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Computer programs are often viewed as collections of functions – each function has parameters (inputs) and computes a return value, and each has potential side effects that modify program state (outputs). In this research, a Sandia symbolic execution tool designed to support “human-in-the-loop” analysis was modified to automatically create “function summaries,” and a new tool, “diaboolical,” was created to support enhancing readability of the summary using a novel approach to bit-vector simplification that leverages logic synthesis and tautologies. For this effort, students at Auburn University created several finite state machines (FSMs) to serve as exemplars for high-consequence systems. Function summaries for each of the machines were obtained, and then portions of the summaries were simplified using both diaboolical and the simplification procedure of a popular SMT solver. A comparison of the results shows that diaboolical can often produce smaller function summaries, with expression length improvements over the unsimplified function summaries ranging from 0% to 90% for diaboolical and 0% to 65% for the SMT solver, though diaboolical had a significantly greater cost in time. Diaboolical was evaluated against a collection of “arbitrary” C-code as well as FSM exemplars, and for both datasets it achieved an approximately 10% improvement in expression length compared to simplifications that could be obtained using existing techniques. Function summaries can assist assurance efforts that evaluate existing systems and their executable code. A smaller function summary is likely easier for humans to understand and could thus increase the ability and efficacy of assurance practices centered around the analysis of executable artifacts.
Regression verification techniques are used to prove equivalence of syntactically similar programs. Checking equivalence of large programs, however, can be computationally expensive. Existing regression verification techniques rely on abstraction and decomposition techniques to reduce the computational effort of checking equivalence of the entire program. These techniques are sound but not complete. In this work, we propose a novel approach to improve scalability of regression verification by classifying the program behaviors generated during symbolic execution as either impacted or unimpacted. Our technique uses a combination of static analysis and symbolic execution to generate summaries of impacted program behaviors. The impact summaries are then checked for equivalence using an o-the-shelf decision procedure. We prove that our approach is both sound and complete for sequential programs, with respect to the depth bound of symbolic execution. Our evaluation on a set of sequential C artifacts shows that reducing the size of the summaries can help reduce the cost of software equivalence checking. Various reduction, abstraction, and compositional techniques have been developed to help scale software verification techniques to industrial-sized systems. Although such techniques have greatly increased the size and complexity of systems that can be checked, analysis of large software systems remains costly. Regression analysis techniques, e.g., regression testing [16], regression model checking [22], and regression verification [19], restrict the scope of the analysis by leveraging the differences between program versions. These techniques are based on the idea that if code is checked early in development, then subsequent versions can be checked against a prior (checked) version, leveraging the results of the previous analysis to reduce analysis cost of the current version. Regression verification addresses the problem of proving equivalence of closely related program versions [19]. These techniques compare two programs with a large degree of syntactic similarity to prove that portions of one program version are equivalent to the other. Regression verification can be used for guaranteeing backward compatibility, and for showing behavioral equivalence in programs with syntactic differences, e.g., when a program is refactored to improve its performance, maintainability, or readability. Existing regression verification techniques leverage similarities between program versions by using abstraction and decomposition techniques to improve scalability of the analysis [10, 12, 19]. The abstractions and decomposition in the these techniques, e.g., summaries of unchanged code [12] or semantically equivalent methods [19], compute an over-approximation of the program behaviors. The equivalence checking results of these techniques are sound but not complete-they may characterize programs as not functionally equivalent when, in fact, they are equivalent. In this work we describe a novel approach that leverages the impact of the differences between two programs for scaling regression verification. We partition program behaviors of each version into (a) behaviors impacted by the changes and (b) behaviors not impacted (unimpacted) by the changes. Only the impacted program behaviors are used during equivalence checking. We then prove that checking equivalence of the impacted program behaviors is equivalent to checking equivalence of all program behaviors for a given depth bound. In this work we use symbolic execution to generate the program behaviors and leverage control- and data-dependence information to facilitate the partitioning of program behaviors. The impacted program behaviors are termed as impact summaries. The dependence analyses that facilitate the generation of the impact summaries, we believe, could be used in conjunction with other abstraction and decomposition based approaches, [10, 12], as a complementary reduction technique. An evaluation of our regression verification technique shows that our approach is capable of leveraging similarities between program versions to reduce the size of the queries and the time required to check for logical equivalence. The main contributions of this work are: - A regression verification technique to generate impact summaries that can be checked for functional equivalence using an off-the-shelf decision procedure. - A proof that our approach is sound and complete with respect to the depth bound of symbolic execution. - An implementation of our technique using the LLVMcompiler infrastructure, the klee Symbolic Virtual Machine [4], and a variety of Satisfiability Modulo Theory (SMT) solvers, e.g., STP [7] and Z3 [6]. - An empirical evaluation on a set of C artifacts which shows that the use of impact summaries can reduce the cost of regression verification.
