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At least 307 records · Page 17

Parallelization of Rocket Engine Simulator Software (PRESS)

Parallelization of Rocket Engine System Software (PRESS) project is part of a collaborative effort with Southern University at Baton Rouge (SUBR), University of West Florida (UWF), and Jackson State University (JSU). The second-year funding, which supports two graduate students enrolled in our new Master's program in Computer Science at Hampton University and the principal investigator, have been obtained for the period from October 19, 1996 through October 18, 1997. The key part of the interim report was new directions for the second year funding. This came about from discussions during Rocket Engine Numeric Simulator (RENS) project meeting in Pensacola on January 17-18, 1997. At that time, a software agreement between Hampton University and NASA Lewis Research Center had already been concluded. That agreement concerns off-NASA-site experimentation with PUMPDES/TURBDES software. Before this agreement, during the first year of the project, another large-scale FORTRAN-based software, Two-Dimensional Kinetics (TDK), was being used for translation to an object-oriented language and parallelization experiments. However, that package proved to be too complex and lacking sufficient documentation for effective translation effort to the object-oriented C + + source code. The focus, this time with better documented and more manageable PUMPDES/TURBDES package, was still on translation to C + + with design improvements. At the RENS Meeting, however, the new impetus for the RENS projects in general, and PRESS in particular, has shifted in two important ways. One was closer alignment with the work on Numerical Propulsion System Simulator (NPSS) through cooperation and collaboration with LERC ACLU organization. The other was to see whether and how NASA's various rocket design software can be run over local and intra nets without any radical efforts for redesign and translation into object-oriented source code. There were also suggestions that the Fortran based code be encapsulated in C + + code thereby facilitating reuse without undue development effort. The details are covered in the aforementioned section of the interim report filed on April 28, 1997.

Cezzar, Ruknet↗

Intelligent Agents for Design and Synthesis Environments: My Summary

This presentation gives a summary of intelligent agents for design synthesis environments. We'll start with the conclusions, and work backwards to justify them. First, an important assumption is that agents (whatever they are) are good for software engineering. This is especially true for software that operates in an uncertain, changing environment. The "real world" of physical artifacts is like that: uncertain in what we can measure, changing in that things are always breaking down, and we must interact with non-software entities. The second point is that software engineering techniques can contribute to good design. There may have been a time when we wanted to build simple artifacts containing little or no software. But modern aircraft and spacecraft are complex, and rely on a great deal of software. So better software engineering leads to better designed artifacts, especially when we are designing a series of related artifacts and can amortize the costs of software development. The third point is that agents are especially useful for design tasks, above and beyond their general usefulness for software engineering, and the usefulness of software engineering to design.

Norvig, Peter↗

The TAME Project: Towards improvement-oriented software environments

Experience from a dozen years of analyzing software engineering processes and products is summarized as a set of software engineering and measurement principles that argue for software engineering process models that integrate sound planning and analysis into the construction process. In the TAME (Tailoring A Measurement Environment) project at the University of Maryland, such an improvement-oriented software engineering process model was developed that uses the goal/question/metric paradigm to integrate the constructive and analytic aspects of software development. The model provides a mechanism for formalizing the characterization and planning tasks, controlling and improving projects based on quantitative analysis, learning in a deeper and more systematic way about the software process and product, and feeding the appropriate experience back into the current and future projects. The TAME system is an instantiation of the TAME software engineering process model as an ISEE (integrated software engineering environment). The first in a series of TAME system prototypes has been developed. An assessment of experience with this first limited prototype is presented including a reassessment of its initial architecture.

Basili, Victor R.↗

Software development environments: Status and trends

Currently software engineers are the essential integrating factors tying several components together. The components consist of process, methods, computers, tools, support environments, and software engineers. The engineers today empower the tools versus the tools empowering the engineers. Some of the issues in software engineering are quality, managing the software engineering process, and productivity. A strategy to accomplish this is to promote the evolution of software engineering from an ad hoc, labor intensive activity to a managed, technology supported discipline. This strategy may be implemented by putting the process under management control, adopting appropriate methods, inserting the technology that provides automated support for the process and methods, collecting automated tools into an integrated environment and educating the personnel.

