SMT-based checking of refinement types for call-by-value languages is a well-studied subject. Unfortunately, the classical translation of refinement types to verification conditions is unsound under lazy evaluation. When checking an expression, such systems implicitly assume that all the free variables in the expression are bound to values. This property is trivially guaranteed by eager, but does not hold under lazy, evaluation. Thus, to be sound and precise, a refinement type system for Haskell and the corresponding verification conditions must take into account which subset of binders actually reduces to values. We present a stratified type system that labels binders as potentially diverging or not, and that (circularly) uses refinement types to verify the labeling. We have implemented our system in LIQUIDHASKELL and present an experimental evaluation of our approach on more than 10,000 lines of widely used Haskell libraries. We show that LIQUIDHASKELL is able to prove 96% of all recursive functions terminating, while requiring a modest 1.7 lines of termination-annotations per 100 lines of code.

SMT-based checking of refinement types for call-by-value languages is a well-studied subject. Unfortunately, the classical translation of refinement types to verification conditions is unsound under lazy evaluation. When checking an expression, such systems implicitly assume that all the free variables in the expression are bound to values. This property is trivially guaranteed by eager, but does not hold under lazy, evaluation. Thus, to be sound and precise, a refinement type system for Haskell and the corresponding verification conditions must take into account which subset of binders actually reduces to values. We present a stratified type system that labels binders as potentially diverging or not, and that (circularly) uses refinement types to verify the labeling. We have implemented our system in LIQUIDHASKELL and present an experimental evaluation of our approach on more than 10,000 lines of widely used Haskell libraries. We show that LIQUIDHASKELL is able to prove 96% of all recursive functions terminating, while requiring a modest 1.7 lines of termination-annotations per 100 lines of code.

Localizing type errors is challenging in languages with global type inference, as the type checker must make assumptions about what the programmer intended to do. We introduce Nate, a data-driven approach to error localization based on supervised learning. Nate analyzes a large corpus of training data -pairs of ill-typed programs and their "fixed" versions -to automatically learn a model of where the error is most likely to be found. Given a new ill-typed program, Nate executes the model to generate a list of potential blame assignments ranked by likelihood. We evaluate Nate by comparing its precision to the state of the art on a set of over 5,000 ill-typed OCaml programs drawn from two instances of an introductory programming course. We show that when the top-ranked blame assignment is considered, Nate's data-driven model is able to correctly predict the exact sub-expression that should be changed 72% of the time, 28 points higher than OCaml and 16 points higher than the state-of-the-art SHErrLoc tool. Furthermore, Nate's accuracy surpasses 85% when we consider the top two locations and reaches 91% if we consider the top three.

We present a new technique called type targeted testing, which translates precise refinement types into comprehensive test-suites. The key insight behind our approach is that through the lens of SMT solvers, refinement types can also be viewed as a high-level, declarative, test generation technique, wherein types are converted to SMT queries whose models can be decoded into concrete program inputs. Our approach enables the systematic and exhaustive testing of implementations from high-level declarative specifications, and furthermore, provides a gradual path from testing to full verification. We have implemented our approach as a Haskell testing tool called TARGET, and present an evaluation that shows how TARGET can be used to test a wide variety of properties and how it compares against state-of-the-art testing approaches

Component frameworks are complex systems that rely on many layers of abstraction to function properly. One essential requirement is a consistent means of describing each individual component and how it relates to both other components and the whole framework. As component frameworks are designed to be flexible by nature, the description method should be simultaneously powerful, lead to efficient code, and be easy to use, so that new users can quickly adapt their own code to work with the framework.In this paper, we discuss the Cactus Configuration Language (CCL) which is used to describe components ("thorns") in the Cactus Framework. The CCL provides a description language for the variables, parameters, functions, scheduling and compilation of a component and includes concepts such as interface and implementation which allow thorns providing the same capabilities to be easily interchanged. We include several application examples which illustrate how community toolkits use the CCL and Cactus and identify needed additions to the language.