Reference : Leveraging Execution Logs to Support Model Inference and Software Testing |
Dissertations and theses : Doctoral thesis | |||
Engineering, computing & technology : Computer science | |||
Security, Reliability and Trust | |||
http://hdl.handle.net/10993/48513 | |||
Leveraging Execution Logs to Support Model Inference and Software Testing | |
English | |
Messaoudi, Salma ![]() | |
29-Jun-2021 | |
University of Luxembourg, Luxembourg | |
Docteur en Informatique | |
Briand, Lionel ![]() | |
Shin, Donghwan ![]() | |
Pastore, Fabrizio ![]() | |
Bianculli, Domenico ![]() | |
Mariani, Leonardo ![]() | |
Panichella, Annibale ![]() | |
[en] Software testing ; System logs ; Regression testing ; Program slicing ; Model inference ; Search-based software engineering | |
[en] Many software engineering activities process the events contained in log files. However, before performing any processing activity, it is necessary to correctly parse the entries in a log file to retrieve the actual events recorded in the log.
In the case of cyber-physical systems, execution logs are highly important because such systems integrate multiple third-party components where their source code is not always available. This limits the visibility of the system behavior to what is collected in the execution logs. The increasing amount of logs produced by cyber-physical systems calls for 1) more advanced techniques for accurate log parsing, 2) scalable model inference that will enabling efficient program comprehension and, 3) cost-effective software testing to ensuring the quality of complex soft- ware systems. | |
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab) | |
Researchers ; Professionals ; Students | |
http://hdl.handle.net/10993/48513 |
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