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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Pragmatic quality metrics for evolutionary software development models

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

Royce, Walker↗
NASA NTRS1988

Modernization of software quality assurance

The customers satisfaction depends not only on functional performance, it also depends on the quality characteristics of the software products. An examination of this quality aspect of software products will provide a clear, well defined framework for quality assurance functions, which improve the life-cycle activities of software development. Software developers must be aware of the following aspects which have been expressed by many quality experts: quality cannot be added on; the level of quality built into a program is a function of the quality attributes employed during the development process; and finally, quality must be managed. These concepts have guided our development of the following definition for a Software Quality Assurance function: Software Quality Assurance is a formal, planned approach of actions designed to evaluate the degree of an identifiable set of quality attributes present in all software systems and their products. This paper is an explanation of how this definition was developed and how it is used.

Bhaumik, Gokul↗
NASA NTRS1966

New developments in NASA quality assurance

The purpose of this talk is to examine and discuss NASA's basic quality concept, the policy and procedures which define and implement this concept and subsequently explore the NASA-Industry quality relationships which are essential to the success of NASA's quality assurance concept. It is important to emphasize that NASA's Quality Assurance program is predicated on the concept of an individually tailored quality program for each significant NASA procurement - particularly, large space systems. As a result, NASA's Quality Assurance program - to be effective - must be responsive to various technologies, hardware systems, and space missions. In addition, the program must be responsive to changing policies and practices in research, engineering and procurement. Key issues in the NASA-Contractor quality relationships in the framework of an over all NASA-Industry partnership include: (1) the necessity for NASA to effectively discharge its responsibility for providing clear and complete definition of quality requirements at all phases of the procurement cycle; (2) the right of the contractor to expect an explicit definition of NASA quality requirements in each RFP and contract and to request same if it is not provided; (3) the necessity for the contractor to have a dynamic and responsive quality program which is directed towards assuring that the hardware meets all technical requirements and to accomplish this in an effective and efficient manner; and (4) the critical need for investigation and study of the economic aspects of quality and an evaluation of our policies and practices based upon the results of such a study.

Condon, John E.↗
NASA NTRS2016

ESIP Information Quality Cluster (IQC)

The Information Quality Cluster (IQC) within the Federation of Earth Science Information Partners (ESIP) was initially formed in 2011 and has evolved significantly over time. The current objectives of the IQC are to: 1. Actively evaluate community data quality best practices and standards; 2. Improve capture, description, discovery, and usability of information about data quality in Earth science data products; 3. Ensure producers of data products are aware of standards and best practices for conveying data quality, and data providers distributors intermediaries establish, improve and evolve mechanisms to assist users in discovering and understanding data quality information; and 4. Consistently provide guidance to data managers and stewards on how best to implement data quality standards and best practices to ensure and improve maturity of their data products. The activities of the IQC include: 1. Identification of additional needs for consistently capturing, describing, and conveying quality information through use case studies with broad and diverse applications; 2. Establishing and providing community-wide guidance on roles and responsibilities of key players and stakeholders including users and management; 3. Prototyping of conveying quality information to users in a more consistent, transparent, and digestible manner; 4. Establishing a baseline of standards and best practices for data quality; 5. Evaluating recommendations from NASA's DQWG in a broader context and proposing possible implementations; and 6. Engaging data providers, data managers, and data user communities as resources to improve our standards and best practices. Following the principles of openness of the ESIP Federation, IQC invites all individuals interested in improving capture, description, discovery, and usability of information about data quality in Earth science data products to participate in its activities.

data products↗
NASA NTRSDate not supplied

Data Quality Challenges for Analysis Ready Data (ARD)

Data quality plays a critical role in research and applications. The Earth Science Information Partners (ESIP) Information Quality Cluster (IQC) defines four aspects of information quality: Science, Product, Stewardship, and Services. The ESIP IQC has become internationally recognized as an authoritative and responsive resource of information and guidance to data producers and distributors on how to implement data quality standards and best practices for their science data systems, datasets, and data/metadata dissemination services. In recent years, cloud computing environments have provided scale-up capabilities such as data archives and services, enabling interdisciplinary science and applications. More value-added products are expected from data service providers, including Analysis Ready Data (ARD). ARD refers to data that has been preprocessed into a form that allows immediate analysis by the end user, processed to a minimum set of requirements and provides interoperability over time and across multiple datasets. Once a dataset has been developed from its original form to produce ARD, what quality characteristics should the derived dataset or ARD possess? Also, is it safe to assume that the quality of the ARD is consistent with the quality of the source data, or are there special attributes to an ARD that would warrant a secondary, independent quality assessment? What provenance (also called “data lineage”) information needs to be included in ARD? It is important to answer these questions, especially given the ease of use of ARD, and the consequent temptation by users to trust ARD without understanding the limitations or possible variations in quality compared to the source data. In this presentation, we will discuss data quality challenges for ARD products and services and introduce IQC for participation.