Recent advancements in scientific equipment and the adaptation of electronics and the Internet of Things (IoT) in our everyday lives resulted in large and complex data production at a high rate. Making meaningful and timely knowledge discovery at a modest cost from this big data is difficult for computing power and storage limitations. Training deep learning models incrementally in a streaming setting can help us with overcoming these limitations. However, in a well-known phenomenon named catastrophic forgetting, incrementally trained models increasingly perform poorly on the past data. To mitigate catastrophic forgetting in training in a streaming setting, we propose constructing a historical summary over time and use the summary with newly arrived data during incremental training. We propose various data summarization techniques such as random sampling, micro clustering, coreset computation, and Auto Encoders to counteract catastrophic forgetting. We built a pipeline for incremental training with a historical summary for training deep learning models for streaming data. We demonstrate the effectiveness of historical summary in mitigating catastrophic forgetting using three case studies involving three different deep learning applications: an Artificial Neural Network (ANN) for classification task on MNIST dataset, a language model (RNN-LM) on the WikiText2 dataset, and a Convolutional Neural Network (CNN), ResNet50 to classify the ImageNet dataset. Through the training of the models, we observe that catastrophic forgetting is evident in ANN and CNN but not in an RNN. For the first task, our method recovers up to 47.9% lost accuracy due to catastrophic forgetting. For the third task, the historical summary recovers classification accuracy by up to 25%. For the second task, though there is not proof of catastrophic forgetting, the training performance (PPL) improves by up to 26% with historical summary.
NASA's Office of Aeronautics and Space Technology (OAST) conducted a workshop on technology for space station evolution 16-19 Jan. 1990. The purpose of this workshop was to collect and clarify Space Station Freedom technology requirements for evolution and to describe technologies that can potentially fill those requirements. These proceedings are organized into an Executive Summary and Overview and five volumes containing the technology discipline presentations. The Executive Summary and Overview contains an executive summary for the workshop, the technology discipline summary packages, and the keynote address. The executive summary provides a synopsis of the events and results of the workshop and the technology discipline summary packages.
Under the mandate contained in the FY 1976 NASA Authorization Act, the National Aeronautics and Space Administration (NASA) has developed and is implementing a comprehensive program of research, technology, and monitoring of the Earth's upper atmosphere, with emphasis on the stratosphere. This program aims at expanding our understanding to permit both the quantitative analysis of current perturbations as well as the assessment of possible future changes in this important region of our environment. It is carried out jointly by the Upper Atmosphere Research Program (UARP) and the Atmospheric Chemistry Modeling and Analysis Program (ACMAP), both managed within the Science Division in the Office of Mission to Planet Earth at NASA. Significant contributions to this effort are also provided by the Atmospheric Effects of Aviation Project (AEAP) of NASA's Office of Aeronautics. The long-term objectives of the present program are to perform research to: understand the physics, chemistry, and transport processes of the upper atmosphere and their effect on the distribution of chemical species in the stratosphere, such as ozone; understand the relationship of the trace constituent composition of the lower stratosphere and the lower troposphere to the radiative balance and temperature distribution of the Earth's atmosphere; and accurately assess possible perturbations of the upper atmosphere caused by human activities as well as by natural phenomena. In compliance with the Clean Air Act Amendments of 1990, Public Law 101-549, NASA has prepared a report on the state of our knowledge of the Earth's upper atmosphere, particularly the stratosphere, and on the progress of UARP and ACMAP. The report for the year 1996 is composed of two parts. Part 1 summarizes the objectives, status, and accomplishments of the research tasks supported under NASA UARP and ACMAP in a document entitled, Research Summary 1994-1996. Part 2 is entitled Present State of Knowledge of the Upper Atmosphere 1996.- An Assessment Report. It consists primarily of the Executive Summary and Chapter Summaries of the World Meteorological Organization Global Ozone Research and Monitoring Project Report No. 37, Scientific Assessment of Ozone Depletion: 1994, sponsored by NASA, the National Oceanic and Atmospheric Administration (NOAA), the UK Department of the Environment, the United Nations Environment Program, and the World Meteorological Organization. Other sections of Part 11 include summaries of the following: an Atmospheric Ozone Research Plan from NASA's Office of Mission to Planet Earth; summaries from a series of Space Shuttle-based missions and two recent airborne measurement campaigns; the Executive Summary of the 1995 Scientific Assessment of the Atmospheric Effects of Stratospheric Aircraft, and the most recent evaluation of photochemical and chemical kinetics data (Evaluation No. 12 of the NASA Panel for Data Evaluation) used as input parameters for atmospheric models.
