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NASA NTRS2004

Software Quality Assurance Metrics

Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.

McRae, Kalindra A.↗
NASA NTRS1991

Training, Quality Assurance Factors, and Tools Investigation: a Work Report and Suggestions on Software Quality Assurance

Previously, several research tasks have been conducted, some observations were obtained, and several possible suggestions have been contemplated involving software quality assurance engineering at NASA Johnson. These research tasks are briefly described. Also, a brief discussion is given on the role of software quality assurance in software engineering along with some observations and suggestions. A brief discussion on a training program for software quality assurance engineers is provided. A list of assurance factors as well as quality factors are also included. Finally, a process model which can be used for searching and collecting software quality assurance tools is presented.

Lee, Pen-Nan↗
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 NTRS1990

Software quality assurance plan for GCS

The software quality assurance (SQA) function for the Guidance and Control Software (GCS) project which is part of a software error studies research program is described. The SQA plan outlines all of the procedures, controls, and audits to be carried out by the SQA organization to ensure adherence to the policies, procedures, and standards for the GCS project.

Duncan, Stephen E.↗
NASA NTRS1990

Software Quality Assurance Audits Guidebooks

The growth in cost and importance of software to NASA has caused NASA to address the improvement of software development across the agency. One of the products of this program is a series of guidebooks that define a NASA concept of the assurance processes that are used in software development. The Software Assurance Guidebook, NASA-GB-A201, issued in September, 1989, provides an overall picture of the NASA concepts and practices in software assurance. Second level guidebooks focus on specific activities that fall within the software assurance discipline, and provide more detailed information for the manager and/or practitioner. This is the second level Software Quality Assurance Audits Guidebook that describes software quality assurance audits in a way that is compatible with practices at NASA Centers.

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NASA NTRS2013

Tool Use Within NASA Software Quality Assurance

As space mission software systems become larger and more complex, it is increasingly important for the software assurance effort to have the ability to effectively assess both the artifacts produced during software system development and the development process itself. Conceptually, assurance is a straightforward idea - it is the result of activities carried out by an organization independent of the software developers to better inform project management of potential technical and programmatic risks, and thus increase management's confidence in the decisions they ultimately make. In practice, effective assurance for large, complex systems often entails assessing large, complex software artifacts (e.g., requirements specifications, architectural descriptions) as well as substantial amounts of unstructured information (e.g., anomaly reports resulting from testing activities during development). In such an environment, assurance engineers can benefit greatly from appropriate tool support. In order to do so, an assurance organization will need accurate and timely information on the tool support available for various types of assurance activities. In this paper, we investigate the current use of tool support for assurance organizations within NASA, and describe on-going work at JPL for providing assurance organizations with the information about tools they need to use them effectively.

software assurance↗
NASA NTRS2010

A Discussion of the Software Quality Assurance Role

The basic idea underlying this paper is that the conventional understanding of the role of a Software Quality Assurance (SQA) engineer is unduly limited. This is because few have asked who the customers of a SQA engineer are. Once you do this, you can better define what tasks a SQA engineer should perform, as well as identify the knowledge and skills that such a person should have. The consequence of doing this is that a SQA engineer can provide greater value to his or her customers. It is the position of this paper that a SQA engineer providing significant value to his or her customers must not only assume the role of an auditor, but also that of a software and systems engineer. This is because software engineers and their managers particularly value contributions that directly impact products and their development. These ideas are summarized as lessons learned, based on my experience at Jet Propulsion Laboratory (JPL).

experience↗
NASA NTRS1992

Daily quality assurance software for a satellite radiometer system

Six Differential Microwave Radiometers (DMR) on COBE (Cosmic Background Explorer) measure the large-angular-scale isotropy of the cosmic microwave background (CMB) at 31.5, 53, and 90 GHz. Quality assurance software analyzes the daily telemetry from the spacecraft to ensure that the instrument is operating correctly and that the data are not corrupted. Quality assurance for DMR poses challenging requirements. The data are differential, so a single bad point can affect a large region of the sky, yet the CMB isotropy requires lengthy integration times (greater than 1 year) to limit potential CMB anisotropies. Celestial sources (with the exception of the moon) are not, in general, visible in the raw differential data. A 'quicklook' software system was developed that, in addition to basic plotting and limit-checking, implements a collection of data tests as well as long-term trending. Some of the key capabilities include the following: (1) stability analysis showing how well the data RMS averages down with increased data; (2) a Fourier analysis and autocorrelation routine to plot the power spectrum and confirm the presence of the 3 mK 'cosmic' dipole signal; (3) binning of the data against basic spacecraft quantities such as orbit angle; (4) long-term trending; and (5) dipole fits to confirm the spacecraft attitude azimuth angle.

Keegstra, P. B.↗
NASA NTRS1997

Application of Domain Knowledge to Software Quality Assurance

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Wild, Christian W.↗
NASA NTRS1985

Proceedings of Tenth Annual Software Engineering Workshop

Papers are presented on the following topics: measurement of software technology, recent studies of the Software Engineering Lab, software management tools, expert systems, error seeding as a program validation technique, software quality assurance, software engineering environments (including knowledge-based environments), the Distributed Computing Design System, and various Ada experiments.

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NASA NTRS2004

Software for Optimizing Quality Assurance of Other Software

Software assurance is the planned and systematic set of activities that ensures that software processes and products conform to requirements, standards, and procedures. Examples of such activities are the following: code inspections, unit tests, design reviews, performance analyses, construction of traceability matrices, etc. In practice, software development projects have only limited resources (e.g., schedule, budget, and availability of personnel) to cover the entire development effort, of which assurance is but a part. Projects must therefore select judiciously from among the possible assurance activities. At its heart, this can be viewed as an optimization problem; namely, to determine the allocation of limited resources (time, money, and personnel) to minimize risk or, alternatively, to minimize the resources needed to reduce risk to an acceptable level. The end result of the work reported here is a means to optimize quality-assurance processes used in developing software.

Feather, Martin↗
NASA NTRS1991

Quality and security - They work together

This paper describes the importance of considering computer security as part of software quality assurance practice. The intended audience is primarily those professionals involved in the design, development, and quality assurance of software. Many issues are raised which point to the need ultimately for integration of quality assurance and computer security disciplines. To address some of the issues raised, the NASA Automated Information Security program is presented as a model which may be used for improving interactions between the quality assurance and computer security community of professionals.

Carr, Richard↗
NASA NTRS1993

Experience with Formal Methods techniques at the Jet Propulsion Laboratory from a quality assurance perspective

Recent experience with Formal Methods (FM) in the Software Quality Assurance Section at the Jet Propulsion Lab is presented. An integrated Formal Method process is presented to show how related existing requirements analysis and FM techniques complement one another. Example application of FM techniques such as formal specifications and specification animators are presented. The authors suggest that the quality assurance organization is a natural home for the Formal Methods specialist, whose expertise can then be used to best advantage across a range of projects.

Kelly, John C.↗
NASA NTRS1993

Software quality: Process or people

This paper will present data related to software development processes and personnel involvement from the perspective of software quality assurance. We examine eight years of data collected from six projects. Data collected varied by project but usually included defect and fault density with limited use of code metrics, schedule adherence, and budget growth information. The data are a blend of AFSCP 800-14 and suggested productivity measures in Software Metrics: A Practioner's Guide to Improved Product Development. A software quality assurance database tool, SQUID, was used to store and tabulate the data.

Palmer, Regina↗