Publication Data

   Loop Recognition in C++/Java/Go/Scala

Abstract: In this experience report we encode a well specified, compact benchmark in four programming languages, namely C++, Java, Go, and Scala. The implementations each use the languages’ idiomatic container classes, looping constructs, and memory/object allocation schemes. It does not attempt to exploit specific language and runtime features to achieve maximum performance. This approach allows an almost fair comparison of language features, code complexity, compilers and compile time, binary sizes, runtimes, and memory footprint. While the benchmark itself is simple and compact, it employs many language features, in particular, higher-level data structures (lists, maps, lists and arrays of sets and lists), a few algorithms (union/find, dfs / deep recursion, and loop recognition based on Tarjan), iterations over collection types, some object oriented features, and interesting memory allocation patterns. We do not explore any aspects of multi-threading, or higher level type mechanisms, which vary greatly between the languages. The benchmark points to very large differences in all examined dimensions of the language implementations. After publication of the benchmark internally at Google, several engineers produced highly optimized versions of the benchmark. While this whole effort is an anectodal comparison only, the benchmark and subsequent tuning effort might be indicatie of typical performance pain points in the respective languages.