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JavaScript has become one of the most widely used programming languages forweb development, server-side programming, and even micro-controllers for IoT.However, its extremely functional and dynamic features degrade the performanceand precision of static analysis. Moreover, the variety of built-in functionsand host environments requires excessive manual modeling of their behaviors. Toalleviate these problems, researchers have proposed various ways to leveragedynamic analysis during JavaScript static analysis. However, they do not fullyutilize the high performance of dynamic analysis and often sacrifice thesoundness of static analysis.  In this paper, we present dynamic shortcuts, a new technique to flexiblyswitch between abstract and concrete execution during JavaScript staticanalysis in a sound way. It can significantly improve the analysis performanceand precision by using highly-optimized commercial JavaScript engines andlessen the modeling efforts for opaque code. We actualize the technique via$\text{SAFE}_\textsf{DS}$, an extended combination of $\text{SAFE}$ andJalangi, a static analyzer and a dynamic analyzer, respectively. We evaluated$\text{SAFE}_\textsf{DS}$ using 269 official tests of Lodash 4 library. Ourexperiment shows that $\text{SAFE}_\textsf{DS}$ is 7.81x faster than thebaseline static analyzer, and it improves the precision to reduce failedassertions by 12.31% on average for 22 opaque functions.

Accelerating JavaScript Static Analysis via Dynamic Shortcuts (Extended Version)