Enhancing test scripts
Example embodiments disclosed herein relate to enhancing test scripts with dynamic data. The disclosed embodiments include receiving production data that reflects real user interaction with an application process. Test scripts are generated based on the production data, where the test scripts simulate behavior relating to execution of the application process. The embodiments also include automatically enhancing the test scripts with dynamic data that includes at least one of correlation data and asynchronous data.
1. A method comprising:
receiving production data reflecting real user interaction with an application process;
generating, using a hardware processor, test scripts based on the production data, wherein the test scripts simulate behavior relating to execution of the application process;
subsequent to generating the test scripts:
identifying asynchronous data using predefined patterns; and
automatically enhancing the test scripts with dynamic data comprising at least the asynchronous data.
2. The method of claim 1 , wherein identifying asynchronous data comprises classification of a time and content of network traffic.
3. The method of claim 1 , wherein the dynamic data further comprises correlation data, wherein the correlation data identifies communication between at least one client computer and a server computer, and wherein the asynchronous data includes asynchronous data of a plurality of execution instances of the application process.
4. The method of claim 1 , comprising generating a plurality of execution instances of the application process based on the production data.
5. The method of claim 1 , comprising automatically enhancing the test scripts using at least one of pattern matching algorithms, pre-defined correlation rules, pre-defined asynchronous rules, and replacement and adaptation rules for injecting the enhanced test scripts into a testing environment.
6. The method of claim 1 , wherein behavior of the application process includes at least one of user behavior, network load, performance statistics and metrics, think time, and traffic behavior.
7. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:
receive production data reflecting real user interaction with an application process;
generate test scripts based on the production data, wherein the test scripts simulate behavior relating to execution of the application process;
subsequent to generating the test scripts:
identify asynchronous data using predefined patterns; and
automatically enhance the test scripts with dynamic data comprising at least the asynchronous data.
8. The method of claim 1 , further comprising running an asynchronous pattern matching algorithm to recreate asynchronous calls.
9. The method of claim 8 , wherein running the asynchronous pattern matching algorithm comprises recognizing poll and push patterns, and replacing different separate requests with application programming interface (API) calls.
10. The non-transitory computer readable medium of claim 7 , wherein the dynamic data further comprises correlation data, wherein the correlation data identifies communication between at least one client computer and a server computer, and wherein the asynchronous data includes asynchronous data generated by the server computer and provided to the at least one client computer.
11. The non-transitory computer readable medium of claim 7 , wherein the real user interaction includes a plurality of combination of sequences of execution paths of the application process.
12. The method of claim 3 , wherein the correlation data includes a session identifier for a particular session between the at least one client computer and the server computer.
13. The method of claim 3 , wherein the correlation data includes authentication data for the at least one client computer.
14. The method of claim 3 , further comprising identifying the correlation data using a response-based correlation technique.
15. The non-transitory computer readable medium of claim 7 , wherein the behavior of the application process includes at least one of user behavior, network load, performance statistics and metrics, think time, and traffic behavior.
16. A system comprising:
at least one hardware processor;
a production data extraction engine to extract production data reflecting real user interaction with an application process;
a test script generation engine executable by the at least one hardware processor to generate test scripts based on the production data, wherein the test scripts simulate behavior relating to execution of the application process;
a test script enhancement engine to:
identify asynchronous data using predefined patterns; and
automatically enhance the generated test scripts with dynamic data, wherein the dynamic data includes at least the asynchronous data.
17. The system of claim 16 , the test script enhancement engine to automatically:
enhance the generated test scripts with at least one of pattern matching algorithms, pre-defined correlation rules, pre-defined asynchronous rules, and testing environment replacement and adaptation rules;
insert the enhanced test scripts into a testing environment comprising at least one of functional testing environment, application programming interface (API) testing environment, and load testing environment; and
adapt the enhanced test script to the testing environment.
18. The system of claim 16 , wherein the real user interaction comprises multiple paths taken during execution of the application process and combinations of the multiple paths.
19. The method of claim 3 , further comprising identifying the correlation data using a replay-and-scan technique.
20. The method of claim 19 , wherein using the replay-and-scan technique includes comparing recorded data to replayed data until a failure point is identified.