a non-executing static analysis of the rules specification and the translation definition.