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At least 37 records · Page 2

Software Process Assurance for Complex Electronics (SPACE)

Complex Electronics (CE) are now programmed to perform tasks that were previously handled in software, such as communication protocols. Many of the methods used to develop software bare a close resemblance to CE development. For instance, Field Programmable Gate Arrays (FPGAs) can have over a million logic gates while system-on-chip (SOC) devices can combine a microprocessor, input and output channels, and sometimes an FPGA for programmability. With this increased intricacy, the possibility of software-like bugs such as incorrect design, logic, and unexpected interactions within the logic is great. Since CE devices are obscuring the hardware/software boundary, we propose that mature software methodologies may be utilized with slight modifications in the development of these devices. Software Process Assurance for Complex Electronics (SPACE) is a research project that looks at using standardized S/W Assurance/Engineering practices to provide an assurance framework for development activities. Tools such as checklists, best practices and techniques can be used to detect missing requirements and bugs earlier in the development cycle creating a development process for CE that will be more easily maintained, consistent and configurable based on the device used.

Plastow, Richard A.↗

Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

Heroux, Michael A.↗

EOS MLS Level 1B Data Processing Software

This software is an improvement on Version 2, which was described in EOS MLS Level 1B Data Processing, Version 2.2, NASA Tech Briefs, Vol. 33, No. 5 (May 2009), p. 34. It accepts the EOS MLS Level 0 science/engineering data, and the EOS Aura spacecraft ephemeris/attitude data, and produces calibrated instrument radiances and associated engineering and diagnostic data. This version makes the code more robust, improves calibration, provides more diagnostics outputs, defines the Galactic core more finely, and fixes the equator crossing. The Level 1 processing software manages several different tasks. It qualifies each data quantity using instrument configuration and checksum data, as well as data transmission quality flags. Statistical tests are applied for data quality and reasonableness. The instrument engineering data (e.g., voltages, currents, temperatures, and encoder angles) is calibrated by the software, and the filter channel space reference measurements are interpolated onto the times of each limb measurement with the interpolates being differenced from the measurements. Filter channel calibration target measurements are interpolated onto the times of each limb measurement, and are used to compute radiometric gain. The total signal power is determined and analyzed by each digital autocorrelator spectrometer (DACS) during each data integration. The software converts each DACS data integration from an autocorrelation measurement in the time domain into a spectral measurement in the frequency domain, and estimates separately the spectrally, smoothly varying and spectrally averaged components of the limb port signal arising from antenna emission and scattering effects. Limb radiances are also calibrated.

Perun, Vincent S.↗

A communication channel model of the software process

Reported here is beginning research into a noisy communication channel analogy of software development process productivity, in order to establish quantifiable behavior and theoretical bounds. The analogy leads to a fundamental mathematical relationship between human productivity and the amount of information supplied by the developers, the capacity of the human channel for processing and transmitting information, the software product yield (object size), the work effort, requirements efficiency, tool and process efficiency, and programming environment advantage. Also derived is an upper bound to productivity that shows that software reuse is the only means than can lead to unbounded productivity growth; practical considerations of size and cost of reusable components may reduce this to a finite bound.

Tausworthe, R. C.↗

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗

Image-Processing Software For A Hypercube Computer

Concurrent Image Processing Executive (CIPE) is software system intended to develop and use image-processing application programs on concurrent computing environment. Designed to shield programmer from complexities of concurrent-system architecture, it provides interactive image-processing environment for end user. CIPE utilizes architectural characteristics of particular concurrent system to maximize efficiency while preserving architectural independence from user and programmer. CIPE runs on Mark-IIIfp 8-node hypercube computer and associated SUN-4 host computer.

Lee, Meemong↗

Future trends in image processing software and hardware

JPL image processing applications are examined, considering future trends in fields such as planetary exploration, electronics, astronomy, computers, and Landsat. Attention is given to adaptive search and interrogation of large image data bases, the display of multispectral imagery recorded in many spectral channels, merging data acquired by a variety of sensors, and developing custom large scale integrated chips for high speed intelligent image processing user stations and future pipeline production processors.

Green, W. B.↗

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗

A user's guide for the signal processing software for image and speech compression developed in the Communications and Signal Processing Laboratory (CSPL), version 1

A complete documentation of the software developed in the Communication and Signal Processing Laboratory (CSPL) during the period of July 1985 to March 1986 is provided. Utility programs and subroutines that were developed for a user-friendly image and speech processing environment are described. Additional programs for data compression of image and speech type signals are included. Also, programs for the zero-memory and block transform quantization in the presence of channel noise are described. Finally, several routines for simulating the perfromance of image compression algorithms are included.

