Feedback-Directed Random Test Generation
Massachusetts Institute of Technology · Microsoft Research (United Kingdom) · +1 more institution
Abstract
We present a technique that improves random test generation by incorporating feedback obtained from executing test inputs as they are created. Our technique builds inputs incrementally by randomly selecting a method call to apply and finding arguments from among previously-constructed inputs. As soon as an input is built, it is executed and checked against a set of contracts and filters. The result of the execution determines whether the input is redundant, illegal, contract-violating, or useful for generating more inputs. The technique outputs a test suite consisting of unit tests for the classes under test. Passing tests can be used to ensure that code contracts are preserved across program changes; failing…
Citation impact
- FWCI
- 49.27
- Percentile
- 100%
- References
- 46
Authors
4Topics & keywords
- Computer science
- Random testing
- Test suite
- Predicate abstraction
- Algorithm
- Unit testing
- Code (set theory)
- Test (biology)
- Peace, Justice and strong institutions