Adequate testing is necessary and important to ensure reliability of software. Most test models are specification-based and fail to capture implicit domain specific properties. This paper presents a technique, which uses a HaskellDB specification of the software to extract domain specific properties and embed them into the test generation model. HaskellDB is an embedded domain specific functional and strongly typed language for database related applications. Specifying using HaskellDB ensures that a set of axioms based on type safeness of the database queries hold for the specification. The implementation of the application should also satisfy these properties and should be tested accordingly. We therefore propose a technique that extracts the axioms automatically from the HaskellDB specification and embeds additional test paths in the test model leading to an enriched test suite. We present an example application of the technique and compare the results against a manual testing technique.

When an Automated Testing Equipment (ATE) company designs a new system, the issue of backward compatibility is always a major concern, both for the company and its customers. If backward compatibility is maintained, the ATE application engineers face the difficult task of trying to support new features on an aging system. The alternative is to face the problem of converting old test programs to the new environment. Translation of legacy code involves an automatic translation tool, and some application effort applied to those problems the translatorcouldn't resolve. To minimize the amount of work required from the application engineers, the tool need to be semantically-aware; that is, the tool must contain domain-specific knowledge and use that knowledge when translating. The more knowledge a tool has at its disposal, the less code an application engineer is forced to translate by hand.Until recently, it has been difficult to perform automatic translation satisfactorily because it was not cost effective to write a translator that possessed such semantic understanding of the test programs. By making good use of Functional Programming techniques and tools, we were able to construct a cost-effective, semantically-aware translation tool in a fraction of the time needed by traditional methods. Based upon its performance during testing, we believe the toolto correctly translate the majority of test programs, thereby greatly easing the applications engineers' burden.

Asynchronous exceptions, such as timeouts are important for robust, modular programs, but are extremely difficult to program with — so much so that most programming languages either heavily restrict them or ban them altogether. We extend our earlier work, in which we added synchronous exceptions to Haskell, to support asynchronous exceptions too. Our design introduces scoped combinators for blocking and unblocking asynchronous interrupts, along with a somewhat surprising semantics for operations that can suspend. Uniquely, we also give a formal semantics for our system.

The standard implementation technique for lazy functional languages is call-by-need, which ensures that an argument to a function in any given call is evaluated at most once. A significant problem with call-by-need is that it is difficult -- even for compiler writers -- to predict the effects of program transformations. The traditional theories for lazy functional languages are based on call-by-name models, and offer no help in determining which transformations do indeed optimize a program.In this article we present an operational theory for call-by-need, based upon an improvement ordering on programs: M is improved by N if in all program-contexts C, when C[M] terminates then C[N] terminates at least as cheaply.We show that this improvement relation satisfies a "context lemma", and supports a rich inequational theory, subsuming the call-by-need lambda calculi of Ariola et al. [AFM+95]. The reduction-based call-by-need calculi are inadequate as a theory of lazy-program transformation since they only permit transformations which speed up programs by at most a constant factor (a claim we substantiate); we go beyond the various reduction-based calculi for call-by-need by providing powerful proof rules for recursion, including syntactic continuity -- the basis of fixed-point-induction style reasoning, and an improvement theorem, suitable for arguing the correctness and safety of recursion-based program transformations.