Kumar, P.↗

Capturing a failure of an ASIC in-situ, using infrared radiometry and image processing software

Failures in electronic devices can sometimes be tricky to locate-especially if they are buried inside radiation-shielded containers designed to work in outer space. Such was the case with a malfunctioning ASIC (Application Specific Integrated Circuit) that was drawing excessive power at a specific temperature during temperature cycle testing. To analyze the failure, infrared radiometry (thermography) was used in combination with image processing software to locate precisely where the power was being dissipated at the moment the failure took place. The IR imaging software was used to make the image of the target and background, appear as unity. As testing proceeded and the failure mode was reached, temperature changes revealed the precise location of the fault. The results gave the design engineers the information they needed to fix the problem. This paper describes the techniques and equipment used to accomplish this failure analysis.

infrared↗

Capability Maturity Model (CMM) for Software Process Improvements

This slide presentation reviews the Avionic Systems Division's implementation of the Capability Maturity Model (CMM) for improvements in the software development process. The presentation reviews the process involved in implementing the model and the benefits of using CMM to improve the software development process.

Ling, Robert Y.↗

Product-oriented Software Certification Process for Software Synthesis

The purpose of this document is to propose a product-oriented software certification process to facilitate use of software synthesis and formal methods. Why is such a process needed? Currently, software is tested until deemed bug-free rather than proving that certain software properties exist. This approach has worked well in most cases, but unfortunately, deaths still occur due to software failure. Using formal methods (techniques from logic and discrete mathematics like set theory, automata theory and formal logic as opposed to continuous mathematics like calculus) and software synthesis, it is possible to reduce this risk by proving certain software properties. Additionally, software synthesis makes it possible to automate some phases of the traditional software development life cycle resulting in a more streamlined and accurate development process.

Nelson, Stacy↗

A method for tailoring the information content of a software process model

The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to set of accepted processes and products for achieving each criterion; (5) Select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5.

Perkins, Sharon↗

A method for tailoring the information content of a software process model

The framework is defined for a general method for selecting a necessary and sufficient subset of a general software life cycle's information products, to support new software development process. Procedures for characterizing problem domains in general and mapping to a tailored set of life cycle processes and products is presented. An overview of the method is shown using the following steps: (1) During the problem concept definition phase, perform standardized interviews and dialogs between developer and user, and between user and customer; (2) Generate a quality needs profile of the software to be developed, based on information gathered in step 1; (3) Translate the quality needs profile into a profile of quality criteria that must be met by the software to satisfy the quality needs; (4) Map the quality criteria to a set of accepted processes and products for achieving each criterion; (5) select the information products which match or support the accepted processes and product of step 4; and (6) Select the design methodology which produces the information products selected in step 5.

Perkins, Sharon↗

Ten steps to successful software process improvement

This paper identifies ten steps for managing change that address organizational and cultural issues. Four of these steps are critical, that if not done, will almost guarantee failure. This ten-step program emphasizes the alignment of business goals, change process goals, and the work performed by the employees of an organization.

software process improvement↗

Parallel-Processing Software for Correlating Stereo Images

A computer program implements parallel- processing algorithms for cor relating images of terrain acquired by stereoscopic pairs of digital stereo cameras on an exploratory robotic vehicle (e.g., a Mars rove r). Such correlations are used to create three-dimensional computatio nal models of the terrain for navigation. In this program, the scene viewed by the cameras is segmented into subimages. Each subimage is assigned to one of a number of central processing units (CPUs) opera ting simultaneously.

Klimeck, Gerhard↗

Solar Automated Permit Processing Software for Distributed PV (Cooperative Research and Development Final Report, CRADA Number CRD-19-00825)

NREL and its project partners built and commercialized the novel Solar Automated Permitting Processing Plus (SolarAPP+) software platform that delivers instant residential rooftop solar permits. The tool provides installers with a standard portal for entering permit information for residential solar systems across all Authorities Having Jurisdiction (AHJs) using SolarAPP+, thereby providing a streamlined plan review form, transparency into permitting timelines, and required specifications. The project has proven to reduce permitting timelines from as many as 20 business days to zero, delivering solar projects faster in the four participating AHJs using the platform. Streamlining permitting timelines, all else equal, results in consumers installing their systems and reducing their electricity bills faster. The continued expansion of SolarAPP+ features and adoption nationwide will expand the benefits of the SolarAPP+ beyond the current user base.

14 SOLAR ENERGY↗

Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

Beyon, Jeffrey Y.↗