Model-based Fault Classification for Automotive Software
Intensive testing using model-based approaches is the standard way of demonstrating the correctness of automotive software. Unfortunately, state-of-the-art techniques leave a crucial and labor intensive task to the test engineer: identifying bugs in failing tests. Our contribution is a model-based classification algorithm for failing tests that assists the engineer when identifying bugs. It consists of three steps. (i) Fault localization replays the test on the model to identify the moment when the two diverge. (ii) Fault explanation then computes the reason for the divergence. The reason is a subset of messages from the test that is sufficient for divergence. (iii) Fault classification groups together tests that fail for similar reasons. Our approach relies on machinery from formal methods: (i) symbolic execution, (ii) Hoare logic and a new relationship between the intermediary assertions constructed for a test, and (iii) a new relationship among Hoare proofs. A crucial aspect in automotive software are timing requirements, for which we develop appropriate Hoare logic theory. We also briefly report on our prototype implementation for the CAN bus Unified Diagnostic Services in an industrial project.
Mon 5 DecDisplayed time zone: Auckland, Wellington change
13:30 - 15:00 | Testing and VerificationAPLAS at Seminar Room G007 Chair(s): Jonathan Aldrich Carnegie Mellon University | ||
13:30 30mTalk | RHLE: Modular Deductive Verification of Relational ∀∃ Properties APLAS Robert Dickerson Purdue University, Qianchuan Ye Purdue University, Michael K. Zhang Purdue University, Benjamin Delaware Purdue University | ||
14:00 30mTalk | Automated Temporal Verification for Algebraic Effects APLAS Yahui Song National University of Singapore, Darius Foo National University of Singapore, Wei-Ngan Chin National University of Singapore | ||
14:30 30mTalk | Model-based Fault Classification for Automotive Software APLAS Mike Becker TU Braunschweig, Roland Meyer TU Braunschweig, Tobias Runge TU Braunschweig, Ina Schaefer KIT, Sören van der Wall PhD Student, Sebastian Wolff New York University |