Search

Repository mining research is a data-intensive domain with a focus on source code. There are many ways to search for code in the worldwide software ecosystem, but these search methods are inefficient and only cover small parts of the software ecosystem. One of the problems is granularity: it is possible to search through code on a file-level and cover a significant part of the software ecosystem or search for a line of code and only cover a small part of the software ecosystem, but not both. We propose SearchSECO: a language-agnostic search engine and research platform that searches through abstract representations of source code methods. We use SearchSECO to search across the worldwide software ecosystem and index the encountered methods. With SearchSECO, the field is advanced because it (1) provides finer-grained and more efficient searches, (2) covers more of the software ecosystem than other search mechanisms, and (3) provides mechanisms for source code provenance.

International audience; Read-eval-print-loops (REPLs) allow programmers to test out snippets of code, explore APIs, or even incrementally construct code, and get immediate feedback on their actions. However, even though many languages provide a REPL, the relation between the language as is and what is accepted at the REPL prompt is not always well-defined. Furthermore, implementing a REPL for new languages, such as DSLs, may incur significant language engineering cost. In this paper we survey the domain of REPLs and investigate the (formal) principles underlying REPLs. We identify and define the class of sequential languages, which admit a sound REPL implementation based on a definitional interpreter , and present design guidelines for extending existing language implementations to support REPL-style interfaces (including computational notebooks). The obtained REPLs can then be generically turned into an exploring interpreter, to allow exploration of the user's interaction. The approach is illustrated using three case studies, based on MiniJava, QL (a DSL for questionnaires), and eFLINT (a DSL for normative rules). We expect sequential languages, and the consequent design principles, to be stepping stones towards a better understanding of the essence of REPLs.

Block-based programming systems employ a jigsaw metaphor to write programs. They are popular in the domain of programming education (e.g., Scratch), but also used as a programming interface for end-users in other disciplines, such as arts, robotics, and configuration management. In particular, block-based environments promise a convenient interface for Domain-Specific Languages (DSLs) for domain experts who might lack a traditional programming education. However, building a block-based environment for a DSL from scratch requires significant effort. This paper presents an approach to engineer block-based language interfaces by reusing existing language artifacts. We present Kogi, a tool for deriving block-based environments from context-free grammars. We identify and define the abstract structure for describing block-based environments. Kogi transforms a context-free grammar into this structure, which then generates a block-based environment based on Google Blockly. The approach is illustrated with four case studies, a DSL for state machines, Sonification Blocks (a DSL for sound synthesis), Pico (a simple programming language), and QL (a DSL for questionnaires). The results show that usable block-based environments can be derived from context-free grammars, and with an order of magnitude reduction in effort.

Programming is everywhere, and is becoming an increasingly essential component of knowledge work outside the realms of traditional software development. Examples include data journalism, scientific computing, machine control, machine learning, financial management, and others. A key aspect of this trend is that users have to use programming tools, but typically lack programming education, let alone a computer science background. In this short paper we revisit potential assumptions and preconceptions underlying traditional programming system design, from the perspective of practicing scientists using tools like MATLAB, R, Bash, Python, C++, and others. Specifically, we aim to peel off some ingrained assumptions that have informed programming language and system design for decades. Without giving a lot of answers, we hope some of our contrarian observations may turn out to be controversial, and stimulate a meaningful discussion towards a better programmer experience in the domain of science.

Interactive notebooks allow people to communicate and collaborate through a single rich document that might include live code, multimedia, computed results, and documentation, which is persisted as a whole for reproducibility. Notebooks are currently being used extensively in domains such as data science, data journalism, and machine learning. However, constructing a notebook interface for a new language requires a lot of effort. In this tool paper, we present Bacatá, a language parametric notebook generator for domain-specific languages (DSL) based on the Jupyter framework. Bacatá is designed so that language engineers may reuse existing language components (such as parsers, code generators, interpreters, etc.) as much as possible. Moreover, we explain the design of Bacatá and how DSL notebooks can be generated with minimum effort in the context of the Rascal meta programming system and language workbench.

Interactive notebooks, such as provided by the Jupyter plat- form [ 2 ], are gaining traction in scientic computing, data science, and machine learning. Developing a Jupyter kernel machinery for a new language, however, requires consider- able eort. In this extended abstract, we present Bacatá, a language-parametric bridge between Jupyter and the Rascal language workbench [3 ]. Reusing existing language compo- nents, such as a parsers, interpreters, Read-Eval-Print Loop (REPLs) and autocomplete, Bacatá generates a Jupyter kernel machinery so that the DSL can be used in notebook form. We sketch the architecture of Bacatá and demonstrate it in action using a DSL for image processing, called Amalga.

Large organizations like banks suffer from the ever growing complexity of their systems. Evolving the software becomes harder and harder since a single change can affect a much larger part of the system than predicted upfront. A large contributing factor to this problem is that the actual domain knowledge is often implicit, incomplete, or out of date, making it difficult to reason about the correct behavior of the system as a whole. With Rebel we aim to capture and centralize the domain knowledge and relate it to the running systems. Rebel is a formal specification language for controlling the intrinsic complexity of software for financial enterprise systems. In collaboration with ING, a large Dutch bank, we developed the Rebel specification language and an Integrated Specification Environment (ISE), currently offering automated simulation and checking of Rebel specifications using a Satisfiability Modulo Theories (SMT) solver. In this paper we report on our design choices for Rebel, the implementation and features of the ISE, and our initial observations on the application of Rebel inside the bank.

International audience; Modular interpreters have the potential to achieve component-based language development: instead of writing language interpreters from scratch, they can be assembled from reusable, semantic building blocks. Unfortunately, traditional language interpreters are hard to extend because different language constructs may require different interpreter signatures. For instance, arithmetic interpreters produce a value without any context information, whereas binding constructs require an additional environment. In this paper, we present a practical solution to this problem based on implicit context propagation. By structuring denotational-style interpreters as Object Algebras, base interpreters can be retroactively lifted into new interpreters that have an extended signature. The additional parameters are implicitly propagated behind the scenes, through the evaluation of the base interpreter. Interpreter lifting enables a flexible style of component-based language development. The technique works in mainstream object-oriented languages, does not sacrifice type safety or separate compilation, and can be easily automated. We illustrate implicit context propagation using a modular definition of Featherweight Java and its extension to support side-effects.

International audience; 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.