Combining Aspect-Oriented and Strategic Programming

Properties such as logging, persistence, debugging, tracing, distribution, performance monitoring and exception handling occur in most programming paradigms and are normally very difficult or even impossible to modularizewith traditional modularization mechanisms because they are cross-cutting. Recently, aspect-oriented programming has enjoyed recognition as a practical solution for separating these concerns. In this paper we describe an extension to the Stratego term rewriting language for capturing such properties. We show our aspect language offers a concise, practical and adaptable solution for dealing with unanticipated algorithm extension for forward data-flow propagation and dynamic type checking of terms. We briefly discuss some of the challenges faced when designing and implementing an aspect extension for and in a rule-based term rewriting system.publishedVersio

Scope States (Artifact)

Compilers that can type check compilation units in parallel can make more efficient use of multi-core architectures, which are nowadays widespread. Developing parallel type checker implementations is complicated by the need to handle concurrency and synchronization of parallel compilation units. This artifact contains benchmarks and sources for a new framework for implementing hierarchical type checkers that provides implicit parallel execution in the presence of dynamic and mutual dependencies between compilation units. The resulting type checkers can be written without explicit handling of communication or synchronization between different compilation units. We achieve this by providing type checkers with an API for name resolution based on scope graphs, a language-independent formalism that supports a wide range of binding patterns. Our framework is implemented in Java using the actor paradigm. We evaluated our approach by parallelizing the solver for Statix, a meta-language for type checkers based on scope graphs, using our framework. Benchmarks show that the approach results in speedups for the parallel Statix solver of up to 5.0x on 8 cores for real-world code bases

Preventing injection attacks with syntax embeddings

Software written in one language often needs to construct sen-tences in another language, such as SQL queries, XML output, or shell command invocations. This is almost always done using un-hygienic string manipulation, the concatenation of constants and client-supplied strings. A client can then supply specially crafted input that causes the constructed sentence to be interpreted in an unintended way, leading to an injection attack. We describe a more natural style of programming that yields code that is impervious to injections by construction. Our approach embeds the grammars of the guest languages (e.g., SQL) into that of the host language (e.g., Java) and automatically generates code that maps the embed-ded language to constructs in the host language that reconstruct the embedded sentences, adding escaping functions where appropriate. This approach is generic, meaning that it can be applied with rela-tive ease to any combination of host and guest languages

Scopes Describe Frames: A Uniform Model for Memory Layout in Dynamic Semantics

Semantic specifications do not make a systematic connection between the names and scopes in the static structure of a program and memory layout, and access during its execution. In this paper, we introduce a systematic approach to the alignment of names in static semantics and memory in dynamic semantics, building on the scope graph framework for name resolution. We develop a uniform memory model consisting of frames that instantiate the scopes in the scope graph of a program. This provides a language-independent correspondence between static scopes and run-time memory layout, and between static resolution paths and run-time memory access paths. The approach scales to a range of binding features, supports straightforward type soundness proofs, and provides the basis for a language-independent specification of sound reachability-based garbage collection

IceDust: Incremental and Eventual Computation of Derived Values in Persistent Object Graphs

Derived values are values calculated from base values. They can be expressed in object-oriented languages by means of getters calculating the derived value, and in relational or logic databases by means of (materialized) views. However, switching to a different calculation strategy (for example caching) in object-oriented programming requires invasive code changes, and the databases limit expressiveness by disallowing recursive aggregation. In this paper, we present IceDust, a data modeling language for expressing derived attribute values without committing to a calculation strategy. IceDust provides three strategies for calculating derived values in persistent object graphs: Calculate-on-Read, Calculate-on-Write, and Calculate-Eventually. We have developed a path-based abstract interpretation that provides static dependency analysis to generate code for these strategies. Benchmarks show that different strategies perform better in different scenarios. In addition we have conducted a case study that suggests that derived value calculations of systems used in practice can be expressed in IceDust

Agromere: how to integrate urban agriculture in the development of the Dutch city of Almere?

Urban agriculture produces green city areas with as an extra dimension providing food, energy, care, education or recreation for the civilians. And thus it can contribute to a more sustainable and liveable cities. The objective of the project Agromere is to create a process which will lead to a new residential quarter where agriculture is fully integrated in city live. Agromere is situated in the fast growing city of Almere, the Netherlands. In a combined stakeholder and design process a township is designed which integrates living (5,000 inhabitants) with urban agriculture on 250 ha. During this process an enthusiastic network of stakeholders has been established which developed innovating and unique ideas on urban farming. The potential for organic farming in the city is high because of its emphasis on animal welfare and consumer relations

Scopes Describe Frames: A Uniform Model for Memory Layout in Dynamic Semantics (Artifact)

Our paper introduces a systematic approach to the alignment of names in the static structure of a program, and memory layout and access during its execution. We develop a uniform memory model consisting of frames that instantiate the scopes in the scope graph of a program. This provides a language-independent correspondence between static scopes and run-time memory layout, and between static resolution paths and run-time memory access paths. The approach scales to a range of binding features, supports straightforward type soundness proofs, and provides the basis for a language-independent specification of sound reachability-based garbage collection. This Coq artifact showcases how our uniform model for memory layout in dynamic semantics provides structure to type soundness proofs. The artifact contains type soundness proofs mechanized in Coq for (supersets of) all languages in the paper. The type soundness proofs rely on a language-independent framework formalizing scope graphs and frame heaps

IceDust 2: Derived Bidirectional Relations and Calculation Strategy Composition (Artifact)

This artifact is based on IceDust2, a data modeling language with derived values. The provided package is designed to support the claims of the companion paper: in particular, it allows users to compile and run IceDust2 specifications. Instructions for building the IceDust2 compiler from source in Spoofax are also provided

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

Stateful Entities: Object-oriented Cloud Applications as Distributed Dataflows

Programming stateful cloud applications remains a very painful experience. Instead of focusing on the business logic, programmers spend most of their time dealing with distributed systems considerations, with the most important being consistency, load balancing, failure management, recovery, and scalability. At the same time, we witness an unprecedented adoption of modern dataflow systems such as Apache Flink, Google Dataflow, and Timely Dataflow. These systems are now performant and fault-tolerant, and they offer excellent state management primitives. With this line of work, we aim at investigating the opportunities and limits of compiling general-purpose programs into stateful dataflows. Given a set of easy-to-follow code conventions, programmers can author stateful entities, a programming abstraction embedded in Python. We present a compiler pipeline named StateFlow, to analyze the abstract syntax tree of a Python application and rewrite it into an intermediate representation based on stateful dataflow graphs. StateFlow compiles that intermediate representation to a target execution system: Apache Flink and Beam, AWS Lambda, Flink's Statefun, and Cloudburst. Through an experimental evaluation, we demonstrate that the code generated by StateFlow incurs minimal overhead. While developing and deploying our prototype, we came to observe important limitations of current dataflow systems in executing cloud applications at scale