Practical SMT-based type error localization

Abstract

Compilers for statically typed functional programming languages are notorious for generating confusing type error messages. When the compiler detects a type error, it typically reports the program location where the type checking failed as the source of the error. Since other error sources are not even considered, the actual root cause is often missed. A more adequate approach is to consider all possible error sources and report the most useful one subject to some usefulness criterion. In our previous work, we showed that this approach can be formulated as an optimization problem related to satisfiability modulo theories (SMT). This formulation cleanly separates the heuristic nature of usefulness criteria from the underlying search problem. Unfortunately, algorithms that search for an optimal error source cannot directly use principal types which are crucial for dealing with the exponential-time complexity of the decision problem of polymorphic type checking. In this paper, we present a new algorithm that efficiently finds an optimal error source in a given ill-typed program. Our algorithm uses an improved SMT encoding to cope with the high complexity of polymorphic typing by iteratively expanding the typing constraints from which principal types are derived. The algorithm preserves the clean separation between the heuristics and the actual search. We have implemented our algorithm for OCaml. In our experimental evaluation, we found that the algorithm reduces the running times for optimal type error localization from minutes to seconds and scales better than previous localization algorithms.

Automatic diagnosis and correction of logical errors for functional programming assignments

“…Debugging functional programs. For functional languages, prior works have focused on localizing and fixing type errors [Chen and Erwig 2014;Lerner et al 2007;Pavlinovic et al 2014Pavlinovic et al , 2015Seidel et al 2017;Zhang et al 2017]. For example, Seidel et al [2017] recently proposed a data-driven approach to localize type errors in OCaml programs.…”

“…; studied how type errors are fixed and presented Learnskell for producing user-friendly feedback on type errors. Pavlinovic et al [2014Pavlinovic et al [ , 2015 presented SMT-based techniques for localizing type errors. Chen and Erwig [2014] presented a method for fixing type errors by generating possible changes and checking the them using type checker.…”

“…However, assisting students to resolve those errors is challenging. In particular, providing personalized feedback on logical errors was most difficult as it requires instructors to manually figure out the cause of the errors, unlike syntax or type errors for which a wealth of tool support already exists [Chen and Erwig 2014;Lerner et al 2007;Pavlinovic et al 2014Pavlinovic et al , 2015Seidel et al 2017;Zhang et al 2017].…”