18 research outputs found
Eelco Visser: The Oregon Connection
This paper shares some memories of Eelco gathered over the past 25 years as a colleague and friend, and reflects on the nature of modern international collaborations
Towards Zero-Overhead Disambiguation of Deep Priority Conflicts
**Context** Context-free grammars are widely used for language prototyping
and implementation. They allow formalizing the syntax of domain-specific or
general-purpose programming languages concisely and declaratively. However, the
natural and concise way of writing a context-free grammar is often ambiguous.
Therefore, grammar formalisms support extensions in the form of *declarative
disambiguation rules* to specify operator precedence and associativity, solving
ambiguities that are caused by the subset of the grammar that corresponds to
expressions.
**Inquiry** Implementing support for declarative disambiguation within a
parser typically comes with one or more of the following limitations in
practice: a lack of parsing performance, or a lack of modularity (i.e.,
disallowing the composition of grammar fragments of potentially different
languages). The latter subject is generally addressed by scannerless
generalized parsers. We aim to equip scannerless generalized parsers with novel
disambiguation methods that are inherently performant, without compromising the
concerns of modularity and language composition.
**Approach** In this paper, we present a novel low-overhead implementation
technique for disambiguating deep associativity and priority conflicts in
scannerless generalized parsers with lightweight data-dependency.
**Knowledge** Ambiguities with respect to operator precedence and
associativity arise from combining the various operators of a language. While
*shallow conflicts* can be resolved efficiently by one-level tree patterns,
*deep conflicts* require more elaborate techniques, because they can occur
arbitrarily nested in a tree. Current state-of-the-art approaches to solving
deep priority conflicts come with a severe performance overhead.
**Grounding** We evaluated our new approach against state-of-the-art
declarative disambiguation mechanisms. By parsing a corpus of popular
open-source repositories written in Java and OCaml, we found that our approach
yields speedups of up to 1.73x over a grammar rewriting technique when parsing
programs with deep priority conflicts--with a modest overhead of 1-2 % when
parsing programs without deep conflicts.
**Importance** A recent empirical study shows that deep priority conflicts
are indeed wide-spread in real-world programs. The study shows that in a corpus
of popular OCaml projects on Github, up to 17 % of the source files contain
deep priority conflicts. However, there is no solution in the literature that
addresses efficient disambiguation of deep priority conflicts, with support for
modular and composable syntax definitions
Avoiding Unnecessary Information Loss: Correct and Efficient Model Synchronization Based on Triple Graph Grammars
Model synchronization, i.e., the task of restoring consistency between two
interrelated models after a model change, is a challenging task. Triple Graph
Grammars (TGGs) specify model consistency by means of rules that describe how
to create consistent pairs of models. These rules can be used to automatically
derive further rules, which describe how to propagate changes from one model to
the other or how to change one model in such a way that propagation is
guaranteed to be possible. Restricting model synchronization to these derived
rules, however, may lead to unnecessary deletion and recreation of model
elements during change propagation. This is inefficient and may cause
unnecessary information loss, i.e., when deleted elements contain information
that is not represented in the second model, this information cannot be
recovered easily. Short-cut rules have recently been developed to avoid
unnecessary information loss by reusing existing model elements. In this paper,
we show how to automatically derive (short-cut) repair rules from short-cut
rules to propagate changes such that information loss is avoided and model
synchronization is accelerated. The key ingredients of our rule-based model
synchronization process are these repair rules and an incremental pattern
matcher informing about suitable applications of them. We prove the termination
and the correctness of this synchronization process and discuss its
completeness. As a proof of concept, we have implemented this synchronization
process in eMoflon, a state-of-the-art model transformation tool with inherent
support of bidirectionality. Our evaluation shows that repair processes based
on (short-cut) repair rules have considerably decreased information loss and
improved performance compared to former model synchronization processes based
on TGGs.Comment: 33 pages, 20 figures, 3 table
Language Support for Programming High-Performance Code
Nowadays, the computing landscape is becoming increasingly heterogeneous and this trend is currently showing no signs of turning around. In particular, hardware becomes more and more specialized and exhibits different forms of parallelism. For performance-critical codes it is indispensable to address hardware-specific peculiarities. Because of the halting problem, however, it is unrealistic to assume that a program implemented in a general-purpose programming language can be fully automatically compiled to such specialized hardware while still delivering peak performance. One form of parallelism is single instruction, multiple data (SIMD). Part I of this thesis presents Sierra: an extension for C ++ that facilitates portable and effective SIMD programming. Part II discusses AnyDSL. This framework allows to embed a so-called domain-specific language (DSL) into a host language. On the one hand, a DSL offers the application developer a convenient interface; on the other hand, a DSL can perform domain-specific optimizations and effectively map DSL constructs to various architectures. In order to implement a DSL, one usually has to write or modify a compiler. With AnyDSL though, the DSL constructs are directly implemented in the host language while a partial evaluator removes any abstractions that are required in the implementation of the DSL.Die Rechnerlandschaft wird heutzutage immer heterogener und derzeit ist keine Trendwende in Sicht. Insbesondere wird die Hardware immer spezialisierter und weist verschiedene Formen der Parallelität auf. Für performante Programme ist es unabdingbar, hardwarespezifische Eigenheiten zu adressieren. Wegen des Halteproblems ist es allerdings unrealistisch anzunehmen, dass ein Programm, das in einer universell einsetzbaren Programmiersprache implementiert ist, vollautomatisch auf solche spezialisierte Hardware übersetzt werden kann und dabei noch Spitzenleistung erzielt. Eine Form der Parallelität ist „single instruction, multiple data (SIMD)“. Teil I dieser Arbeit stellt Sierra vor: eine Erweiterung für C++, die portable und effektive SIMD-Programmierung unterstützt. Teil II behandelt AnyDSL. Dieses Rahmenwerk ermöglicht es, eine sogenannte domänenspezifische Sprache (DSL) in eine Gastsprache einzubetten. Auf der einen Seite bietet eine DSL dem Anwendungsentwickler eine komfortable Schnittstelle; auf der anderen Seiten kann eine DSL domänenspezifische Optimierungen durchführen und DSL-Konstrukte effektiv auf verschiedene Architekturen abbilden. Um eine DSL zu implementieren, muss man gewöhnlich einen Compiler schreiben oder modifizieren. In AnyDSL werden die DSL-Konstrukte jedoch direkt in der Gastsprache implementiert und ein partieller Auswerter entfernt jegliche Abstraktionen, die in der Implementierung der DSL benötigt werden
Programming Languages and Systems
This open access book constitutes the proceedings of the 29th European Symposium on Programming, ESOP 2020, which was planned to take place in Dublin, Ireland, in April 2020, as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The actual ETAPS 2020 meeting was postponed due to the Corona pandemic. The papers deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems
Implicit Incremental Model Analyses and Transformations
When models of a system change, analyses based on them have to be reevaluated in order for the results to stay meaningful. In many cases, the time to get updated analysis results is critical. This thesis proposes multiple, combinable approaches and a new formalism based on category theory for implicitly incremental model analyses and transformations. The advantages of the implementation are validated using seven case studies, partially drawn from the Transformation Tool Contest (TTC)