It is well-known, and often a topic of heated debates, that programs in some programming languages are more concise than in others. This is a relevant factor when comparing or aggregating volume-impacted metrics on source code written in a combination of programming languages. In this paper, we present a model for measuring the conciseness of programming languages in a consistent, objective and evidence-based way. We present the approach, explain how it is founded on information theoretical principles, present detailed analysis steps and show the quantitative results of applying this model to a large benchmark of diverse commercial software applications. We demonstrate that our metric for language conciseness is strongly correlated with both an alternative analytical approach, and with a large scale developer survey, and show how its results can be applied to improve software metrics for multi-language applications.

Historically, programming languages have been—benevolent—dictators: reducing all possible semantics to specific ones offered by a few built-in language constructs. Over the years, some programming languages have freed the programmers from the restrictions to use only built-in libraries, built-in data types, and builtin type-checking rules. Even though—arguably—such freedom could lead to anarchy, or people shooting themselves in the foot, the contrary tends to be the case: a language that does not allow for extensibility is depriving software engineers of the ability to construct proper abstractions and to structure software in the most optimal way. Therefore the software becomes less structured and maintainable than would be possible if the software engineer could express the behavior of the program with the most appropriate abstractions. The idea proposed by this paper is to move composition from built-in language constructs to programmable, first-class abstractions in a language. We discuss several prototypes of the Co-op language, which show that it is possible, with a relatively simple model, to express a wide range of compositions as first-class concepts.

In event-driven systems, separating the reactive part of software (i.e., event-driven control) from the non-reactive part is a common design practice. The reactive part is typically structured according to the states and transitions of a system, whereas the non-reactive part is typically structured according to the concepts of the application domain (e.g., the services provided by the system). In such systems, the non-reactive part of software stimulates the reactive part with event calls . Whenever the non-reactive part is modified (e.g., during evolution), the existing event calls may become invalid, new event calls may become necessary, and the two parts of software may become incompatible . Manually finding and repairing these types of defects is a time-consuming and error-prone maintenance task. In this article, we present a solution that combines source code model checking and aspect-oriented programming techniques, to reduce the time spent by developers and to automatically find defects, while performing the maintenance task mentioned above. In addition, we present controlled experiments showing that the solution can reduce the time by 75%, and enable the prevention of one defect per 140 lines of source code.

Abstract. Domain specific aspect languages (DSALs) are becoming more pop-ular because they can be designed to represent recurring concerns in a way that is optimized for a specific domain. However, the design and implementation of even a limited domain-specific aspect language can be a tedious job. To address this, we propose a framework that offers a fast way to prototype implementations of domain specific aspect languages. A particular goal of the framework is to be general enough to support a wide range of aspect language concepts, such that existing language concepts can be easily used, and new language concepts can be quickly created. We briefly introduce the framework and its underlying model, as well as the work-flow used when implementing DSALs. Subsequently, we show mappings of sev-eral domain specific aspect languages to demonstrate the framework. Since in our approach the DSALs are mapped to a common model, the framework provides an integrating platform allowing us to compose programs that use aspects written in multiple DSALs. The framework also provides explicit mechanisms to specify composition of advices written in multiple DSALs. 1

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