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Exploiting Synergy Between Testing and Inferred Partial Specifications Tao Xie David Notkin Department of Computer Science & Engineering University of Washington May 9, 2003 Workshop on Dynamic Analysis (WODA 2003) Outline

  1. Exploiting Synergy Between Testing and Inferred Partial Specifications Tao Xie David Notkin Department of Computer Science & Engineering University of Washington May 9, 2003 Workshop on Dynamic Analysis (WODA 2003)

  2. Outline � Background � Synergy issues � Application � Why it will fail � Why it will succeed

  3. Background Specification-based testing (likely) Tests Specs Dynamic likely spec inference � Test case generation, e.g. Korat [BKM 02], Jtest [ParaSoft] , AsmL [MSR] � Test oracle generation, e.g. Korat, Jtest, JML+JUnit [CL 01] � Test selection/coverage criteria, e.g. ADLscope [CR 99], UMLTest [OA 99] � Likely spec Inference based on test executions, e.g. Daikon operational abstraction [ECGN 01], Strauss [ABL 02], Hastings [WML 02]

  4. Synergy Issue: Chicken-and-Egg I Spec-based test generation (likely) Tests Specs Dynamic likely spec inference � Win-win feedback loop: better spec �� better tests? � Chicken and egg problem?

  5. Synergy Issue: Chicken-and-Egg II Spec-based test generation (likely) Tests Specs Dynamic likely spec inference � I nitial tests T ( manually written tests, automatically generated tests w/o specs, etc.) � Likely specs S inferred from T � Tests T’ generated based on S � Executions of T’ � select a subset of T’ [ Test augmentation: T = T ∪ the subset of T’ ] Better tests Better tests Likely specs S inferred from T Better specs Better specs �

  6. Executions of Tests Generated From Likely Specifications -I Universal Universal Method Execution Legal Legal ☺ ☺ inputs outputs Stronger inferred pre Input domain Stronger inferred post Output domain Inferred precondition Inferred postcondition constrained domain constrained domain Postcondition violation ☺ (exercise a new feature) ☺ Postcondition violation (expose a fault)

  7. Executions of Tests Generated From Likely Specifications -II Method Execution ☺ ☺ Legal Legal ☺ ☺ inputs outputs Weaker inferred pre Input domain Stronger inferred post Output domain Inferred precondition Inferred postcondition constrained domain constrained domain Postcondition violation ☺ (exercise a new feature) ☺ Postcondition violation Postcondition violation ☺ (narrow down precondition) (expose a fault)

  8. Executions of Tests Generated From Likely Specifications -III Method Execution Legal Legal inputs outputs ☺ Stronger inferred pre Input domain Weaker inferred post Output domain Inferred precondition Inferred postcondition constrained domain constrained domain ☺ Postcondition violation (expose a fault)

  9. Executions of Tests Generated From Likely Specifications -IV Method Execution Legal Legal ☺ inputs outputs ☺ Weaker inferred pre Input domain Weaker inferred post Output domain Inferred precondition Inferred postcondition constrained domain constrained domain Postcondition violation ☺ ☺ Postcondition violation (narrow down precondition) (expose a fault)

  10. Handling Synergy Issues � Precondition guard removal � Too restrictive preconditions may leave (maybe important) legal unit inputs untested � Iterations until reaching a fixed point � Add new violating tests (legal inputs) to the existing test suite for spec inference in next cycle � Add stronger preconditions manually

  11. Application: Spec-Violation Approach to Unit Test Data Selection � Problem � Insufficiency of the manually maintained unit test suite A (small number) � Oracle unavailability of the automatically generated unit test suite B (large number) � Goal: Selectively augment A with a small (most valuable) subset of B � Related work: Operational Difference [HME 03], DIDUCE [HL 02]

  12. Why it will fail � Not enough inferred postconditions to violate � Improved inference techniques can help � Precondition guard removal might induce false positives � Precondition guard relaxation can help � Postcondition violations are due to limited test data value range uninteresting to testers � Manually commenting out violated specs is tedious � Improved Jtest to support it can help

  13. Why it will succeed � Without a priori specification, there are few effective black box unit test data selection approaches. � Violating tests can guarantee to exercise a new program feature � The violated specs for the corresponding violating tests can help developers to make selection decision easily. � The approach can be largely automated

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