This report documents results obtained for revisions made to cases involving Highly Enriched Uranium (HEU), Intermediate Enriched Uranium (IEU), a mixture of Pu and Uranium (MIX), as well as Pu cases. A previous summary of revisions for HEU an Pu cases was reported and additional investigations into four cases originally presented therein uncovered further revisions which led to better agreement with other transport codes, those cases are updated in this report. The summary of all cases reported in Reference 2 is updated in this report. In addition, a previous summary of revisions for LEU and MIX was reported, a summary of those revisions in reproduced in this report for a comprehensive summary of changes to benchmarks beginning in fiscal year 2020 to current date. The report focuses on the changes made to LANL benchmarks modeled with MCNP6 using ENDF/B-VII.1 nuclear data that appeared to have discrepant results when compared with results of other codes. Feedback was used to pinpoint review of benchmark input files and to revise them when necessary. This report documents the results of review and revision of specific benchmarks highlighted as possibly discrepant in the comparison study. In addition, there is an effort tied to this work involving collaboration between LANL XCP and NCS Divisions in the development of a shared review/revision procedure and use of a new benchmark repository. LANL has a benchmark library of critical experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook modeled for use with MCNP. This collection is now over 1100 benchmarks, referred to as the Whisper-1.1 library because it is used with the sensitivity/uncertainty package, Whisper, which supports nuclear criticality safety validation and is released with MCNP6.2. The collection, originally created several decades ago, is a combination of smaller collections, which has been revised and expanded, by various groups at LANL over the years. The original authors are no longer at the laboratory and little formal documentation of review and revision of these benchmarks exists today. A branch of the benchmark collection was already the subject of a formal review undertaken by the LANL NCS Division and expanded to include XCP Division.
A computer program, the Subsystems Component Definitions Summary (SUBCOMDEF), was developed to provide a quick and efficient means of summarizing large quantities of subsystems component data in terms of weight, volume, resupply, and power. The program was validated using Space Station Freedom Program Definition Requirements Document data for the internal and external thermal control subsystem. Once all component descriptions, unit weights and volumes, resupply, and power data are input, the user may obtain a summary report of user-specified portions of the subsystem or of the entire subsystem as a whole. Any combination or all of the parameters of wet and dry weight, wet and dry volume, resupply weight and volume, and power may be displayed. The user may vary the resupply period according to individual mission requirements, as well as the number of hours per day power consuming components operate. Uses of this program are not limited only to subsystem component summaries. Any applications that require quick, efficient, and accurate weight, volume, resupply, or power summaries would be well suited to take advantage of SUBCOMDEF's capabilities.
This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.
