Efficient module-level dynamic analysis for dynamic languages with module recontextualizationEfficient module-level dynamic analysis for dynamic languages with module recontextualization Δημοσίευση σε Συνέδριο Conference Publication 2023-06-232021enDynamic program analysis is a long-standing technique for obtaining information about program execution. We present module recontextualization, a new dynamic analysis approach that targets modern dynamic languages such as JavaScript and Racket, enabled by the fact that they feature a module-import mechanism that loads code at runtime as a string. This approach uses lightweight load-time code transformations that operate on the string representation of the module, as well as the context to which it is about to be bound, to insert developer-provided, analysis-specific code into the module before it is loaded. This code implements the dynamic analysis, enabling this approach to capture all interactions around the module in unmodified production language runtime environments. We implement this approach in two systems targeting the JavaScript and Racket ecosystems. Our evaluation shows that this approach can deliver order-of-magnitude performance improvements over state-of-the-art dynamic analysis systems while supporting a range of analyses, implemented on average in about 100 lines of code.http://creativecommons.org/licenses/by/4.0/1202–121329th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software EngineeringProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software EngineeringVasilakis_et_al_ESEC.FSE_2021.pdfChania [Greece]Library of TUC2023-06-23application/pdf436.1 kBfree Vasilakis Nikos Ntousakis Grigorios Ντουσακης Γρηγοριος Heller Veit Rinard Martin C. Association for Computing Machinery (ACM) Runtime Performance Recontextualization Dynamic Analysis Security Instrumentation