Profile-Guided Static Typing for Dynamic Scripting Languages
Michael Furr, Jong-hoon (David) An, and Jeffrey S. Foster
University of Maryland, Computer Science Department Technical Report CS-TR-4935 April 2009
[ Abstract | pdf ]
Many popular scripting languages such as Ruby, Python, and Perl include highly dynamic language constructs, such as an eval method that evaluates a string as program text. While these constructs allow terse and expressive code, they have traditionally obstructed static analysis. In this paper we present PRuby, an extension to Diamondback Ruby (DRuby), a static type inference system for Ruby. PRuby augments DRuby with a novel dynamic analysis and transformation that allows us to precisely type uses of highly dynamic constructs. PRuby’s analysis proceeds in three steps. First, we use run-time instrumentation to gather per-application profiles of dynamic feature usage. Next, we replace dynamic features with statically analyzable alternatives based on the profile. We also add instrumentation to safely handle cases when subsequent runs do not match the profile. Finally, we run DRuby’s static type inference on the transformed code to enforce type safety. We used PRuby to gather profiles for a benchmark suite of sample Ruby programs. We found that dynamic features are pervasive throughout the benchmarks and the libraries they include, but that most uses of these features are highly constrained and hence can be effectively profiled. Using the profiles to guide type inference, we found that DRuby can generally statically type our benchmarks modulo some refactoring, and we discovered several previously unknown type errors. These results suggest that profiling and transformation is a lightweight but highly effective approach to bring static typing to highly dynamic languages.

Checking Type Safety of Foreign Function Calls
Michael Furr, and Jeffrey S. Foster
University of Maryland, Computer Science Department Technical Report CS-TR-4845 December 2006
[ Abstract | pdf ]
Foreign function interfaces (FFIs) allow components in different languages to communicate directly with each other. While FFIs are useful, they often require writing tricky, low-level code and include little or no static safety checking, thus providing a rich source of hard-to-find programming errors. In this paper, we study the problem of enforcing type safety across the OCaml-to-C FFI and the Java Native Interface (JNI). We present O-Saffire and J-Saffire, a pair of multilingual type inference systems that ensure C code that uses these FFIs accesses high-level data safely. Our inference systems use representational types to model C’s low-level view of OCaml and Java values, and singleton types to track integers, strings, memory offsets, and type tags through C. J-Saffire, our Java system, uses a polymorphic, flow-insensitive, unification-based analysis. Polymoprhism is important because it allows us to precisely model user-defined wrapper functions and the more than 200 JNI functions. O-Saffire, our OCaml system, uses a monomorphic, flow-sensitive analysis, because while polymorphism is much less important for the OCaml FFI, flow-sensitivity is critical to track conditional branches, which are used when ``pattern matching’’ OCaml data in C. O-Saffire also tracks garbage collection information to ensure that local C pointers to the OCaml heap are registered properly, which is not necessary for the JNI. We have applied O-Saffire and J-Saffire to a set of benchmarks and found many bugs and questionable coding practices. These results suggest that static checking of FFIs can be a valuable tool in writing correct multilingual software.

Polymorphic Type Inference for the JNI
Michael Furr, and Jeffrey S. Foster
University of Maryland, Computer Science Department Technical Report CS-TR-4759 November 2005
[ Abstract | pdf ]
We present a multi-lingual type inference system for checking type safety of programs that use the Java Native Interface (JNI). The JNI uses specially-formatted strings to represent class and field names as well as method signatures, and so our type system tracks the flow of string constants through the program. Our system embeds string variables in types, and as those variables are resolved to string constants during inference they are replaced with the structured types the constants represent. This restricted form of dependent types allows us to directly assign type signatures to each of the more than 200 functions in the JNI. Moreover, it allows us to infer types for user-defined functions that are parameterized by Java type strings, which we have found to be common practice. Our inference system allows such functions to be treated polymorphically by using instantiation constraints, solved with semi-unification, at function calls. Finally, we have implemented our system and applied it to a small set of benchmarks. Although semi-unification is undecidable, we found our system to be scalable and effective in practice. We discovered 155 errors 36 cases of suspicious programming practices in our benchmarks.

Checking Type Safety of Foreign Function Calls
Michael Furr, and Jeffrey S. Foster
University of Maryland, Computer Science Department Technical Report CS-TR-4627 November 2004
[ Abstract | pdf ]
We present a multi-lingual type inference system for checking type safety across a foreign function interface. The goal of our system is to prevent foreign function calls from introducing type and memory safety violations into an otherwise safe language. Our system targets OCaml’s FFI to C, which is relatively lightweight and illustrates some interesting challenges in multi-lingual type inference. The type language in our system embeds OCaml types in C types and vice-versa, which allows us to track type information accurately even through the foreign language, where the original types are lost. Our system uses a representational type that can model multiple OCaml types, because C programs can observe that many OCaml types have the same physical representation. Furthermore, because C has a low-level view of OCaml data, our inference system includes a dataflow analysis to track memory offsets and tag information. Finally, our type system includes garbage collection information to ensure that pointers from the FFI to the OCaml heap are tracked properly. We have implemented our inference system and applied it to a small set of benchmarks. Our results show that programmers do misuse these interfaces, and our implementation has found several bugs and questionable coding practices in our benchmarks.