Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)

The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition

The Rascal Language Workbench

Rascal is a programming language for source code analysis and transformation. This means that typically the input of a Rascal program is a program in some programming language, and the output is often yet another program. So Rascal is a meta programming language. Source code is thus primary object of manipulation in Rascal. Many of the use cases that Rascal is designed to address, follow the Extract-Analyze- SYnthesize, or EASY paradigm (shown in Figure 1.1). Meta programs often start by extracting information (facts) from the input program. This is the extraction phase. An example could be the call-graph of a program. Then, this extracted information is often subject to analysis: derived facts are computed, the information is enriched. For the call graph, a simple analysis is determining the root or leaf routines in the a source program by analysing the extracted call-graph. Another analysis could be concerned by identifying routines that are never called (dead code). Finally, the meta program will synthesize some kind of result. This can be transformed source code (e.g., removal of dead code from the input program), a report (e.g., statistics on the number of root and leaf routines), or a visualization (e.g., a graphical depiction of the call-graph). Of course, these phases are not strictly sequential: there may be feedback loops. Some analysis leads to new extraction, synthesis of a result may lead to new analyses and so on. Rascal has elaborated features to support each of the phases of the EASY paradigm fully integrated in the language. Naturally, the implementation of domain specific languages (DSLs), or more generally, modeldriven engineering (MDE) fits the EASY paradigm very well. When implementing a DSL compiler or interpreter the input is, of course, DSL source code. Extraction could, for instance, include the derivation of an AST from the concrete syntax tree. Another extracted model could be a graph-like structure representing the input in a more abstract way, or a performance model. Such abstractions are input to analyses such as constraint checking or type checking, verification, quality-of-service analysis etc. Finally, synthesis covers tasks such as graphical visualization, code generation, and optimization. To conclude, in the context of Rascal, we see DSL implementation as an instance of source code analysis and transformation

Composing configurable Java components

This paper presents techniques to reason about the composition of configurable components and to automatically derive consistent compositions. The reasoning is achieved by describing components in a formal component description language, that allows the description of component variability, dependencies and configuration actions. It also enables the automatic, configuration-driven, derivation of product instances. To illustrate the approach we instantiate the abstract component model for Java components (packages

Mobile applications in colorectal surgery:Digitally advancing patient care

This thesis describes the current landscape of medical mobile applications, assesses patients’ perspectives on stoma care, and evaluates the clinical effectiveness of patient-centred mobile applications in colorectal surgical care. This thesis highlights the importance of data privacy and safety regulations in medical mobile applications. Mobile applications have the potential to enhance and support colorectal surgical care in several ways. However, only a limited number of applications have been adequately assessed in peer-reviewed literature. An essential component is to safeguard the accuracy of medical content and ensure that apps undergo robust research and vetting. Therefore, we have researched the needs of both patients and healthcare providers. Based on these findings the Stoma App was developed and clinically evaluated. Clinical trials assessed the effectiveness of both the Stoma App and the ERAS App in improving patient outcomes. Results showed notable enhancements, with the Stoma App significantly boosting postoperative stoma-related quality of life, while the ERAS App notably improved patient adherence to the ERAS protocol. This thesis emphasises the feasibility of integrating medical applications into colorectal surgical care, revealing their potential to enhance patient empowerment and other outcomes. However, the prevailing challenge is that the majority of presently available apps lack sufficient clinical evaluation regarding their effectiveness and safety. The journey toward the systematic integration of medical apps into clinical practice demands the overcoming of several hurdles