DEVELOPMENT AND PRODUCTION DATA BASED APPLICATION EVOLUTION

• US 20180046570A1
• Filed: 07/26/2017
• Published: 02/15/2018
• Est. Priority Date: 08/11/2016
• Status: Active Grant

• Current Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Original Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Inventors: KAULGUD, Vikrant, SINGI, Kapil, SAXENA, Amitabh, DINAKAR, Chethana, PODDER, Sanjay
• Granted Patent: US 10,452,521 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 11/3672 Test management
• CPC Class Codes: G06F 11/3676 for coverage analysis
• CPC Class Codes: G06F 11/3684 for test design, e.g. generating new test cases
• CPC Class Codes: G06F 8/70 Software maintenance or management
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

According to examples, development and production data based application evolution may include ascertaining a goal, development data, and production data for a specified release of an application. Development and production data based application evolution may further include determining, from the development data, a feature, a use-case associated with the feature, and a plurality of tasks associated with the use-case. Further, development and production data based application evolution may include determining, from the production data, production log data and user feedback, determining, from the production log data and the user feedback data, criteria, ascertaining, a weightage for each criterion of the criteria, and determining, based on the weightage, a task priority for each task of the plurality of tasks to be applied to a different release of the application.

Claims

1. A development and production data based application evolution system comprising:

a processor; and

a memory storing machine readable instructions that when executed by the processor cause the processor to;

ascertain application strategy information for a specified release of an application;

determine, from the application strategy information for the specified release of the application, a goal for the specified release of the application;

ascertain development data and production data for the specified release of the application;

determine, from the development data for the specified release of the application,

a feature associated with the specified release of the application,

at least one use-case associated with the feature, and

a plurality of tasks associated with the at least one use-case;

determine, from the production data, production log data and user feedback data associated with operation of the specified release of the application;

determine, from the production log data and the user feedback data, criteria associated with the specified release of the application;

ascertain a weightage for each criterion of the criteria associated with the specified release of the application;

determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, a task priority for each task of the plurality of tasks to be applied to a different release of the application; and

apply, based on the determination of the task priority for each task of the plurality of tasks to be applied to the different release of the application, test cases associated with a highest priority task of the plurality of tasks to the different release of the application.

2. The development and production data based application evolution system according to claim 1, wherein

the production log data includes at least one of crashes associated with a particular display for the specified release of the application, errors associated with the particular display for the specified release of the application, and usage of the particular display for the specified release of the application, and

the user feedback data includes at least one of issues associated with the specified release of the application and popularity associated with the specified release of the application.

3. The development and production data based application evolution system according to claim 1, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the user feedback data by

performing a natural language processing analysis on the user feedback data,

identifying, based on the performing of the natural language processing analysis on the user feedback data, at least one keyword,

identifying a mapping of the at least one keyword to each task of the plurality of tasks, each use-case of the at least one use-case, and the feature,

for each identified mapping of the at least one keyword, increasing a weightage associated with each corresponding task of the plurality of tasks,

identifying a task of the plurality of tasks including a highest weightage, and

incrementing, for the identified task of the plurality of tasks including the highest weightage, the number of occurrences of the criterion associated with the user feedback data.

4. The development and production data based application evolution system according to claim 1, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the user feedback data by

performing a natural language processing analysis on the user feedback data,

identifying, based on the performing of the natural language processing analysis on the user feedback data, at least one keyword,

identifying a mapping of the at least one keyword to each task of the plurality of tasks, each use-case of the at least one use-case, and the feature,

for each identified mapping of the at least one keyword, increasing a weightage associated with each corresponding task of the plurality of tasks,

determining, whether a task of the plurality of tasks includes a highest weightage,

in response to a determination that no task of the plurality of tasks includes the highest weightage, identifying tasks of the plurality of tasks that include a same highest weightage, and

incrementing, for the identified tasks of the plurality of tasks that include the same highest weightage, the number of occurrences of the criterion associated with the user feedback data.

5. The development and production data based application evolution system according to claim 1, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the production log data by

identifying displays associated with the specified release of the application,

identifying, for each display of the displays associated with the specified release of the application, at least one criterion of the criteria,

identifying a mapping of each display of the displays associated with the specified release of the application and the at least one criterion of the criteria to each task of the plurality of tasks,

for each identified mapping, increasing a weightage associated with each corresponding task of the plurality of tasks,

identifying a task of the plurality of tasks including a highest weightage, and

incrementing, for the identified task of the plurality of tasks including the highest weightage, the number of occurrences of the criterion associated with the production log data.

