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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Semantic Metrics for Object Oriented Design

The purpose of this proposal is to research a new suite of object-oriented (OO) software metrics, called semantic metrics, that have the potential to help software engineers identify fragile, low quality code sections much earlier in the development cycle than is possible with traditional OO metrics. With earlier and better Fault detection, software maintenance will be less time consuming and expensive, and software reusability will be improved. Because it is less costly to correct faults found earlier than to correct faults found later in the software lifecycle, the overall cost of software development will be reduced. Semantic metrics can be derived from the knowledge base of a program understanding system. A program understanding system is designed to understand a software module. Once understanding is complete, the knowledge-base contains digested information about the software module. Various semantic metrics can be collected on the knowledge base. This new kind of metric measures domain complexity, or the relationship of the software to its application domain, rather than implementation complexity, which is what traditional software metrics measure. A semantic metric will thus map much more closely to qualities humans are interested in, such as cohesion and maintainability, than is possible using traditional metrics, that are calculated using only syntactic aspects of software.

Etzkorn, Lethe↗
NASA NTRS2019

NASA EOSDIS Data Usage Metrics- Insight and Assessment

NASA's Earth Science Data and Information System (ESDIS) Project collects Earth science data usage metrics on a daily basis through the ESDIS Metrics System (EMS). This includes metrics on distribution of data products, users, data volumes, and number of files, which are key parameters in evaluating system-level performance of any of the Distributed Active Archive Centers (DAACs) encompassed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS). EOSDIS data usage metrics illustrate the benefits of making NASA data openly available to the public and show a rapid growth in data distribution to a worldwide user community. In fact, each year since 2014 the EOSDIS has distributed over one billion data files of products from EOS satellite, airborne, and in situ observations. An assessment of the long-term trends of data usage metrics and user characterization provides insights into data usability.This study will focus on describing the EMS as a metrics collection tool and will provide a comprehensive analysis of EOSDIS data usage metrics over the last 10 years. This study will also characterize the product distribution metrics by various tools and services, such as Giovanni, the Open-source Project for a Network Data Access Protocol (OPeNDAP), and subsets, to address how these tools/services have extended the usage of data in the EOSDIS collection. Data usage patterns based on discipline and study area will further assist in understanding how EOSDIS data user needs have evolved over time. Results from this study will provide useful information for the DAACs that can help them improve the functionality of their tools and services as well as more efficiently allocate the resources necessary for enhanced access and availability of their data products. Knowledge of these metrics may also benefit user discovery of data in the EOSDIS collection, promote research collaboration, and stimulate new ideas from work and research conducted using specific datasets and data collections.

Kafle, Durga N.↗
NASA NTRS2019

Integrated Analysis of Multiple User Metrics - A “Sequel”; and Introducing the Google Analytic

For decades, the Goddard Earth Sciences Data and Information Services Center (GES DISC) has archived and distributed enormous volumes of NASA Earth science data (accompanied with many developed tools and services) to various research/applications communities and the general public. Being “immersed” in the Big Data era, we have inevitably faced the challenges of our continually increasing archived data in both volume and variety, as well as enhanced user needs and demands. In recent years, we have actively analyzed different types of user metrics, such as operational distribution metrics (recording numbers of distinct users and downloaded data files, size of distributed data volume): user publication metrics (mining info from our Giovanni users’ publications): and Bugzilla metrics (collecting info from user questions or feedback from user assistance tickets). Such metrics have helped us achieve a better understanding of user needs, demands, characteristics, and behaviors, which has then helped us improve our user services. Now we will present a “Sequel” of integrated analysis of multiple metrics at the GES DISC by introducing and adding one new kind of metrics acquired via utilizing our recently implemented Google Analytic 360 suite. Several “newer” reports, e.g., “What web site features and links are the most popular (and least)?” and “What are the top 25 dataset Keyword searches?” retrieved from this new metrics set will be presented, along with the aforementioned “traditional” metrics results.

