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Coverage analysis is widely used but can suffer from high overhead.
Residual test coverage monitoring. In Proceedings of the 21st international conference on Software engineering . 277–284
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An API for Runtime Code Patching
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Efficient online computation of statement coverage
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Demand-driven structural testing with dynamic instrumentation. In Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005. 156–165
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Leveraging disposable instrumentation to reduce coverage collection overhead
Kalyan-Ram Chilakamarri and Sebastian G. Elbaum. 2006 · 2006
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Is bytecode instrumentation as good as source code instrumentation: An empirical study with industrial tools (Experience Report). In IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013, Pasadena, CA, USA, November 4-7, 2013 . IEEE Computer Society, 380–389
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The Java Virtual Machine Specification
Tim Lindholm, Frank Yellin, Gilad Bracha, and Alex Buckley. 2013 · 2013
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Code coverage at Google. In Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2019, Tallinn, Estonia, August 26-30, 2019 , Marlon Dumas, Dietmar Pfahl, Sven Apel, and Alessandra Russo (Eds.). ACM, 955–963
Marko Ivanković, Goran Petrović, René Just, and Gordon Fraser. 2019 · 2019
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Full-Speed Fuzzing: Reducing Fuzzing Overhead through Coverage-Guided Tracing. In 2019 IEEE Symposium on Security and Privacy, SP 2019, San Francisco, CA, USA, May 19-23, 2019 . IEEE, 787–802
Stefan Nagy and Matthew Hicks. 2019 · 2019
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PEP659: Specializing Adaptive Interpreter
Mark Shannon. 2021 · 2021
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Investigating Managed Language Runtime Performance: Why JavaScript and Python are 8x and 29x slower than C++, yet Java and Go can be Faster?. In 2022 USENIX Annual Technical Conference, USENIX ATC 2022, Carlsbad, CA, USA, July 11-13, 2022 , Jiri Schindler and Noa Zilberman (Eds.). USENIX Association, 835–852
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