Abstract
Automotive electronic components are tested via hardware-in-the-loop (HiL) testing at the unit and integration test stages, according to ISO 26262. It is difficult to obtain debugging information from the HiL test because the simulator runs a black-box test automatically, depending on the scenario in the test script. At this time, debugging information can be obtained in HiL tests, using memory-updated information, without the source code or the debugging tool. However, this method does not know when the fault occurred, and it is difficult to select the starting point of debugging if the execution flow of the software is not known. In this paper, we propose a fault-localization method using a pattern in which each memory address is updated in the HiL test. Via a sequential pattern-mining algorithm in the memory-updated information of the transferred unit tests, memory-updated patterns are extracted, and the system learns using a convolutional neural network. Applying the learned pattern in the memory-updated information of the integration test can determine the fault point from the normal pattern. The point of departure from the normal pattern is highlighted as a fault-occurrence time, and updated addresses are presented as fault candidates. We applied the proposed method to an HiL test of an OSEK/VDX-based electronic control unit. Through fault-injection testing, we could find the cause of faults by checking the average memory address of 3.28%, and we could present the point of fault occurrence with an average accuracy of 80%.
Highlights
In recent years, electronic control units (ECUs) and software have been developed in a distributed manner because functions, such as driving assistants and passenger convenience functions, have diversified [1]
We have developed a fault-localization method that uses the difference in memory-updated information between unit tests and integration tests [14]
We introduce the necessary preparations for fault localization using the features and patterns that update each address in memory for software execution
Summary
Electronic control units (ECUs) and software have been developed in a distributed manner because functions, such as driving assistants and passenger convenience functions, have diversified [1]. The execution history of the software can be checked by observing the memory periodically, and the cause of the fault can be found For this reason, we have developed a fault-localization method that uses the difference in memory-updated information between unit tests and integration tests [14]. We propose a fault-localization method that uses updated patterns of memory in integrated testing. In the integration test, the updated feature is classified in the memory data of each frame, and the fault-occurrence timing is found by pattern matching with the updated pattern of the normal operation. 1. Example fault localization ofmemory-updated using memory-updated patterns in an integration a result, the proposed method the occurrence point the cause of fault the fault in the.
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