3,150 research outputs found

    Integrated testing and verification system for research flight software design document

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    The NASA Langley Research Center is developing the MUST (Multipurpose User-oriented Software Technology) program to cut the cost of producing research flight software through a system of software support tools. The HAL/S language is the primary subject of the design. Boeing Computer Services Company (BCS) has designed an integrated verification and testing capability as part of MUST. Documentation, verification and test options are provided with special attention on real time, multiprocessing issues. The needs of the entire software production cycle have been considered, with effective management and reduced lifecycle costs as foremost goals. Capabilities have been included in the design for static detection of data flow anomalies involving communicating concurrent processes. Some types of ill formed process synchronization and deadlock also are detected statically

    Same Coverage, Less Bloat: Accelerating Binary-only Fuzzing with Coverage-preserving Coverage-guided Tracing

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    Coverage-guided fuzzing's aggressive, high-volume testing has helped reveal tens of thousands of software security flaws. While executing billions of test cases mandates fast code coverage tracing, the nature of binary-only targets leads to reduced tracing performance. A recent advancement in binary fuzzing performance is Coverage-guided Tracing (CGT), which brings orders-of-magnitude gains in throughput by restricting the expense of coverage tracing to only when new coverage is guaranteed. Unfortunately, CGT suits only a basic block coverage granularity -- yet most fuzzers require finer-grain coverage metrics: edge coverage and hit counts. It is this limitation which prohibits nearly all of today's state-of-the-art fuzzers from attaining the performance benefits of CGT. This paper tackles the challenges of adapting CGT to fuzzing's most ubiquitous coverage metrics. We introduce and implement a suite of enhancements that expand CGT's introspection to fuzzing's most common code coverage metrics, while maintaining its orders-of-magnitude speedup over conventional always-on coverage tracing. We evaluate their trade-offs with respect to fuzzing performance and effectiveness across 12 diverse real-world binaries (8 open- and 4 closed-source). On average, our coverage-preserving CGT attains near-identical speed to the present block-coverage-only CGT, UnTracer; and outperforms leading binary- and source-level coverage tracers QEMU, Dyninst, RetroWrite, and AFL-Clang by 2-24x, finding more bugs in less time.Comment: CCS '21: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Securit

    Discovery Over Application: A Case Study of Misaligned Incentives in Software Engineering

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    In this thesis, we present evidence that there is an under-emphasis on the application of software systems in Software Engineering research, affecting the advancement of the field as a whole. Specifically, we perform a case-study on KLEE, a tool with over 1000 citations. We made improvements that consisted of fixing performance bugs and implementing optimizations that have become common practice, increasing KLEE\u27s performance by 2-11X. To understand how techniques proposed in the literature would be affected by these improvements, we analyzed 100 papers that cited the original KLEE paper. From this analysis we found two things. First, it is clear that coherence to the principles of replication is lacking; it was often very difficult to understand how a particular study used KLEE, and therefore to understand how our improvements would affect the study. Second, when conservatively estimating how the studies relied on KLEE, we believe that seven of the 21 papers that we investigated could have their conclusions significantly strengthened or weakened. Upon closer investigation, six of these seven papers involved studies that directly compared a KLEE or a KLEE dependent tool to some other tool. The potential for mis-application within these competing techniques makes it difficult to understand which observations are true, a situation that potentially leads to wasted effort and slowed progress. To conclude, we examine several recent proposals to address this under-emphasis, using KLEE as an exemplar to understand their likely effects. Advisers: Matthew B. Dwyer and Sebastian Elbau

    Restoring Independent Living after Disability Using a Wearable Device: A Synergistic Physio-Neuro Approach to Leverage Neuroplasticity

