RestPi: Path-Sensitive Type Inference for REST APIs

JEFFREY S. FOSTER, Tufts University, USA REST APIs form the backbone of modern interconnected systems by providing a language-agnostic communication interface. REST API specifications should clearly describe all response types, but automatically generating specifications is difficult with existing tools.

We present REST 𝜋 , a type inference engine capable of automatically generating REST API specifications. The novel contribution of REST 𝜋 is our use of path-sensitive type inference, which encodes symbolic pathconstraints directly into a type system. This allows REST 𝜋 to enumerate all response types by considering each distinct execution path through an endpoint implementation. We implement path-sensitive type inference for Ruby, a popular language used for REST API servers. We evaluate REST 𝜋 by using it to infer types for 132 endpoints across 5 open-source REST API implementations without utilizing existing specifications or test suites. We find REST 𝜋 performs type inference efficiently and produces types that are more precise and complete than those obtained via an HTTP proxy. Our results suggest that path-sensitivity is a key technique to enumerate distinct response types for REST endpoints.

CCS Concepts: • Software and its engineering → Data types and structures; Documentation.