6. The development and production data based application evolution system according to claim 1, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the production log data by

identifying displays associated with the specified release of the application,

identifying, for each display of the displays associated with the specified release of the application, at least one criterion of the criteria,

identifying a mapping of each display of the displays associated with the specified release of the application and the at least one criterion of the criteria to each task of the plurality of tasks,

for each identified mapping, increasing a weightage associated with each corresponding task of the plurality of tasks,

determining, whether a task of the plurality of tasks includes a highest weightage,

in response to a determination that no task of the plurality of tasks includes the highest weightage, identifying tasks of the plurality of tasks that include a same highest weightage, and

incrementing, for the identified tasks of the plurality of tasks that include the same highest weightage, the number of occurrences of the criterion associated with the production log data.

7. The development and production data based application evolution system according to claim 1, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of each criterion of the criteria respectively associated with the production log data or the user feedback data;

determine, for each criterion of the criteria, an averaging-based weightage value by dividing a number of occurrences of a criterion for a task by a total number of occurrences of the criterion for the plurality of the tasks; and

determine a global priority of each task by

determining, for each criterion of the criteria, a product of the weightage ascertained for a respective criterion and the averaging-based weightage value for the respective criterion, and

determining a total of each of the products for each criterion of the criteria.

8. The development and production data based application evolution system according to claim 7, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprise machine readable instructions to cause the processor to:

ascertain, for each task of the plurality of tasks, a feature priority; and

determine, for each task of the plurality of tasks, the task priority by determining a product of the global priority of a corresponding task and the feature priority of the corresponding task.

9. The development and production data based application evolution system according to claim 1, further comprising machine readable instructions to cause the processor to:

apply, based on the determination of the task priority for each task of the plurality of tasks to be applied to the different release of the application, further test cases associated with remaining tasks of the plurality of tasks in order of the task priority to the different release of the application.

10. A method for development and production data based application evolution, the method comprising:

ascertaining, by at least one hardware processor, from application strategy information for a specified release of an application, a goal for the specified release of the application;

ascertaining, by the at least one hardware processor, development data and production data for the specified release of the application;

determining, by the at least one hardware processor, from the development data for the specified release of the application,

a feature associated with the specified release of the application,

at least one use-case associated with the feature, and

a plurality of tasks associated with the at least one use-case;

determining, by the at least one hardware processor, from the production data, production log data and user feedback data associated with operation of the specified release of the application;

determining, by the at least one hardware processor, from the production log data and the user feedback data, criteria associated with the specified release of the application;

ascertaining, by the at least one hardware processor, a weightage for each criterion of the criteria associated with the specified release of the application; and

determining, by the at least one hardware processor, based on the weightage for each criterion of the criteria associated with the specified release of the application, a task priority for each task of the plurality of tasks to be applied to a different release of the application.

11. The method according to claim 10, further comprising:

applying, by the at least one hardware processor, based on the determination of the task priority for each task of the plurality of tasks to be applied to the different release of the application, test cases associated with a highest priority task of the plurality of tasks to the different release of the application.

12. The method according to claim 11, further comprising:

applying, by the at least one hardware processor, based on the determination of the task priority for each task of the plurality of tasks to be applied to the different release of the application, further test cases associated with remaining tasks of the plurality of tasks in order of the task priority to the different release of the application.

13. The method according to claim 10, wherein ascertaining, by the at least one hardware processor, the weightage for each criterion of the criteria associated with the specified release of the application further comprises:

ascertaining, by the at least one hardware processor, the weightage for each criterion of the criteria associated with the specified release of the application based on

crowd sourcing of weights associated with the specified release of the application, and

implementing a pairwise comparison of each of the criterion.

14. The method according to claim 10, wherein determining, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprises:

determining, by the at least one hardware processor, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the user feedback data by

performing a natural language processing analysis on the user feedback data,

identifying, based on the performing of the natural language processing analysis on the user feedback data, at least one keyword,

identifying a mapping of the at least one keyword to each task of the plurality of tasks, each use-case of the at least one use-case, and the feature,

for each identified mapping of the at least one keyword, increasing a weightage associated with each corresponding task of the plurality of tasks,

identifying a task of the plurality of tasks including a highest weightage, and

incrementing, for the identified task of the plurality of tasks including the highest weightage, the number of occurrences of the criterion associated with the user feedback data.