data quality↗
NASA NTRS1998

The UNO Aviation Monograph Series: The Airline Quality Rating 1998

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline performance on combined multiple factors important to consumers. Development history and calculation details for the AQR rating system are detailed in The Airline Quality Rating 1991 issued in April, 1991, by the National Institute for Aviation Research at Wichita State University. This current report, Airline Quality Rating 1998, contains monthly Airline Quality Rating scores for 1997. Additional copies are available by contacting Wichita State University or University of Nebraska at Omaha. The Airline Quality Rating 1998 is a summary of month-by-month quality ratings for the ten major U.S. airlines operating during 1997. Using the Airline Quality Rating system and monthly performance data for each airline for the calendar year of 1997, individual and comparative ratings are reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for major airlines domestic operations for the 12 month period of 1997, and industry average results. Also, comparative Airline Quality Rating data for 1991 through 1996 are included to provide a longer term view of quality in the industry.

Bowen, Brent D.↗
NASA NTRS2001

The Airline Quality Rating 2001

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, Airline Quality Rating 2001, reflects monthly Airline Quality Rating scores for 2000. AQR scores for the calendar year 2000 are based on 15 elements that focus on airline performance areas important to air travel consumers. The Airline Quality Rating 2001 is a summary of month-by-month quality ratings for the ten major U.S. airlines operating during 2000. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, major airlines comparative performance for the calendar year of 2000 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for major airlines domestic operations for the 12 month period of 2000, and industry average results. Also, comparative Airline Quality Rating data for 1999 are included for each airline to provide historical perspective regarding performance quality in the industry.

Bowen, Brent D.↗
NASA NTRS2002

The Airline Quality Rating 2002

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, Airline Quality Rating 2002, reflects monthly Airline Quality Rating scores for 2001. AQR scores for the calendar year 2001 are based on 15 elements that focus on airline performance areas important to air travel consumers. The Airline Quality Rating 2002 is a summary of month-by-month quality ratings for the 11 largest U.S. airlines operating during 2001. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, airlines comparative performance for the calendar year of 2001 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for domestic airline operations for the 12-month period of 2001, and industry average results. Also, comparative Airline Quality Rating data for 2000 are included for each airline to provide historical perspective regarding performance quality in the industry.

Bowen, Brent D.↗
NASA NTRS2003

The Airline Quality Rating 2003

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, the Airline Quality Rating 2003, reflects monthly Airline Quality Rating scores for 2002. AQR scores for the calendar year 2002 are based on 15 elements that focus on airline performance areas important to air travel consumers. The Airline Quality Rating 2003 is a summary of month-by-month quality ratings for the 10 largest U.S. airlines operating during 2002. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of ontime arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, airlines comparative performance for the calendar year of 2002 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for domestic airline operations for the 12-month period of 2002, and industry average results. Also, comparative Airline Quality Rating data for 2001 are included for each airline to provide historical perspective regarding performance quality in the industry.

Bowen, Brent D.↗
NASA NTRS2004

The Airline Quality Rating 2004

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, the Airline Quality Rating 2004, reflects monthly Airline Quality Rating scores for 2003. AQR scores for the calendar year 2003 are based on 15 elements in four major areas that focus on airline performance aspects important to air travel consumers. The Airline Quality Rating 2004 is a summary of month-by-month quality ratings for U.S. airlines that have at least 1 % of domestic passenger volume during 2003. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, airlines comparative performance for the calendar year of 2003 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for domestic airline operations for the 12-month period of 2003, and industry results. Also, comparative Airline Quality Rating data for 2002 are included, where available, to provide historical perspective regarding performance quality in the industry.

Fink, Mary M.↗
NASA NTRS1990

Taguchi Approach to Design Optimization for Quality and Cost: An Overview

Calibrations to existing cost of doing business in space indicate that to establish human presence on the Moon and Mars with the Space Exploration Initiative (SEI) will require resources, felt by many, to be more than the national budget can afford. In order for SEI to succeed, we must actually design and build space systems at lower cost this time, even with tremendous increases in quality and performance requirements, such as extremely high reliability. This implies that both government and industry must change the way they do business. Therefore, new philosophy and technology must be employed to design and produce reliable, high quality space systems at low cost. In recognizing the need to reduce cost and improve quality and productivity, Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) have initiated Total Quality Management (TQM). TQM is a revolutionary management strategy in quality assurance and cost reduction. TQM requires complete management commitment, employee involvement, and use of statistical tools. The quality engineering methods of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high quality systems at reduced cost. Taguchi methods provide an efficient and systematic way to optimize designs for performance, quality, and cost. Taguchi methods have been used successfully in Japan and the United States in designing reliable, high quality products at low cost in such areas as automobiles and consumer electronics. However, these methods are just beginning to see application in the aerospace industry. The purpose of this paper is to present an overview of the Taguchi methods for improving quality and reducing cost, describe the current state of applications and its role in identifying cost sensitive design parameters.

Unal, Resit↗
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS1991

A multiple objective optimization approach to quality control

The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios: tuning of process controllers to meet specified performance objectives and tuning of process inputs to meet specified quality objectives. Five case studies are presented.

