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We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket's JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for Racket proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites.
The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop-we discuss two strategies for identifying loops and measure their impact.
Distributed applications are hard to debug because timing-dependent network communication is a source of non-deterministic behavior. Current approaches to debug non deterministic failures include post-mortem debugging as well as record and replay. However, the first impairs system performance to gather data, whereas the latter requires developers to understand the timing-dependent communication at a lower level of abstraction than they develop at. Furthermore, both approaches require intrusive core library modifications to gather data from live systems. In this paper, we present the Peek-At-Talk debugger for investigating non-deterministic failures with low overhead in a systematic, top-down method, with a particular focus on tool-building issues in the following areas: First, we show how our debugging framework Path Tools guides developers from failures to their root causes and gathers run-time data with low overhead. Second, we present Peek-At-Talk, an extension to our Path Tools framework to record non-deterministic communication and refine behavioral data that connects source code with network events. Finally, we scope changes to the core library to record network communication without impacting other network applications.
We report our experience in implementing SqueakJS, a bitcompatible implementation of Squeak/Smalltalk written in pure JavaScript. SqueakJS runs entirely in theWeb browser with a virtual file system that can be directed to a server or client-side storage. Our implementation is notable for simplicity and performance gained through adaptation to the host object memory and deployment leverage gained through the Lively Web development environment. We present several novel techniques as well as performance measurements for the resulting virtual machine. Much of this experience is potentially relevant to preserving other dynamic language systems and making them available in a browser-based environment.
Virtual machine (VM) implementations are made of intricately intertwined subsystems, interacting largely through implicit dependencies. As the degree of crosscutting present in VMs is very high, VM implementations exhibit significant internal complexity. This study proposes an architecture approach for VMs that regards a VM as a composite of service modules coordinated through explicit bidirectional interfaces. Aspect-oriented programming techniques are used to establish these interfaces, to coordinate module interaction, and to declaratively express concrete VM architectures. A VM architecture description language is presented in a case study, illustrating the application of the proposed architectural principles.
Dynamic service adaptation
(2006)
Change can be observed in our environment and in the technology we build. While changes in the environment happen continuously and implicitly, our technology has to be kept in sync with the changing world around it. Although we can prepare for some of the changes for most of them we cannot. This is especially true for next-generation mobile communication systems that are expected to support the creation of a ubiquitous society where virtually everything is connected and made available within an organic information network. Resources will frequently join or leave the network, new types of media or new combinations of existing types will be used to interact and cooperate, and services will be tailored to preferences and needs of individual customers to better meet their needs. This paper outlines our research in the area of dynamic service adaptation to provide concepts and technologies allowing for such environments. Copyright (C) 2006 John Wiley & Sons, Ltd.
Use-cases are considered an integral part of most contemporary development processes since they describe a software system's expected behavior from the perspective of its prospective users. However, the presence of and traceability to use-cases is increasingly lost in later more code-centric development activities. Use-cases, being well-encapsulated at the level of requirements descriptions, eventually lead to crosscutting concerns in system design and source code. Tracing which parts of the system contribute to which use-cases is therefore hard and so limits understandability.
In this paper, we propose an approach to making use-cases first-class entities in both the programming language and the runtime environment. Having use-cases present in the code and the running system will allow developers, maintainers, and operators to easily associate their units of work with what matters to the users. We suggest the combination of use-cases, acceptance tests, and dynamic analysis to automatically associate source code with use-cases. We present UseCasePy, an implementation of our approach to use-case-centered development in Python, and its application to the Django Web framework.
Context-oriented programming (COP) provides dedicated support for defining and composing variations to a basic program behavior. A variation, which is defined within a layer, can be de-/activated for the dynamic extent of a code block. While this mechanism allows for control flow-specific scoping, expressing behavior adaptations can demand alternative scopes. For instance, adaptations can depend on dynamic object structure rather than control flow. We present scenarios for behavior adaptation and identify the need for new scoping mechanisms. The increasing number of scoping mechanisms calls for new language abstractions representing them. We suggest to open the implementation of scoping mechanisms so that developers can extend the COP language core according to their specific needs. Our open implementation moves layer composition into objects to be affected and with that closer to the method dispatch to be changed. We discuss the implementation of established COP scoping mechanisms using our approach and present new scoping mechanisms developed for our enhancements to Lively Kernel.
First-class concepts
(2022)
Ideally, programs are partitioned into independently maintainable and understandable modules. As a system grows, its architecture gradually loses the capability to accommodate new concepts in a modular way. While refactoring is expensive and not always possible, and the programming language might lack dedicated primary language constructs to express certain cross-cutting concerns, programmers are still able to explain and delineate convoluted concepts through secondary means: code comments, use of whitespace and arrangement of code, documentation, or communicating tacit knowledge. <br /> Secondary constructs are easy to change and provide high flexibility in communicating cross-cutting concerns and other concepts among programmers. However, such secondary constructs usually have no reified representation that can be explored and manipulated as first-class entities through the programming environment. <br /> In this exploratory work, we discuss novel ways to express a wide range of concepts, including cross-cutting concerns, patterns, and lifecycle artifacts independently of the dominant decomposition imposed by an existing architecture. We propose the representation of concepts as first-class objects inside the programming environment that retain the capability to change as easily as code comments. We explore new tools that allow programmers to view, navigate, and change programs based on conceptual perspectives. In a small case study, we demonstrate how such views can be created and how the programming experience changes from draining programmers' attention by stretching it across multiple modules toward focusing it on cohesively presented concepts. Our designs are geared toward facilitating multiple secondary perspectives on a system to co-exist in symbiosis with the original architecture, hence making it easier to explore, understand, and explain complex contexts and narratives that are hard or impossible to express using primary modularity constructs.
The performance of value classes is highly dependent on how they are represented in the virtual machine. Value class instances are immutable, have no identity, and can only refer to other value objects or primitive values and since they should be very lightweight and fast, it is important to optimize them carefully. In this paper we present a technique to detect and compress common patterns of value class usage to improve memory usage and performance. The technique identifies patterns of frequent value object references and introduces abbreviated forms for them. This allows to store multiple inter-referenced value objects in an inlined memory representation, reducing the overhead stemming from meta data and object references. Applied to a small prototype and an implementation of the Racket language, we found improvements in memory usage and execution time for several micro-benchmarks. (C) 2016 Elsevier B.V. All rights reserved.