15. The method according to claim 10, wherein determining, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application further comprises:

determining, by the at least one hardware processor, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the production log data by

identifying displays associated with the specified release of the application,

identifying, for each display of the displays associated with the specified release of the application, at least one criterion of the criteria,

identifying a mapping of each display of the displays associated with the specified release of the application and the at least one criterion of the criteria to each task of the plurality of tasks,

for each identified mapping, increasing a weightage associated with each corresponding task of the plurality of tasks,

identifying a task of the plurality of tasks including a highest weightage, and

incrementing, for the identified task of the plurality of tasks including the highest weightage, the number of occurrences of the criterion associated with the production log data.

16. A non-transitory computer readable medium having stored thereon machine readable instructions to provide development and production data based application evolution, the machine readable instructions, when executed, cause a processor to:

ascertain, from application strategy information for a specified release of an application, a goal for the specified release of the application;

ascertain, development data and production data for the specified release of the application;

determine, from the development data for the specified release of the application,

a feature associated with the specified release of the application,

at least one use-case associated with the feature, and

a plurality of tasks associated with the at least one use-case;

determine, from the production data, at least one of production log data and user feedback data associated with operation of the specified release of the application;

determine, from the at least one of the production log data and the user feedback data, criteria associated with the specified release of the application;

ascertain, a weightage for each criterion of the criteria associated with the specified release of the application; and

determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, a task priority for each task of the plurality of tasks to be applied to a different release of the application.

17. The non-transitory computer readable medium of claim 16, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application, when executed, further cause the processor to:

for the user feedback data, determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the user feedback data by

performing a natural language processing analysis on the user feedback data,

identifying, based on the performing of the natural language processing analysis on the user feedback data, at least one keyword,

identifying a mapping of the at least one keyword to each task of the plurality of tasks, each use-case of the at least one use-case, and the feature,

for each identified mapping of the at least one keyword, increasing a weightage associated with each corresponding task of the plurality of tasks,

determining, whether a task of the plurality of tasks includes a highest weightage,

in response to a determination that no task of the plurality of tasks includes the highest weightage, identifying tasks of the plurality of tasks that include a same highest weightage, and

incrementing, for the identified tasks of the plurality of tasks that include the same highest weightage, the number of occurrences of the criterion associated with the user feedback data.

18. The non-transitory computer readable medium of claim 16, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application, when executed, further cause the processor to:

for the production log data, determine, for each task of the plurality of tasks, a number of occurrences of a criterion associated with the production log data by

identifying displays associated with the specified release of the application,

identifying, for each display of the displays associated with the specified release of the application, at least one criterion of the criteria,

identifying a mapping of each display of the displays associated with the specified release of the application and the at least one criterion of the criteria to each task of the plurality of tasks,

for each identified mapping, increasing a weightage associated with each corresponding task of the plurality of tasks,

determining, whether a task of the plurality of tasks includes a highest weightage,

in response to a determination that no task of the plurality of tasks includes the highest weightage, identifying tasks of the plurality of tasks that include a same highest weightage, and

incrementing, for the identified tasks of the plurality of tasks that include the same highest weightage, the number of occurrences of the criterion associated with the production log data.

19. The non-transitory computer readable medium of claim 16, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application, when executed, further cause the processor to:

determine, for each task of the plurality of tasks, a number of occurrences of each criterion of the criteria respectively associated with the at least one of the production log data and the user feedback data;

determine, for each criterion of the criteria, an averaging-based weightage value by dividing a number of occurrences of a criterion for a task by a total number of occurrences of the criterion for the plurality of the tasks; and

determine a global priority of each task by

determining, for each criterion of the criteria, a product of the weightage ascertained for a respective criterion and the averaging-based weightage value for the respective criterion, and

determining a total of each of the products for each criterion of the criteria.

20. The non-transitory computer readable medium of claim 19, wherein the machine readable instructions to determine, based on the weightage for each criterion of the criteria associated with the specified release of the application, the task priority for each task of the plurality of tasks to be applied to the different release of the application, when executed, further cause the processor to:

ascertain, for each task of the plurality of tasks, a feature priority; and

determine, for each task of the plurality of tasks, the task priority by determining a product of the global priority of a corresponding task and the feature priority of the corresponding task.