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Methodological Principles for Reproducible Performance Evaluation in Cloud Computing

, , , , , , , , , и . Software Engineering 2020, Fachtagung des GI-Fachbereichs Softwaretechnik, 24.-28. Februar 2020, Innsbruck, Austria, том P-300 из LNI, стр. 93--94. Gesellschaft für Informatik e.V., (2020)

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Software Abstractions for Component Interaction in the Internet of Things, , , , и . Computer, 49 (12): 50--59 (декабря 2016)On the limits of modeling generational garbage collector performance., , , и . ICPE, стр. 15-26. ACM, (2014)Capturing performance assumptions using stochastic performance logic., , , , , и . ICPE, стр. 311-322. ACM, (2012)Methodological Principles for Reproducible Performance Evaluation in Cloud Computing - A SPEC Research Technical Report, , , , , , , , , и . SPEC-RG-2019-04. SPEC Research Group --- Cloud Working Group, Standard Performance Evaluation Corporation (SPEC), (апреля 2019)Investigating Cache Parameters of x86 Family Processors., и . SPEC Benchmark Workshop, том 5419 из Lecture Notes in Computer Science, стр. 77-96. Springer, (2009)Towards Systematic Synthesis of Reflective Middleware., , и . Reflection, том 1616 из Lecture Notes in Computer Science, стр. 144-146. Springer, (1999)Diagnosing Compiler Performance by Comparing Optimization Decisions (Poster Abstract)., , и . MPLR, стр. 179. ACM, (2023)Validating Model-Driven Performance Predictions on Random Software Systems., , и . QoSA, том 6093 из Lecture Notes in Computer Science, стр. 3-19. Springer, (2010)Generic Environment for Full Automation of Benchmarking., , и . SOQUA/TECOS, том P-58 из LNI, стр. 125-132. GI, (2004)Resource Sharing in Performance Models., , и . EPEW, том 4748 из Lecture Notes in Computer Science, стр. 245-259. Springer, (2007)