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In developing a software system, we would like to estimate the total number of faults inserted into a software system, the residual fault content of that system at any given time, and the efficacy of the testing activity in executing the code containing the newly inserted faults.
Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following recent seismic events, including the Tohoku tsunami of March 11, 2011. We observe fluctuations correlated in time, space, and wave properties with this tsunami in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the Tohoku tsunami near the epicenter, at Hawaii, and near the west coast of North America. Disturbance magnitudes are 1-10% of the background TEC value. Observations near the epicenter are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement. The potential exists to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for future early warning systems.
Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following two recent seismic events: the American Samoa earthquake of September 29, 2009, and the Chile earthquake of February 27, 2010. Fluctuations in TEC correlated in time, space, and wave properties with these tsunamis were observed in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with wavelengths and periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the tsunamis in certain locations, but not in others. Where variations are observed, the typical amplitude tends to be on the order of 1% of the background TEC value. Variations with amplitudes ~ 0.1 - 0.2 TECU are observable with periods and timing affiliated with the tsunami. These observations are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement in some locations, though there are cases when the model predicts an observable tsunami-driven signature and none is observed. These TEC variations are not always seen when a tsunami is present, but in these two events the regions where a strong ocean tsunami was observed did coincide with clear TEC observations, while a lack of clear TEC observations coincided with smaller tsunami amplitudes. There exists the potential to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for early warning systems.
Approach developed to establish utility of pivotal functions for estimation and prediction of reliability of software. Improved estimates of reliability with statistical confidence obtained when relatively few testing data available. Pivotal functions effective tools for determination of confidence limits for reliability of software and prediction limits for time to next failure. Provides exact confidence and prediction limits regardless of how many bugs found in software.
The software measures and estimation techniques appropriate to a Commercial Off the Shelf (COTS) integration project differ from those commonly used for custom software development. Labor and schedule estimation tools that model COTS integration are available. Like all estimation tools, they must be calibrated with the organization's local project data. This paper describes the calibration of a commercial model using data collected by the Flight Dynamics Division (FDD) of the NASA Goddard Spaceflight Center (GSFC). The model calibrated is SLIM Release 4.0 from Quantitative Software Management (QSM). By adopting the SLIM reuse model and by treating configuration parameters as lines of code, we were able to establish a consistent calibration for COTS integration projects. The paper summarizes the metrics, the calibration process and results, and the validation of the calibration.
Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.
A computer program has been written as a unique implementation of an image-based wavefront-sensing algorithm reported in "Iterative-Transform Phase Retrieval Using Adaptive Diversity" (GSC-14879-1), NASA Tech Briefs, Vol. 31, No. 4 (April 2007), page 32. This software was originally intended for application to the James Webb Space Telescope, but is also applicable to other segmented-mirror telescopes. The software is capable of determining optical-wavefront information using, as input, a variable number of irradiance measurements collected in defocus planes about the best focal position. The software also uses input of the geometrical definition of the telescope exit pupil (otherwise denoted the pupil mask) to identify the locations of the segments of the primary telescope mirror. From the irradiance data and mask information, the software calculates an estimate of the optical wavefront (a measure of performance) of the telescope generally and across each primary mirror segment specifically. The software is capable of generating irradiance data, wavefront estimates, and basis functions for the full telescope and for each primary-mirror segment. Optionally, each of these pieces of information can be measured or computed outside of the software and incorporated during execution of the software.
There are no author-identified significant results in this report.
Method of estimating size and complexity of large computer program under development based on metric called "function mass." Simplification of Demarco's "function bang" metric. Size of completed program usually expressed in terms of number of lines of code (SLOC), shown in previous research to be highly correlated with amount of development effort and therefore important predictor of development cost. Proposed method of estimating ultimate size of program is intermediate product of continuing research on estimation of size and structured analysis of developmental software.
This viewgraph presentation reviews cost models to properly estimate the cost of software development.