Shie, Chung-Lin↗
NASA NTRSDate not supplied

Estimating Sonic Boom Metrics Across a Community Using a Kalman Filter

As part of the Quesst mission, NASA will fly the X‑59 aircraft over selected communities to evaluate community responses to low-intensity sonic booms. The purpose of these community tests is to determine the dose-response relationship between the noise exposure metrics and the community response. The independent variables for the dose-response relationship are the noise exposure metrics experienced by survey respondents within the community. Two sources of noise exposure metrics are available in each community: measurements at sparse locations throughout the community, and calculations from propagation models across the community. Both the measurements and calculations are subject to uncertainty. A Kalman filter is proposed to combine the measured and calculated noise exposure metrics to obtain the best estimate of the true noise exposure metrics across the community. The noise exposure metrics estimated by the Kalman filter have lower uncertainty than either the measured or calculated noise exposure metrics alone. Simulations demonstrate that the Kalman filter produces a more accurate estimate of the true noise exposure metrics than other noise estimation methods.

Sonic boom↗
DOE OSTI2025

Are light curve classification metrics good proxies for SN Ia cosmological constraining power?

Context. When selecting a light curve classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process. Aims. This study tests the assumption that light curve classification metrics are an appropriate proxy for cosmology metrics. Methods. We emulated photometric SN Ia cosmology light curve samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates. Results. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter. Conclusions. Based on these findings, we discourage any exclusive reliance on light curve classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Advanced Life Support System Value Metric

The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have led to the following approach. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are considered to be exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is defined after many trade-offs. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, SVM/[ESM + function (TRL)], with appropriate weighting and scaling. The total value is given by SVM. Cost is represented by higher ESM and lower TRL. The paper provides a detailed description and example application of a suggested System Value Metric and an overall ALS system metric.

Jones, Harry W.↗
NASA NTRS2009

A Complexity Metric for Automated Separation

A metric is proposed to characterize airspace complexity with respect to an automated separation assurance function. The Maneuver Option metric is a function of the number of conflict-free trajectory change options the automated separation assurance function is able to identify for each aircraft in the airspace at a given time. By aggregating the metric for all aircraft in a region of airspace, a measure of the instantaneous complexity of the airspace is produced. A six-hour simulation of Fort Worth Center air traffic was conducted to assess the metric. Results showed aircraft were twice as likely to be constrained in the vertical dimension than the horizontal one. By application of this metric, situations found to be most complex were those where level overflights and descending arrivals passed through or merged into an arrival stream. The metric identified high complexity regions that correlate well with current air traffic control operations. The Maneuver Option metric did not correlate with traffic count alone, a result consistent with complexity metrics for human-controlled airspace.

Aweiss, Arwa↗
NASA NTRS2018

Comparison of Several Global Mixing Performance Metrics for High-Speed Fuel Injectors

To experimentally assess and compare the mixing performance of high-speed fuel injectors for scramjet engines, quantitative global metrics are needed. The one-dimensional metric most commonly used to assess the degree of mixing completeness at a given downstream station is the mixing efficiency parameter. The experimental determination of the mixing efficiency parameter requires measurement of the spatial distributions of both the fuel mass fraction and the mass flux. Standard in-stream gas sampling techniques can be used to measure the fuel mass fraction distribution, however the mass flux distribution is not easily determined experimentally because it requires the measurement of three independent aerothermodynamic variables in addition to the mixture composition. For this reason, several metrics that can be calculated from the fuel distribution alone are commonly used to assess mixing performance. Because these other metrics do not provide a mass flux-weighted measure of the local degree of mixing completeness, they may not correlate well with the mixing efficiency parameter. Therefore, if the substitute metrics are to be used to compare the mixing performance of candidate fuel injector concepts, it is important to understand their relationships to the mixing efficiency parameter in a representative scramjet combustor flowfield. This work investigates the relationships between the mixing efficiency parameter and several substitute metrics that are able to be measured with the current experimental setup of the Enhanced Injection and Mixing Project at the NASA Langley Research Center for baseline strut and ramp injectors. The results of these comparisons have revealed that it is possible to glean different (i.e., incorrect) conclusions about which injector is the better mixer when the substitute mixing performance metrics are used instead of the mixing efficiency parameter, thereby highlighting the importance of mass flux-weighted mixing performance metrics.

