What we eval in the shadows: a large-scale study of eval in R programs

Most dynamic languages allow users to turn text into code using various functions, often named <tt>eval</tt>, with language-dependent semantics. The widespread use of these reflective functions hinders static analysis and prevents compilers from performing optimizations. This paper aims provide a better sense why programmers <tt>eval</tt>. Understanding <tt>eval</tt> is used in practice key finding ways mitigate its negative impact. We have reasons believe that feature usage language application domain-specific; we focus on data science written R compare our results previous work analyzed web programming JavaScript. analyze 49,296,059 calls 240,327 scripts extracted 15,401 packages. find indeed use; R’s more pervasive arguably dangerous than what was previously reported for