  We present stack graphs, an extension of Visser et al.'s scope graphs
framework. Stack graphs power Precise Code Navigation at GitHub, allowing users
to navigate name binding references both within and across repositories. Like
scope graphs, stack graphs encode the name binding information about a program
in a graph structure, in which paths represent valid name bindings. Resolving a
reference to its definition is then implemented with a simple path-finding
search.
  GitHub hosts millions of repositories, containing petabytes of total code,
implemented in hundreds of different programming languages, and receiving
thousands of pushes per minute. To support this scale, we ensure that the graph
construction and path-finding judgments are file-incremental: for each source
file, we create an isolated subgraph without any knowledge of, or visibility
into, any other file in the program. This lets us eliminate the storage and
compute costs of reanalyzing file versions that we have already seen. Since
most commits change a small fraction of the files in a repository, this greatly
amortizes the operational costs of indexing large, frequently changed
repositories over time. To handle type-directed name lookups (which require
"pausing" the current lookup to resolve another name), our name resolution
algorithm maintains a stack of the currently paused (but still pending)
lookups. Stack graphs can be constructed via a purely syntactic analysis of the
program's source code, using a new declarative graph construction language.
This means that we can extract name binding information for every repository
without any per-package configuration, and without having to invoke an
arbitrary, untrusted, package-specific build process.
