Although the study of static and dynamic type systems plays a major role in research, relatively little is known about the impact of type systems on software development. Perhaps one of the more common arguments for static type systems in languages such as Java or C++ is that they require developers to annotate their code with type names, which is thus claimed to improve the documentation of software. In contrast, one common argument against static type systems is that they decrease flexibility, which may make them harder to use. While these arguments are found in the literature, rigorous empirical evidence is lacking. We report on a controlled experiment where 27 subjects performed programming tasks on an undocumented API with a static type system (requiring type annotations) as well as a dynamic type system (which does not). Our results show that for some tasks, programmers had faster completion times using a static type system, while for others, the opposite held. We conduct an exploratory study to try and theorize why.

Research in the area of programming languages has different facets -- from formal reasoning about new programming language constructs (such as type soundness proofs for new type systems) over inventions of new abstractions, up to performance measurements of virtual machines. A closer look into the underlying research methods reveals a distressing characteristic of programming language research: developers, which are the main audience for new language constructs, are hardly considered in the research process. As a consequence, it is simply not possible to state whether a new construct that requires some kind of interaction with the developer has any positive impact on the construction of software. This paper argues for appropriate research methods in programming language research that rely on studies of developers -- and argues that the introduction of corresponding empirical methods not only requires a new understanding of research but also a different view on how to teach software science to students.

Recent empirical studies that compared static and dynamic type systems on API usability showed a positive impact of static type systems on developer productivity in most cases. Nevertheless, it is unclear how large this effect is in comparison to other factors. One obvious factor in programming is tooling: It is commonly accepted that modern IDEs have a large positive impact on developers, although it is not clear which parts of modern IDEs are responsible for that. One possible---and for most developers obvious candidate---is code completion. This paper describes a 2x2 randomized trial that compares JavaScript and Microsoft's statically typed alternative TypeScript with and without code completion in MS Visual Studio. While the experiment shows (in correspondence to previous experiments) a large positive effect of the statically typed language TypeScript, the code completion effect is not only marginal, but also just approaching statistical significance. This seems to be an indicator that the effect of static type systems is larger than often assumed, at least in comparison to code completion.

Type systems that permit developers to express themselves more precisely are one of the primary topics in programming language research, as well as in industrial software development. While it seems plausible that an expressive static type system increases developer productivity, there is little empirical evidence for or against this hypothesis. Generic types in Java are an example: as an extension of Java's original type system, some claim that Java 1.5 improves the type system's "expressiveness." Even if this claim is true, there exists little empirical evidence that claimed expressiveness leads to a measurable increase in developer productivity. This paper introduces an experiment where generic types (in comparison to raw types) have been evaluated in three different directions: (1) the documentation impact on undocumented APIs, (2) the time required for fixing type errors, and (3) the extensibility of a generic type hierarchy. The results of the experiment suggest that generic types improve documentation and reduce extensibility -- without revealing a difference in the time required for fixing type errors.

Although static type systems are an essential part in teaching and research in software engineering and computer science, there is hardly any knowledge about what the impact of static type systems on the development time or the resulting quality for a piece of software is. On the one hand there are authors that state that static type systems decrease an application's complexity and hence its development time (which means that the quality must be improved since developers have more time left in their projects). On the other hand there are authors that argue that static type systems increase development time (and hence decrease the code quality) since they restrict developers to express themselves in a desired way. This paper presents an empirical study with 49 subjects that studies the impact of a static type system for the development of a parser over 27 hours working time. In the experiments the existence of the static type system has neither a positive nor a negative impact on an application's development time (under the conditions of the experiment).