This publication contains the preliminary agenda and summaries for the Third Annual JPL Airborne Geoscience Workshop, held at the Jet Propulsion Laboratory, Pasadena, California, on 1-5 June 1992. This main workshop is divided into three smaller workshops as follows: (1) the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on June 1 and 2; the summaries for this workshop appear in Volume 1; (2) the Thermal Infrared Multispectral Scanner (TIMS) workshop, on June 3; the summaries for this workshop appear in Volume 2; and (3) the Airborne Synthetic Aperture Radar (AIRSAR) workshop, on June 4 and 5; the summaries for this workshop appear in Volume 3.
This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D. C. October 25-29, 1993 The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, October 25-26 (the summaries for this workshop appear in this volume, Volume 1); The Thermal Infrared Multispectral Scanner (TMIS) workshop, on October 27 (the summaries for this workshop appear in Volume 2); and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, October 28-29 (the summaries for this workshop appear in Volume 3).
This is volume 2 of a three volume set of publications that contain the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on October 25-26. The summaries for this workshop appear in Volume 1. The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27. The summaries for this workshop appear in Volume 2. The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29. The summaries for this workshop appear in Volume 3.
This publication contains the summaries for the Fourth Annual JPL Airborne Geoscience Workshop, held in Washington, D.C. on October 25-29, 1993. The main workshop is divided into three smaller workshops as follows: The Airborne Visible/Infrared Spectrometer (AVIRIS) workshop, on October 25-26, whose summaries appear in Volume 1; The Thermal Infrared Multispectral Scanner (TIMS) workshop, on October 27, whose summaries appear in Volume 2; and The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on October 28-29, whose summaries appear in this volume, Volume 3.
This publication is the first of three containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in this volume; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in Volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2.
This publication is the second volume of the summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop on January 23-24. The summaries for this workshop appear in Volume 1; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop on January 25-26. The summaries for this workshop appear in volume 3; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop on January 26. The summaries for this workshop appear in this volume.
This publication is the third containing summaries for the Fifth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on January 23-26, 1995. The main workshop is divided into three smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on January 23-24. The summaries for this workshop appear in Volume 1; (2) The Airborne synthetic Aperture Radar (AIRSAR) workshop, on January 25-26. The summaries for this workshop appear in this volume; and (3) The Thermal Infrared Multispectral Scanner (TIMS) workshop, on January 26. The summaries for this workshop appear in Volume 2.
When polygenic risk score (PRS) is derived from summary statistics, independence between discovery and test sets cannot be monitored. We compared two types of PRS studies derived from raw genetic data (denoted as rPRS) and the summary statistics for IGAP (sPRS). Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. sPRS without APOE is derived from International Genomics of Alzheimer’s Project (IGAP), which records ΔAUC and ΔR 2 of 0.051 ± 0.013 and 0.063 ± 0.015 for Alzheimer’s Disease Sequencing Project (ADSP) and 0.060 and 0.086 for Accelerating Medicine Partnership - Alzheimer’s Disease (AMP-AD). On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and test sets are 0.0036 ± 0.0027 (ΔAUC) and 0.0032 ± 0.0028 (ΔR 2 ). For height, ΔR 2 is 0.029 ± 0.0037. Considering the high heritability of hypertension and height of UK Biobank and sample size of UK Biobank, sPRS results from AD databases are inflated. Independence between discovery and test sets is a well-known basic requirement for PRS studies. However, a lot of PRS studies cannot follow such requirements because of impossible direct comparisons when using summary statistics. Thus, for sPRS, potential duplications should be carefully considered within the same ethnic group.
Developing daily duty cycle summaries for every vehicle-day within NLR’s Fleet DNA database was a key output of the FleetREDI project. This project captured second-by-second GPS and controller area network (CAN) data on in-use medium- and heavy-duty fleet vehicles and then summarized the data to provide an overview of vehicle operation throughout the United States. These data summaries were then displayed in aggregated formats on the FleetREDI dashboard, where users can explore the data within Fleet DNA. Fleet DNA’s clearinghouse of commercial fleet vehicle operating data helps vehicle manufacturers and developers optimize vehicle designs and helps fleet managers choose advanced technologies for their fleets. This online tool, which provides data summaries and visualizations similar to real-world "genetics" for medium- and heavy-duty fleet vehicles, helps users understand the broad operational range of commercial vehicles across vocations and weight classes.