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    The number of people living with various grades of disability is now in excess of 1 billion. A significant portion of this population is dependent on caregivers and unable to access or afford therapy. This emerging healthcare challenge coincides with new knowledge about the self-learning, self-organizing, neuroplastic nature of the brain, offering hope to those trying to regain independence after disability. As conditions such as stroke and dementia begin to affect more and more people in the younger age groups, there is an urgent, global need for a connected rehabilitation solution that leverages the advantages of neuroplasticity to restore cognitive and physical function. This chapter explains a novel approach using a Synergistic Physio-Neuro learning model (SynPhNe learning model), which mimics how babies learn. This learning model has been embedded into a wearable, biofeedback device that can be used to restore function after stroke, injury, the degenerative effects of aging or a childhood learning disability. This chapter enumerates the clinical studies conducted with adult stroke patients in two scenarios—with therapist supervision and with lay person supervision. The results indicate that such a learning model is effective and promises to be an accessible and affordable solution for patients striving for independence

    Using Automated Task Solution Synthesis to Generate Critical Junctures for Management of Planned and Reactive Cooperation between a Human-Controlled Blimp and an Autonomous Ground Robot

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    This thesis documents the use of an approach for automated task solution synthesis that algorithmically and automatically identifies periods during which a team of less-than-fully capable robots benefit from tightly-coupled, coordinated, cooperative behavior. I test two hypotheses: 1) That a team’s performance can be increased by cooperating during certain specific periods of a mission and 2) That these periods can be identified automatically and algorithmically. I also demonstrate how identification of cooperative periods can be performed both off-line prior to the application and reactively during mission execution. I validate these premises in a real-world experiment using a human-piloted Unmanned Aerial Vehicle (UAV) and an autonomous mobile robot. For this experiment I construct a UAV and use an off-the-shelf robot. To identify the cooperative periods I use the ASyMTRe task solution synthesis system, and I use the Player robot server for control tasks such as navigation and path planning. My results show that teams employing cooperative behaviors during algorithmically identified cooperative periods exhibit better performance than non-cooperative teams in a target localization task. I also present results showing an increased time cost for cooperative behaviors and compare the increased time cost of two cooperative approaches that generate cooperative periods prior to and during mission execution

    A Methodological Framework for Parametric Combat Analysis

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    This work presents a taxonomic structure for understanding the tension between certain factors of stability for game-theoretic outcomes such as Nash optimality, Pareto optimality, and balance optimality and then applies such game-theoretic concepts to the advancement of strategic thought on spacepower. This work successfully adapts and applies combat modeling theory to the evaluation of cislunar space conflict. This work provides evidence that the reliability characteristics of small spacecraft share similarities to the reliability characteristics of large spacecraft. Using these novel foundational concepts, this dissertation develops and presents a parametric methodological framework capable of analyzing the efficacy of heterogeneous force compositions in the context of space warfare. This framework is shown to be capable of predicting a stochastic distribution of numerical outcomes associated with various modes of conflict and parameter values. Furthermore, this work demonstrates a general alignment in results between the game-theoretic concepts of the framework and Media Interaction Warfare Theory in terms of evaluating force efficacy, providing strong evidence for the validity of the methodological framework presented in this dissertation

    Corticomuscular interactions during different movement periods in a multi-joint compound movement

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    While much is known about motor control during simple movements, corticomuscular communication profiles during compound movement control remain largely unexplored. Here, we aimed at examining frequency band related interactions between brain and muscles during different movement periods of a bipedal squat (BpS) task utilizing regression corticomuscular coherence (rCMC), as well as partial directed coherence (PDC) analyses. Participants performed 40 squats, divided into three successive movement periods (Eccentric (ECC), Isometric (ISO) and Concentric (CON)) in a standardized manner. EEG was recorded from 32 channels specifically-tailored to cover bilateral sensorimotor areas while bilateral EMG was recorded from four main muscles of BpS. We found both significant CMC and PDC (in beta and gamma bands) during BpS execution, where CMC was significantly elevated during ECC and CON when compared to ISO. Further, the dominant direction of information flow (DIF) was most prominent in EEG-EMG direction for CON and EMG-EEG direction for ECC. Collectively, we provide novel evidence that motor control during BpS is potentially achieved through central motor commands driven by a combination of directed inputs spanning across multiple frequency bands. These results serve as an important step toward a better understanding of brain-muscle relationships during multi joint compound movements.V.V.N was supported by the HSE Basic Research Program and the Russian Academic Excellence Project '5–100'. This study was supported by the Max-Planck Society
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