Seaman, Christopher Michael↗
NASA NTRS1993

The impact of flying qualities on helicopter operational agility

Flying qualities standards are formally set to ensure safe flight and therefore reflect minimum, rather than optimum, requirements. Agility is a flying quality but relates to operations at high, if not maximum, performance. While the quality metrics and test procedures for flying, as covered for example in ADS33C, may provide an adequate structure to encompass agility, they do not currently address flight at high performance. This is also true in the fixed-wing world and a current concern in both communities is the absence of substantiated agility criteria and possible conflicts between flying qualities and high performance. AGARD is sponsoring a working group (WG19) title 'Operational Agility' that deals with these and a range of related issues. This paper is condensed from contributions by the three authors to WG19, relating to flying qualities. Novel perspectives on the subject are presented including the agility factor, that quantifies performance margins in flying qualities terms; a new parameter, based on maneuver acceleration is introduced as a potential candidate for defining upper limits to flying qualities. Finally, a probabilistic analysis of pilot handling qualities ratings is presented that suggests a powerful relationship between inherent airframe flying qualities and operational agility.

Padfield, Gareth D.↗
NASA NTRS1997

The UNO Aviation Monograph Series: The Airline Quality Rating 1997

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline performance on combined multiple factors important to consumers. Development history and calculation details for the AQR rating system are detailed in The Airline Quality Rating 1991 issued in April, 1991, by the National Institute for Aviation Research at Wichita State University. This current report, Airline Rating 1997, contains monthly Airline Quality Rating scores for 1996. Additional copies are available by contacting Wichita State University or the University of Nebraska at Omaha. The Airline Quality Rating (AQR) 1997 is a summary of a month-by-month quality ratings for the nine major domestic U.S. airlines operating during 1996. Using the Airline Quality Rating system and monthly performance data for each airline for the calendar year of 1996, individual and comparative ratings are reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for major domestic airlines across the 12 month period of 1996, and industry average results. Also comparative Airline Quality Rating data for 1991 through 1995 are included to provide a longer term view of quality in the industry.

Bowen, Brent D.↗
NASA NTRS1999

The Airline Quality Rating 1999

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline performance on combined multiple criteria. This current report, Airline Quality Rating 1999, reflects an updated approach to calculating monthly Airline Quality Rating scores for 1998. AQR scores for the calendar year 1998 are based on 15 elements that focus on airline performance areas important to air travel consumers. The Airline Quality Rating is a summary of month-by-month quality ratings for the ten major U.S. airlines operating during 1998. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, major airlines comparative performance for the calendar year 1998 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for major airlines domestic operations for the 12 month period of 1998, and industry average results. Also, comparative Airline Quality Rating data for 1997, using the updated criteria, are included to provide a reference point regarding quality in the industry.

Bowen, Brent D.↗
NASA NTRS2003

Production of Near-Mirror Surface Quality by Precision Grinding

Mechanical components such as gears and bearings operate with the working surfaces in intimate contact with a mating part. The performance of such components will be influenced by the quality of the working surface. In general, a smoother surface will perform better than a rougher surface since the lubrication conditions are improved. For example, surfaces with a special near-mirror quality finish of low roughness performed better than ground surfaces when tested using a block-on-ring arrangement. Bearings with near-mirror quality have been tested and analyzed; lower running torques were measured and improved fatigue life was anticipated. Experiments have been done to evaluate the performance of gears with improved, low roughness surface finishing. The measured performance improvements include an increased scuffing (scoring) load capacity by a factor of 1.6, a 30-percent reduction of gear tooth running friction, and longer fatigue lives by a factor of about four. One can also anticipate that near-mirror quality surface finishing could improve the performance of other mechanical components such as mechanical seals and heavily loaded journal bearings. Given these demonstrated benefits, capable and economical methods for the production of mechanical components with near-mirror quality surfaces are desired. One could propose the production of near-mirror quality surfaces by several methods such as abrasive polishing, chemical assisted polishing, or grinding. Production of the surfaces by grinding offers the possibility to control the macro-geometry (form), waviness, and surface texture with one process. The present study was carried out to investigate the possibility of producing near-mirror quality surfaces by grinding. The present study makes use of a specially designed grinding machine spindle to improve the surface quality relative to the quality produced when using a spindle of conventional design.

Dimofte, Florin↗
NASA NTRS2004

The Airline Quality Rating 2004

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, the Airline Quality Rating 2004, reflects monthly Airline Quality Rating scores for 2003. AQR scores far the calendar year 2003 are based on 15 elemnts in four major areas that focus on airline performance aspects important to air travel consumers. The Airline Quality Rating 2004 is a summary of month-by-month quality ratings for U.S. airlines that have at least 1% of domestic passenger volume during 2003. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, airlines comparative performance for the calendar year of 2003 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for domestic airline operations for the 12-month period of 2003, and industry results. Also, comparative Airline Quality Rating data for 2002 are included, where available, to provide historical perspective

Bowen, Brent D.↗