Chemostat growth chambers measure optical density over time and require manual calculation of growth rates. Here, we present chemostat_regression, R software that enables users to automatically identify chemostat cycles and estimate growth rate using a linear regression approach. We describe steps for creating requisite software environment(s), formatting input data, executing the software via command line/RStudio/R-Shiny, interpreting results, assessing the validity of results, and modifying input parameters.
Aerodynamics and Performance Estimation Toolset is a collection of four software programs for rapidly estimating the preliminary design performance of aerospace vehicles represented by doing simplified calculations based on ballistic trajectories, the ideal rocket equation, and supersonic wedges through standard atmosphere. The program consists of a set of Microsoft Excel worksheet subprograms. The input and output data are presented in a user-friendly format, and calculations are performed rapidly enough that the user can iterate among different trajectories and/or shapes to perform "what-if" studies. Estimates that can be computed by these programs include: 1. Ballistic trajectories as a function of departure angles, initial velocities, initial positions, and target altitudes; assuming point masses and no atmosphere. The program plots the trajectory in two-dimensions and outputs the position, pitch, and velocity along the trajectory. 2. The "Rocket Equation" program calculates and plots the trade space for a vehicle s propellant mass fraction over a range of specific impulse and mission velocity values, propellant mass fractions as functions of specific impulses and velocities. 3. "Standard Atmosphere" will estimate the temperature, speed of sound, pressure, and air density as a function of altitude in a standard atmosphere, properties of a standard atmosphere as functions of altitude. 4. "Supersonic Wedges" will calculate the free-stream, normal-shock, oblique-shock, and isentropic flow properties for a wedge-shaped body flying supersonically through a standard atmosphere. It will also calculate the maximum angle for which a shock remains attached, and the minimum Mach number for which a shock becomes attached, all as functions of the wedge angle, altitude, and Mach number.
This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.
Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.
This paper presents a method of noncoherent demodulation of the PSK signal for signal distortion analysis at the RF interface. The received RF signal is downconverted and noncoherently sampled for further off-line processing. Any mismatch in phase and frequency is then compensated for by the software using the estimation techniques to extract the baseband waveform, which is needed in measuring various signal parameters. In this way, various kinds of modulated signals can be treated uniformly, independent of modulation format, and additional distortions introduced by the receiver or the hardware measurement instruments can thus be eliminated. Quantization errors incurred by digital sampling and ensuing software manipulations are analyzed and related numerical results are presented also.
Ground software systems at JPL must meet high assurance standards while remaining on schedule due to relatively immovable launch dates for spacecraft that will be controlled by such systems. Toward this end, the Software Quality Improvement (SQI) project's Measurement and Benchmarking (M&B) team is collecting and analyzing defect data of JPL ground system software projects to build software defect prediction models. The aim of these models is to improve predictability with regard to software quality activities. Predictive models will quantitatively define typical trends for JPL ground systems as well as Critical Discriminators (CDs) to provide explanations for atypical deviations from the norm at JPL. CDs are software characteristics that can be estimated or foreseen early in a software project's planning. Thus, these CDs will assist in planning for the predicted degree to which software quality activities for a project are likely to deviation from the normal JPL ground system based on pasted experience across the lab.
To assist rational investments in advanced software, a formal, explicit, and multi-perspective cost-benefit analysis methodology is proposed. The methodology can be implemented through a six-stage process which is described and explained. The current practice of cost-benefit analysis at KSC is reviewed in the light of this methodology. The review finds that there is a vicious circle operating. Unsound methods lead to unreliable cost-benefit estimates. Unreliable estimates convince management that cost-benefit studies should not be taken seriously. Then, given external demands for cost-benefit estimates, management encourages software enginees to somehow come up with the numbers for their projects. Lacking the expertise needed to do a proper study, courageous software engineers with vested interests use ad hoc and unsound methods to generate some estimates. In turn, these estimates are unreliable, and the cycle continues. The proposed methodology should help KSC to break out of this cycle.