Duffel, Larry E.↗

SAGA: A project to automate the management of software production systems

Research into software development is required to reduce its production cost and to improve its quality. Modern software systems, such as the embedded software required for NASA's space station initiative, stretch current software engineering techniques. The requirements to build large, reliable, and maintainable software systems increases with time. Much theoretical and practical research is in progress to improve software engineering techniques. One such technique is to build a software system or environment which directly supports the software engineering process, i.e., the SAGA project, comprising the research necessary to design and build a software development which automates the software engineering process. Progress under SAGA is described.

Campbell, Roy H.↗

Managing the Software Development Process

The goal of any software development project is to produce a product that is delivered on time, within the allocated budget, and with the capabilities expected by the customer and unfortunately, this goal is rarely achieved. However, a properly managed project in a mature software engineering environment can consistently achieve this goal. In this paper we provide an introduction to three project success factors, a properly managed project, a competent project manager, and a mature software engineering environment. We will also present an overview of the benefits of a mature software engineering environment based on 24 years of data from the Software Engineering Lab, and suggest some first steps that an organization can take to begin benefiting from this environment. The depth and breadth of software engineering exceeds this paper, various references are cited with a goal of raising awareness and encouraging further investigation into software engineering and project management practices.

Lubelczky, Jeffrey T.↗

Quasi-Static and Dynamic Analysis of Composite Panels: Challenges in Engineering-Level Commercial Software

In engineering applications, where analysis time and efficiency are essential, analytical models and commercially available finite element (FE) material models are the two mainstream methods used to analyze composite crush scenarios. A reliable numerical model addressing the crushing response of composite materials requires a nonlinear progressive damage analysis which includes appropriate failure mechanisms such as matrix cracking, fragmentation, delamination, and fiber breakage. One might be able to address all these interacting failure responses through implementation/validation of a user defined material model or by utilization of a commercially available model, the latter being the most efficient engineering approach. In this paper, the quasi-static and dynamic crushing response of composite specimens, consisting of a C-channel and a corrugated geometry manufactured with carbon fiber/epoxy matrix fabric, are modeled using the progressive composite damage model within ABAQUS. The novel part of this work, which has not been previously addressed in the literature, is the utilization of a detailed parametric study to optimize composite damage model parameters for a given quasi-static crush simulation in ABAQUS. C-channel experiments were used to calibrate the model and then refine/optimize a set of material parameters that best fit the experimental results. These identical parameters were then used to simulate the crush response of the corrugated channel specimens, thereby making it a pure prediction and not a double recalibration. Next, the dynamic response of both panels were predicted, further confirming the predictive capability of the developed numerical model. The effect of parameter variation on the crush response is fully documented for future use in engineering applications utilizing this specific ABAQUS damage model.

Paria Naghipour↗

Methodology for automating software systems. Task 1 of the foundations for automating software systems

The early stages of a research program designed to establish an experimental research platform for software engineering are described. Major emphasis is placed on Computer Assisted Software Engineering (CASE). The Poor Man's CASE Tool is based on the Apple Macintosh system, employing available software including Focal Point II, Hypercard, XRefText, and Macproject. These programs are functional in themselves, but through advanced linking are available for operation from within the tool being developed. The research platform is intended to merge software engineering technology with artificial intelligence (AI). In the first prototype of the PMCT, however, the sections of AI are not included. CASE tools assist the software engineer in planning goals, routes to those goals, and ways to measure progress. The method described allows software to be synthesized instead of being written or built.

Moseley, Warren↗

Domain-specific functional software testing: A progress report

Software Engineering is a knowledge intensive activity that involves defining, designing, developing, and maintaining software systems. In order to build effective systems to support Software Engineering activities, Artificial Intelligence techniques are needed. The application of Artificial Intelligence technology to Software Engineering is called Knowledge-based Software Engineering (KBSE). The goal of KBSE is to change the software life cycle such that software maintenance and evolution occur by modifying the specifications and then rederiving the implementation rather than by directly modifying the implementation. The use of domain knowledge in developing KBSE systems is crucial. Our work is mainly related to one area of KBSE that is called automatic specification acquisition. One example is the WATSON prototype on which our current work is based. WATSON is an automatic programming system for formalizing specifications for telephone switching software mainly restricted to POTS, i.e., plain old telephone service. Our current approach differentiates itself from other approaches in two antagonistic ways. On the one hand, we address a large and complex real-world problem instead of a 'toy domain' as in many research prototypes. On the other hand, to allow such scaling, we had to relax the ambitious goal of complete automatic programming, to the easier task of automatic testing.

