The language Esterel has found success in many safety-critical applications, such as fly-by-wire systems and nuclear power plant control software. Its imperative style is natural to programmers building such systems and its precise semantics makes it work well for reasoning about programs. Existing semantics of Esterel generally fall into two categories: translation to Boolean circuits, or operational semantics that give a procedure for running a whole program. In contrast, equational theories enable reasoning about program behavior via equational rewrites at the source level. Such theories form the basis for proofs of transformations inside compilers or for program refactorings, and defining program evaluation syntactically. This paper presents the first such equational calculus for Esterel. It also illustrates the calculus’s usefulness with a series of example equivalences and discuss how it enabled us to find bugs in Esterel implementations.

A medical prescription is a set of health care instructions that govern the plan of care for an individual patient, which may include orders for drug therapy, diet, clinical assessment, and laboratory testing. Clinicians have long used algorithmic thinking to describe and implement prescriptions but without the benefit of a formal programming language. Instead, medical algorithms are expressed using a natural language patois, flowcharts, or as structured data in an electronic medical record system. The lack of a prescription programming language inhibits expressiveness; results in prescriptions that are difficult to understand, hard to debug, and awkward to reuse; and increases the risk of fatal medical error. This article reports on the design and evaluation of Patient-Oriented Prescription Programming Language (POP-PL), a domain-specific programming language designed for expressing prescriptions. The language is based around the idea that programs and humans have complementary strengths that, when combined properly, can make for safer, more accurate performance of prescriptions. Use of POP-PL facilitates automation of certain low-level vigilance tasks, freeing up human cognition for abstract thinking, compassion, and human communication. We implemented this language and evaluated its design attempting to write prescriptions in the new language and evaluated its usability by assessing whether clinicians can understand and modify prescriptions written in the language. We found that some medical prescriptions can be expressed in a formal domain-specific programming language, and we determined that medical professionals can understand and correctly modify programs written in POP-PL. We also discuss opportunities for refining and further developing POP-PL.

Domain-specific languages are the ultimate abstraction, dixit Paul Hudak. But what abstraction should we use to build such ultimate abstractions? What is sauce for the goose is sauce for the gander: a language, of course! Racket is the ultimate abstraction-abstraction, a platform for quickly and easily building new ultimate abstractions. This pearl demonstrates Racket's power by taking a leisurely walk through the implementation of a DSL for Lindenmayer systems, the computational model par excellence of theoretical botany.

Medical professionals have long used algorithmic thinking to describe and implement health care processes without the benefit of the conceptual framework provided by a programming language. Instead, medical algorithms are expressed using English, flowcharts, or data tables. This results in prescriptions that are difficult to understand, hard to debug, and awkward to reuse. This paper reports on the design and evaluation of a domain-specific programming language, POP-PL for expressing medical algorithms. The design draws on the experience of researchers in two disciplines, programming languages and medicine. The language is based around the idea that programs and humans have complementary strengths, that when combined can make for safer, more accurate performance of prescriptions. We implemented a prototype of our language and evaluated its design by writing prescriptions in the new language and administering a usability survey to medical professionals. This formative evaluation suggests that medical prescriptions can be conveyed by a programming language's mode of expression and provides useful information for refining the language. Analysis of the survey results suggests that medical professionals can understand and correctly modify programs in POP-PL.