Method and system for identifying non-executable human-readable test scenarios to be updated due to code changes

1. A computer implemented method for identifying non-executable human-readable test scenarios to be updated due to code changes, comprising:

receiving an old code version and a new code version of a data-oriented large-scale software system;

identifying changed code by running impact analysis on the old code version and the new code version;

identifying scenarios that use the changed code; wherein a scenario defines an activity that operates at least two transactions in a specific way and therefore scenario-based identification provides more accurate results than a transaction-based identification;

receiving non-executable human-readable test scenarios which comprise instructions expressed by user interaction activities;

identifying a subset of the non-executable human-readable test scenarios; wherein manually performing the instructions comprised in the subset is expected to cause the data-oriented large-scale software system to execute the changed code; and

describing likelihood of failure of a selected screen field of an identified non-executable human-readable test scenario based on the changed code used by the identified non-executable human-readable test scenario.

2. The computer implemented method of claim 1 , further comprising prioritizing manual performance of the identified non-executable human-readable test scenarios such that the identified non-executable human-readable test scenarios feature higher priorities than the other non-executable human-readable test scenarios.

3. The computer implemented method of claim 2 , further comprising providing a user with a prioritized task list for manually performing the identified non-executable human-readable test scenarios.

4. The computer implemented method of claim 2 , further comprising parsing the non-executable human-readable test scenarios before identifying the subset of non-executable human-readable test scenarios.

5. The computer implemented method of claim 2 , further comprising describing an expected failure of each identified non-executable human-readable test scenario based on the changed code used by each identified non-executable human-readable test scenario.

6. The computer implemented method of claim 5 , wherein the expected failure comprises a new mandatory field.

7. The computer implemented method of claim 5 , wherein the expected failure comprises a new screen.

8. The computer implemented method of claim 5 , further comprising providing a user with the identified non-executable human-readable test scenarios together with the expected failures.

9. The computer implemented method of claim 2 , wherein the changed code comprises changed code customizations.

10. A non-transitory computer readable medium for use in a computer to identify non-executable human-readable test scenarios to be updated due to code changes, the computer including a processor, and the non-transitory computer readable medium comprising:

program code for accessing an old code version and a new code version of a data-oriented large-scale software system;

program code for identifying changed code by running impact analysis on the old code version and the new code version;

program code for identifying scenarios that use the changed code; wherein a scenario defines an activity that operates at least two transactions in a specific way and therefore scenario-based identification provides more accurate results than a transaction-based identification;

program code for accessing non-executable human-readable test scenarios which comprise instructions expressed by user interaction activities;

program code for identifying a subset of the non-executable human-readable test scenarios;

wherein manually performing the instructions comprised in the subset is expected to cause the data-oriented large-scale software system to execute the changed code; and

program code for describing likelihood of failure of a selected screen field of an identified non-executable human-readable test scenario based on the changed code used by the identified non-executable human-readable test scenario.

11. The non-transitory computer readable medium of claim 10 , further comprising program code for prioritizing manual execution of the identified non-executable human-readable test scenarios such that the identified non-executable human-readable test scenarios feature higher priorities than the other non-executable human-readable test scenarios.

12. The non-transitory computer readable medium of claim 11 , further comprising program code for providing a user with a prioritized task list for manually performing the identified non-executable human-readable test scenarios.

13. The non-transitory computer readable medium of claim 11 , further comprising program code for parsing the non-executable human-readable test scenarios before identifying the subset of the non-executable human-readable test scenarios.

14. The non-transitory computer readable medium of claim 11 , further comprising program code for describing an expected failure of each identified non-executable human-readable test scenario based on the changed code used by each identified non-executable human-readable test scenario.

15. The non-transitory computer readable medium of claim 14 , wherein the expected failure comprises a new mandatory field.

16. The non-transitory computer readable medium of claim 14 , wherein the expected failure comprises a new screen.

17. The non-transitory computer readable medium of claim 11 , wherein the changed code comprises changed code customizations.

18. A computer system to identify non-executable human-readable test scenarios to be updated due to code changes, the computer system comprising:

a storage device containing computer usable code; and

a processing unit operable to execute the computer usable code to:

access an old code version and a new code version of a data-oriented large-scale software system;

identify changed code using impact analysis on the old code version and the new code version;

identify scenarios that use the changed code; wherein a scenario defines an activity that operates at least two transactions in a specific way and therefore scenario-based identification provides more accurate results than a transaction-based identification;

receive non-executable human-readable test scenarios which comprise instructions expressed by user interaction activities;

identify a subset of the non-executable human-readable test scenarios; wherein manually performing the instructions comprised in the subset is expected to cause the data-oriented large-scale software system to execute the changed code; and

describe likelihood of failure of a selected screen field of an identified non-executable human-readable test scenario based on the changed code used by the identified non-executable human-readable test scenario.

19. The computer system of claim 18 , wherein the processing unit further executes the computer usable code to prioritize manual performance of the identified non-executable human-readable test scenarios such that the identified non-executable human-readable test scenarios feature higher priorities than the other non-executable human-readable test scenarios.

20. The computer system of claim 19 , wherein the processing unit further executes the computer usable code to describe an expected failure of each identified non-executable human-readable test scenario based on the changed code used by each identified non-executable human-readable test scenario.

21. The computer system of claim 20 , wherein the expected failure comprises a new mandatory field.

22. The computer system of claim 20 , wherein the expected failure comprises a new screen.

23. The computer system of claim 19 , wherein the changed code comprises changed code customizations.