Ground, Cody R.↗
DOE OSTI2024

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NLR HPC Eagle GPU Node Metrics

Ganglia node metrics and iLO (Integrated Lights Out) power data captured from six representative Eagle GPU nodes The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a representative sample of metrics for 6 of the GPU nodes. Each GPU node contained 2 CPUs and 2 GPUs. Data provided in compressed CSV format. Ganglia and iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 mt: Metric (only present for Ganglia) vl: Value - Value in watts for iLO power (instantaneous value at sampling time) or specified Ganglia metric below Ganglia Metrics Metric name -- Metric description -- Unit cpu_aidle -- Percent of time since boot idle CPU -- Percent cpu_idle -- Percent CPU idle -- Percent cpu_nice -- Percent CPU nice -- Percent cpu_speed -- Speed in MHz of CPU -- MHz cpu_user -- Percent CPU user -- Percent cpu_wio -- The percentage of CPU Wait I/O -- Percent gpu0_bar1_memory -- Used GPU bar1 memory -- MB gpu0_decoder_util -- GPU decoder utilization -- Percent gpu0_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu0_encoder_util -- GPU encoder utilization -- Percent gpu0_fan -- Fan speed -- RPM gpu0_fb_memory -- Used GPU framebuffer memory -- MB gpu0_graphics_clock_report -- Current clock speeds for the device -- MHz gpu0_mem_total -- Memory total -- MB gpu0_mem_util -- Memory utilization -- Percent gpu0_power_usage_report -- Power usage report -- Watts gpu0_temp -- GPU 1 temperature -- Celsius gpu1_bar1_memory -- Used GPU bar1 memory -- MB gpu1_decoder_util -- GPU decoder utilization -- Percent gpu1_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu1_encoder_util -- GPU encoder utilization -- Percent gpu1_fan -- Fan speed -- RPM gpu1_fb_memory -- Used GPU framebuffer memory -- MB gpu1_graphics_clock_report -- Current clock speeds for the GPU -- MHz gpu1_mem_total -- Memory total -- MB gpu1_mem_util -- Memory utilization -- MB gpu1_power_usage_report -- Power usage report -- Watts gpu1_temp -- GPU 1 temperature -- Celsius ipmi_cpu1_temp -- CPU 1 temperature -- Celsius ipmi_cpu2_temp -- CPU 2 temperature -- Celsius ipmi_inlet_ambient_temp -- Temperature measured at intake -- Celsius ipmi_vr_p1_temp -- CPU 1 voltage regulator temperature -- Celsius ipmi_vr_p2_temp -- CPU 2 voltage regulator temperature -- Celsius mem_buffers -- Amount of buffered memory -- Bytes mem_cached -- Amount of cached memory -- Bytes mem_free -- Amount of available memory -- Bytes mem_shared -- Amount of shared memory -- Bytes mem_total -- Amount of available memory -- Bytes

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Performance of a normalized energy metric without jammer state information for an FH/MFSK system in worst case partial band jamming

For a frequency-hopped noncoherent MFSK communication system without jammer state information (JSI) in a worst case partial band jamming environment, it is well known that the use of a conventional unquantized metric results in very poor performance. In this paper, a 'normalized' unquantized energy metric is suggested for such a system. It is shown that with this metric, one can save 2-3 dB in required signal energy over the system with hard decision metric without JSI for the same desired performance. When this very robust metric is compared to the conventional unquantized energy metric with JSI, the loss in required signal energy is shown to be small. Thus, the use of this normalized metric provides performance comparable to systems for which JSI is known. Cutoff rate and bit error rate with dual-k coding are used for the performance measures.

Lee, P. J.↗
NASA NTRS1990

Fighter agility metrics

Fighter flying qualities and combat capabilities are currently measured and compared in terms relating to vehicle energy, angular rates and sustained acceleration. Criteria based on these measurable quantities have evolved over the past several decades and are routinely used to design aircraft structures, aerodynamics, propulsion and control systems. While these criteria, or metrics, have the advantage of being well understood, easily verified and repeatable during test, they tend to measure the steady state capability of the aircraft and not its ability to transition quickly from one state to another. Proposed new metrics to assess fighter aircraft agility are collected and analyzed. A framework for classification of these new agility metrics is developed and applied. A complete set of transient agility metrics is evaluated with a high fidelity, nonlinear F-18 simulation. Test techniques and data reduction methods are proposed. A method of providing cuing information to the pilot during flight test is discussed. The sensitivity of longitudinal and lateral agility metrics to deviations from the pilot cues is studied in detail. The metrics are shown to be largely insensitive to reasonable deviations from the nominal test pilot commands. Instrumentation required to quantify agility via flight test is also considered. With one exception, each of the proposed new metrics may be measured with instrumentation currently available.

