|PI: Sun Jun||Funding Source: MOE|
|Co PI: -||Start Date: 10 January, 2013|
|Research Areas: Software Engineering||End Date: 30 September, 2016|
In this work, we propose to develop a scalable method and software toolkit, which is not only capable of finding bugs efficiently but also provide formal guarantee or conditional guarantee for bug freeness. That is, the proposed toolkit aims to combine the strength of testing and verification while avoiding their problems. The toolkit is composed of three main components, a tester which is built based on state-of-art testing techniques; a verifier which adopts advanced verification techniques; and a learner which uses learning techniques from machine learning community to connect the world of testing and verification.