Juice: An SVG Rendering Peer for Java Swing

SVG—a W3C XML standard—is a relatively new language for describing low-level vector drawings. Due to its cross-platform capabilities and support for events, SVG may potentially be used in interactive GUIs/graphical front-ends. However, a complete and full-featured widget set for SVG does not exist at the time of this writing. I have researched and implemented a framework which retargets a complete and mature raster- based widget library—the JFC Swing GUI library—into a vector-based display substrate: SVG. My framework provides SVG with a full-featured widget set, as well as augmenting Swing’s platform coverage. Furthermore, by using bytecode instrumentation techniques, my Swing to SVG bridging framework is transparent to the developers— allowing them to implement their user interfaces in pure Swing

Patenting Computer Data Structures: The Ghost, the Machine and the Federal Circuit

Courts view data structures, the mechanism by which computers store data in meaningful relationships, differently than do computer scientists. While computer scientists recognize that data structures have aspects that are both physical (how they are stored in memory) and logical (the relationships among the stored information), the Federal Circuit, in its attempts to set clear standards of the scope of patentability of data structures, has not fully appreciated their dualistic nature. This i-brief explains what data structures are, explores how courts have wrestled with setting a limiting principle to determine their patentability, and discusses the resultant impact on claim drafting

Speculative Staging for Interpreter Optimization

Interpreters have a bad reputation for having lower performance than just-in-time compilers. We present a new way of building high performance interpreters that is particularly effective for executing dynamically typed programming languages. The key idea is to combine speculative staging of optimized interpreter instructions with a novel technique of incrementally and iteratively concerting them at run-time. This paper introduces the concepts behind deriving optimized instructions from existing interpreter instructions---incrementally peeling off layers of complexity. When compiling the interpreter, these optimized derivatives will be compiled along with the original interpreter instructions. Therefore, our technique is portable by construction since it leverages the existing compiler's backend. At run-time we use instruction substitution from the interpreter's original and expensive instructions to optimized instruction derivatives to speed up execution. Our technique unites high performance with the simplicity and portability of interpreters---we report that our optimization makes the CPython interpreter up to more than four times faster, where our interpreter closes the gap between and sometimes even outperforms PyPy's just-in-time compiler.Comment: 16 pages, 4 figures, 3 tables. Uses CPython 3.2.3 and PyPy 1.

TIARA: Trust Management, Intrusion-tolerance, Accountability, and Reconstitution Architecture

The last 20 years have led to unprecedented improvements in chipdensity and system performance fueled mainly by Moore's Law. Duringthe same time, system and application software have bloated, leadingto unmanageable complexity, vulnerability to attack, rigidity and lackof robustness and accountability. These problems arise from the factthat all key elements of the computational environment, from hardwarethrough system software and middleware to application code regard theworld as consisting of unconstrained ``raw seething bits''. No elementof the entire stack is responsible for enforcing over-archingconventions of memory structuring or access control. Outsiders mayeasily penetrate the system by exploiting vulnerabilities (e.g. bufferoverflows) arising from this lack of basic constraints. Attacks arenot easily contained, whether they originate from the clever outsiderwho penetrates the defenses or from the insider who exploits existingprivileges. Finally, because there are no facilities for tracing theprovenance of data, even when an attack is detected, it is difficultif not impossible to tell which data are traceable to the attack andwhat data may still be trusted. We have abundant computational resources allowing us to fix thesecritical problems using a combination of hardware, system software,and programming language technology: In this report, we describe theTIARAproject, which is using these resources to design a newcomputer system thatis less vulnerable, more tolerant of intrusions, capable of recoveryfrom attacks, and accountable for their actions. TIARA provides thesecapabilities without significant impact on overall system performance. Itachieves these goals through the judicious use of a modest amountof extra, but reasonably generable purpose, hardware that is dedicatedto tracking the provenance of data at a very fine grained level, toenforcing access control policies, and to constructing a coherentobject-oriented model of memory. This hardware runs in parallel withthe main data-paths of the system and operates on a set of extra bitstagging each word with data-type, bounds, access control andprovenance information. Operations that violate the intendedinvariants are trapped, while normal results are tagged withinformation derived from the tags of the input operands.This hardware level provides fine-grained support for a series ofsoftware layers that enable a variety of comprehensive access controlpolicies, self-adaptive computing, and fine-grained recoveryprocessing. The first of these software layers establishes aconsistent object-oriented level of computing while higher layersestablish wrappers that may not be bypassed, access controls, dataprovenance tracking. At the highest level we create the ``planlevel'' of computing in which code is executed in parallel with anabstract model (or executable specification) of the system that checkswhether the code behaves as intended

A development framework for artificial intelligence based distributed operations support systems

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself

Rosen's (M,R) system in Unified Modelling Language

Robert Rosen's (M,R) system is an abstract biological network architecture that is allegedly non-computable on a Turing machine. If (M,R) is truly non-computable, there are serious implications for the modelling of large biological networks in computer software. A body of work has now accumulated addressing Rosen's claim concerning (M,R) by attempting to instantiate it in various software systems. However, a conclusive refutation has remained elusive, principally since none of the attempts to date have unambiguously avoided the critique that they have altered the properties of (M,R) in the coding process, producing merely approximate simulations of (M,R) rather than true computational models. In this paper, we use the Unified Modelling Language (UML), a diagrammatic notation standard, to express (M,R) as a system of objects having attributes, functions and relations. We believe that this instantiates (M,R) in such a way than none of the original properties of the system are corrupted in the process. Crucially, we demonstrate that (M,R) as classically represented in the relational biology literature is implicitly a UML communication diagram. Furthermore, since UML is formally compatible with object-oriented computing languages, instantiation of (M,R) in UML strongly implies its computability in object-oriented coding languages

Integrating CLIPS applications into heterogeneous distributed systems

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

ISIS and META projects

The ISIS project has developed a new methodology, virtual synchony, for writing robust distributed software. High performance multicast, large scale applications, and wide area networks are the focus of interest. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project is distributed control in a soft real-time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor, and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are reported