Liefer, Randall K.↗
NASA NTRS1991

Metrication report to the Congress. 1991 activities and 1992 plans

During 1991, NASA approved a revised metric use policy and developed a NASA Metric Transition Plan. This Plan targets the end of 1995 for completion of NASA's metric initiatives. This Plan also identifies future programs that NASA anticipates will use the metric system of measurement. Field installations began metric transition studies in 1991 and will complete them in 1992. Half of NASA's Space Shuttle payloads for 1991, and almost all such payloads for 1992, have some metric-based elements. In 1992, NASA will begin assessing requirements for space-quality piece parts fabricated to U.S. metric standards, leading to development and qualification of high priority parts.

Source record↗
NASA NTRS1993

Software metrics: The key to quality software on the NCC project

Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.

Burns, Patricia J.↗
NASA NTRS1999

Advanced Life Support System Value Metric

The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have reached a consensus. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is then set accordingly. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, [SVM + TRL]/ESM, with appropriate weighting and scaling. The total value is the sum of SVM and TRL. Cost is represented by ESM. The paper provides a detailed description and example application of the suggested System Value Metric.

Jones, Harry W.↗
NASA NTRS1991

A Dynamic Testing Complexity Metric

This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

Voas, Jeffrey↗
NASA NTRS2004

Advanced Life Support Research and Technology Development Metric: Fiscal Year 2003

This document provides the official calculation of the Advanced Life Support (ALS) Research and Technology Development Metric (the Metric) for Fiscal Year 2003. As such, the values herein are primarily based on Systems Integration, Modeling, and Analysis (SIMA) Element approved software tools or reviewed and approved reference documents. The Metric is one of several measures employed by the National Aeronautics and Space Administration (NASA) to assess the Agency s progress as mandated by the United States Congress and the Office of Management and Budget. Because any measure must have a reference point, whether explicitly defined or implied, the Metric is a comparison between a selected ALS Project life support system and an equivalently detailed life support system using technology from the Environmental Control and Life Support System (ECLSS) for the International Space Station (ISS). More specifically, the Metric is the ratio defined by the equivalent system mass (ESM) of a life support system for a specific mission using the ISS ECLSS technologies divided by the ESM for an equivalent life support system using the best ALS technologies. As defined, the Metric should increase in value as the ALS technologies become lighter, less power intensive, and require less volume. For Fiscal Year 2003, the Advanced Life Support Research and Technology Development Metric value is 1.47 for an Orbiting Research Facility and 1.36 for an Independent Exploration Mission.

Hanford, A. J.↗
NASA NTRS2014

Launch Vehicle Production and Operations Cost Metrics

Traditionally, launch vehicle cost has been evaluated based on $/Kg to orbit. This metric is calculated based on assumptions not typically met by a specific mission. These assumptions include the specified orbit whether Low Earth Orbit (LEO), Geostationary Earth Orbit (GEO), or both. The metric also assumes the payload utilizes the full lift mass of the launch vehicle, which is rarely true even with secondary payloads.1,2,3 Other approaches for cost metrics have been evaluated including unit cost of the launch vehicle and an approach to consider the full program production and operations costs.4 Unit cost considers the variable cost of the vehicle and the definition of variable costs are discussed. The full program production and operation costs include both the variable costs and the manufacturing base. This metric also distinguishes operations costs from production costs, including pre-flight operational testing. Operations costs also consider the costs of flight operations, including control center operation and maintenance. Each of these 3 cost metrics show different sensitivities to various aspects of launch vehicle cost drivers. The comparison of these metrics provides the strengths and weaknesses of each yielding an assessment useful for cost metric selection for launch vehicle programs.

Watson, Michael D.↗