Nonnenmann, Uwe↗

RSE-Ops

If DevOps is the intersection of "Developer" and "Operations," then how does this concept map to high performance computing? The answer is RSE-ops, or the intersection of Research Software Engineering and Operations. Research Software Engineers (RSEs) are the individuals writing code for scientific software, and supporting researchers to use codes on high performance computing systems. RSE-ops, then, generally refers to best practices for development and operations of scientific software, which typically happens in a high performance computing environment. A comparison can be made to Cloud Native Devops, which is a similar term that has emerged around Cloud Native Computing. It refers to the application of DevOps practices to the cloud.

97 MATHEMATICS AND COMPUTING↗

Building an experience factory for maintenance

This paper reports the preliminary results of a study of the software maintenance process in the Flight Dynamics Division (FDD) of the National Aeronautics and Space Administration/Goddard Space Flight Center (NASA/GSFC). This study is being conducted by the Software Engineering Laboratory (SEL), a research organization sponsored by the Software Engineering Branch of the FDD, which investigates the effectiveness of software engineering technologies when applied to the development of applications software. This software maintenance study began in October 1993 and is being conducted using the Quality Improvement Paradigm (QIP), a process improvement strategy based on three iterative steps: understanding, assessing, and packaging. The preliminary results represent the outcome of the understanding phase, during which SEL researchers characterized the maintenance environment, product, and process. Findings indicate that a combination of quantitative and qualitative analysis is effective for studying the software maintenance process, that additional measures should be collected for maintenance (as opposed to new development), and that characteristics such as effort, error rate, and productivity are best considered on a 'release' basis rather than on a project basis. The research thus far has documented some basic differences between new development and software maintenance. It lays the foundation for further application of the QIP to investigate means of improving the maintenance process and product in the FDD.

Valett, Jon D.↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

The quality assurance role in the Deep Space Network

The quality assurance section provides skilled personnel who perform the following functions: quality hardware engineering, quality software engineering, inspection and testing, and an independent assessment to quality, engineering and project requirements. The quality assurance section provides specifications, workmanship standards, process specifications and quality assurance procedures in support of DSN equipment. In addition, the quality assurance section reviews DSN engineering documents to ensure that appropriate and adequate quality provisions are included.

Sirpilla, R. L.↗

T on the Cray X/MP

This research was aimed at porting the T programming language, a dialect of LISP, to the Cray X/MP computer. The effort involved research into systems engineering and software engineering problems related not only to compiler design and implementation, but also to parallel computation, the X/MP being a shared-memory multiprocessor. Porting also involved the sub-tasks of retargeting the assembler, code-generator, and run-time system. A reasonably effective porting methodology that is relatively straight forward, although more difficult than table-driven approaches, has been developed. The run-time system was not ported, and thus the T programs cannot be run without explicit linking of the required run-time support. The run-time performance gain achieved in generated code was found to be disappointing. Recommendations for the achievement of higher performance are given.

Hudak, Paul↗

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗

Software System Safety and the NASA Aeronautics Blueprint

NASA's Aeronautics Blueprint lays out a research agenda for the Agency s aeronautics program. The word software appears only four times in this Blueprint, but the critical importance of safe and correct software to the fulfillment of the proposed research is evident on almost every page. Most of the technology solutions proposed to address challenges in aviation are software dependent technologies. Of the fifty-two specific technology solutions described in the Blueprint, forty-one depend, at least in part, on software for success. For thirty-five of these forty-one, software is not only critical to success, but also to human safety. That is, implementing the technology solutions will require using software in such a way that it may, if not specified, designed, and implemented properly, lead to fatal accidents. These results have at least two implications for the research based on the Blueprint: (1) knowledge about the current state-of-the-art and state-of-the-practice in software engineering and software system safety is essential, and (2) research into current unsolved problems in these software disciplines is also essential.

Holloway, C. Michael↗