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Assessing Eye Movement Scanpaths in Source Code Comprehension.
Abstract not provided.
Automatically Recognizing Semantics of List-based Data Structures in Source Code
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NST Middleware Enhancements for a Netcentric Simulation Architecture (MENSA)
The presentation outline includes source coding, channel coding, source and channel coding, results, and acknowledgements. Topics include: project description, in-lab demo of coding gain using swarm based platform, source coding algorithms, Huffman coding, Lempel-Ziv coding algorithm, channel coding, LT codes, source and channel coding, MENSA beta code in an unofficial TENA library, and Wireshark tool.
ONIX: An open-source depletion code
Open Source software enables innovative, community-based software development. ONIX brings this concept to the field of depletion calculations. It is an open-source depletion software to be used for nuclear reactor simulations, for fissile material production analysis as well as for nuclear arms control applications. ONIX provides a module to solve the depletion equation using a Chebyshev Rational Approximation Method. For the generation of one-group cross sections, it includes a coupling interface for the open-source neutron transport code, OpenMC, as well as a module to read pre-computed values in a stand-alone mode. ONIX has special features to optimize nuclear data libraries, to update isomeric branching ratio during burnup, and to support automation of simulations for nuclear archaeology. In conclusion, ONIX has been validated against results from numerical and experimental benchmarks, and its results agree with other methods within expected error ranges.
Deep space communications technology thrusts
The paper discusses the technology thrusts that are currently being developed for deep space missions as well as the expected dividends of these thrusts during the 1990's and beyond. Particular attention is given to Ka-band (32 GHz) development, channel coding, source coding, and optical communications. The ongoing development described here attempts to meet the telecommunications demands of future missions by stressing cooperative developments between ground networks and flight projects in order to optimize NASA's overall investment in solar system investment.
ROSE Compiler Framework
The purpose of the ROSE Complier Framework Is to automate source code porting, source and binary code analysis, and source code translations such as platform optimization, binary code analysis, Identification of source code and binary code vulnerablllttes.
Orbital flight simulation utility software unit specifications, revision 1
The HP PASCAL source code defines the specifications for a Utility Software Unit (USU) designed to support orbital flight simulators such as MANHANDLE and GREAS (General Research and Engineering Analysis Simulator). Besides providing basic input/output, mathematical, matrix, quaternion, and statistical routines for such simulators, one of the primary functions of the USU is to isolate all system-dependent codes in one well-defined compartment, thereby facilitating transportation of the simulations from one computer to another. Directives are given for the PASCAL compilers of the HP-9000 Series 200 Pascal 3.0 and the HP-9000 Series 500 HP-UX 5.0 operating systems that produce a single file of relocatable code from four separate files of source code. Three of the source code files are common to both operating systems. The fourth source code file (utilspif.I) contains all of the system-dependent PASCAL code for the USU. A fifth file of source code written in C is required to interface utilspif.I with the HP-UX I/O package. The Pascal 3.0 compiler directives and the driver source code for a unit rest program and counterparts for the HP-UX 5.0 operating system are given. The major portion of the unit test program source code is common to both operating systems. Unit test results from the Pascal 3.0 operating system and results from the HP-UX operating system are given.
Coded aperture imaging of X-ray and gamma-ray sources
Coded aperture telescopes employing arrays of a small number of discrete detector elements for hard X-rays or gamma-rays are discussed. Aperture patterns are described that permit a unique reconstruction of the image with high contrast, and that exhibit a specific rotational antisymmetry to suppress systematic distortions. It is shown that high flux sensitivity can be achieved in this fashion as well as good angular resolution.
An algorithmic code for monotonic sources
Algorithmic code for information source that emits only monotonic strings of characters
Applying Standard Interfaces to a Process-Control Language
A method of applying open-operating-system standard interfaces to the NASA User Interface Language (UIL) has been devised. UIL is a computing language that can be used in monitoring and controlling automated processes: for example, the Timeliner computer program, written in UIL, is a general-purpose software system for monitoring and controlling sequences of automated tasks in a target system. In providing the major elements of connectivity between UIL and the target system, the present method offers advantages over the prior method. Most notably, unlike in the prior method, the software description of the target system can be made independent of the applicable compiler software and need not be linked to the applicable executable compiler image. Also unlike in the prior method, it is not necessary to recompile the source code and relink the source code to a new executable compiler image. Abstraction of the description of the target system to a data file can be defined easily, with intuitive syntax, and knowledge of the source-code language is not needed for the definition.
