Conditional compilation and software product line technologies make it possible to generate a huge number of different programs from a single software project. Typing each of these programs individually is usually impossible due to the sheer number of possible variants. Our previous work has addressed this problem with a type system for variational lambda calculus (VLC), an extension of lambda calculus with basic constructs for introducing and organizing variation. Although our type inference algorithm is more efficient than the brute-force strategy of inferring the types of each variant individually, it is less robust since type inference will fail for the entire variational expression if any one variant contains a type error. In this work, we extend our type system to operate on VLC expressions containing type errors. This extension directly supports locating ill-typed variants and the incremental development of variational programs. It also has many subtle implications for the unification of variational types. We show that our extended type system possesses a principal typing property and that the underlying unification problem is unitary. Our unification algorithm computes partial unifiers that lead to result types that (1) contain errors in as few variants as possible and (2) are most general. Finally, we perform an empirical evaluation to determine the overhead of this extension compared to our previous work, to demonstrate the improvements over the brute-force approach, and to explore the effects of various error distributions on the inference process.

Previous research on static analysis for program families has focused on lifting analyses for single, plain programs to program families by employing idiosyncratic representations. The lifting effort typically involves a significant amount of work for proving the correctness of the lifted algorithm and demonstrating its scalability. In this paper, we propose a parameterized static analysis framework for program families that can automatically lift a class of type-based static analyses for plain programs to program families. The framework consists of a parametric logical specification and a parametric variational constraint solver. We prove that a lifted algorithm is correct provided that the underlying analysis algorithm is correct. An evaluation of our framework has revealed an error in a previous manually lifted analysis. Moreover, performance tests indicate that the overhead incurred by the general framework is bounded by a factor of 2.