主权项 |
1. A computer-implemented method comprising:
receiving a first request to generate a first test case, wherein the first request comprises a coverage schema associated with a first set of events to be covered in the generated first test case; updating the coverage schema, wherein the updating the coverage schema comprises adding a second set of events to be covered in the generated first test case, wherein the second set of events is determined using machine learning techniques or by performing one of a union operation, an intersection operation, or a cross-product operation between at least two events of the first set of events; generating constraints used to satisfy requirements for meeting the first set of events and the second set of events in the updated coverage schema; responsive to the generating constraints used to satisfy requirements for meeting the first set of events and the second set of events in the updated coverage schema, adding the generated constraints to a constraint library; generating the first test case using the generated constraints and the updated coverage schema; performing a test simulation to identify a passing test case; responsive to the performing a test simulation to identify a passing test case, updating a coverage database to reflect the identified passing test case; receiving a second request to generate a second test case, wherein the second request comprises a coverage schema associated with a third set of events to be covered in the generated second test case; the updating the coverage schema, wherein the updating the coverage schema comprises adding a fourth set of events to be covered in the generated second test case, wherein the fourth set of events is determined using machine learning techniques or by performing one of a union operation, an intersection operation, or a cross-product operation between at least two events of the third set of events; and responsive to a failure obtained in the generating constraints, transmitting a notification to the constraint library to generate constraints for the second test case using machine learning techniques. |