Automated Concurrent Blackboard System Generation in C++
In his 1992 Ph.D. thesis, "Design and Analysis Techniques for Concurrent Blackboard Systems", John McManus defined several performance metrics for concurrent blackboard systems and developed a suite of tools for creating and analyzing such systems. These tools allow a user to analyze a concurrent blackboard system design and predict the performance of the system before any code is written. The design can be modified until simulated performance is satisfactory. Then, the code generator can be invoked to generate automatically all of the code required for the concurrent blackboard system except for the code implementing the functionality of each knowledge source. We have completed the port of the source code generator and a simulator for a concurrent blackboard system. The source code generator generates the necessary C++ source code to implement the concurrent blackboard system using Parallel Virtual Machine (PVM) running on a heterogeneous network of UNIX(trademark) workstations. The concurrent blackboard simulator uses the blackboard specification file to predict the performance of the concurrent blackboard design. The only part of the source code for the concurrent blackboard system that the user must supply is the code implementing the functionality of the knowledge sources.
NREL's REopt Lite Tool - Open Source
REopt Lite can be accessed via the web tool, application programming interface (API), or open source code. The open source code allows users to add custom features and capabilities.
Performance and Architecture Lab Modeling Tool
Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this link makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.
Data compression for satellite images
An efficient data compression system is presented for satellite pictures and two grey level pictures derived from satellite pictures. The compression techniques take advantages of the correlation between adjacent picture elements. Several source coding methods are investigated. Double delta coding is presented and shown to be the most efficient. Both predictive differential quantizing technique and double delta coding can be significantly improved by applying a background skipping technique. An extension code is constructed. This code requires very little storage space and operates efficiently. Simulation results are presented for various coding schemes and source codes.
Permutation codes for sources.
Source encoding techniques based on permutation codes are investigated. For a broad class of distortion measures it is shown that optimum encoding of a source permutation code is easy to instrument even for very long block lengths. Also, the nonparametric nature of permutation encoding is well suited to situations involving unknown source statistics. For the squared-error distortion measure a procedure for generating good permutation codes of a given rate and block length is described. The performance of such codes for a memoryless Gaussian source is compared both with the rate-distortion function bound and with the performance of various quantization schemes. The comparison reveals that permutation codes are asymptotically ideal for small rates and perform as well as the best entropy-coded quantizers presently known for intermediate rates. They can be made to compare favorably at high rates, too, provided the coding delay associated with extremely long block lengths is tolerable.
DMTN-312: The MultiProFit astronomical source modelling code
This note describes the MultiProFit astronomical source modelling code, and particularly its development and use for modelling coadded objects in the LSST Science Pipelines.
Parallel sorting algorithm classification: is manual instrumentation necessary?
Understanding parallel algorithms is crucial for accelerating scientific simulations on complex, distributed memory, high-performance computers. Modern algorithm classification approaches learn semantics directly from source code to differentiate between algorithms, however, accessing source code is not always possible. We can learn about parallel algorithms from observing their performance, as programs running the same algorithms and using the same hardware should exhibit similar performance characteristics. We present an approach to learn algorithm classes from parallel performance data directly in order to classify algorithms without access to the source code. We extend previous work to enable classifying parallel sorting algorithms using automatic instrumentation instead of requiring manual region annotations in the source code. In this work, we design and demonstrate a study for classification of parallel sorting algorithms using parallel performance data collected from automatic instrumentation, and evaluate the performance of our new methodology on classification. We leverage Caliper to collect the performance data, Thicket for our exploratory data analysis (EDA), and PyTorch and Scikit-learn to evaluate the effectiveness of random forests, support vector machines (SVMs), decision trees, neural networks, and logistic regressions on parallel performance data. Additionally, we study noise in parallel performance data, whether the removal of noise and pre-processing of the data is necessary to accurately classify parallel sorting algorithms, and determine the effectiveness of features created from performance data. In conclusion, we demonstrate classification accuracy for these five different models of up to 97.7% across four different parallel algorithm classes.