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DOE OSTI2022

Overcoming Challenges to Continuous Integration in HPC

Continuous integration (CI) has become a ubiquitous practice in modern software development, with major code hosting services offering free automation on popular platforms. CI offers major benefits, as it enables detecting bugs in code prior to committing changes. While high-performance computing (HPC) research relies heavily on software, HPC machines are not considered “common” platforms. This presents several challenges that hinder the adoption of CI in HPC environments, making it difficult to maintain bug-free HPC projects, and resulting in adverse effects on the research community. Here we explore the challenges that impede HPC CI, such as hardware diversity, security, isolation, administrative policies, and non-standard authentication, environments, and job submission mechanisms. We propose several solutions that could enhance the quality of HPC software and the experience of developers. Implementing these solutions would require significant changes at HPC centers, but if these changes are made, it would ultimately enable faster and better science.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Reducing the complexity of software systems - A strategic software perspective

The results of a combined management and technical initiative aimed at reducing the size and complexity associated with developing operations planning, scheduling, and resource management software systems are presented. The initiative has produced operations concepts, functional requirements, system architectures, a comprehensive lexicon, and software tools to revolutionize the traditional software technology and development practices for planning, scheduling, and resource management systems used in space operations control centers. Examples of technology and practices to reduce complexity include a method for projecting design consequences from an operations concept, a universal architecture for heuristic algorithms, an object-oriented framework for describing large classes of problems that parametrically adapt to all domain peculiarities, the identification of general approaches which respond to changes with minimum impact on systems implementations, and a management structure for prototyping to minimize the risks of ill-conceived designs.

Hornstein, Rhoda S.↗

NASA NTRS2005

Visions of Automation and Realities of Certification

Quite a lot of people envision automation as the solution to many of the problems in aviation and air transportation today, across all sectors: commercial, private, and military. This paper explains why some recent experiences with complex, highly-integrated, automated systems suggest that this vision will not be realized unless significant progress is made over the current state-of-the-practice in software system development and certification.

Hayhurst, Kelly J.↗

NASA NTRS2014

Recent Developments and Challenges Implementing New and Improved Stress Intensity Factor (K) Solutions in NASGRO for Damage Tolerance Analyses

Fatigue crack growth analysis software has been available to damage tolerance analysts for many years in either commercial products or via proprietary in-house codes. The NASGRO software has been publicly available since the mid-80s (known as NASA/FLAGRO up to 1999) and since 2000 has been sustained and further developed by a collaborative effort between Southwest Research Institute® (SwRI®), the NASA Johnson Space Center (JSC), and the members of the NASGRO Industrial Consortium. Since the stress intensity factor (K) is the foundation of fracture mechanics and damage tolerance analysis of aircraft structures, a significant focus of development efforts in the past fifteen years has been geared towards enhancing legacy K solutions and developing new and efficient numerical K solutions that can handle the complicated stress gradients computed by today’s analysts using detailed finite element models of fatigue critical locations. This paper provides an overview of K solutions that have been recently implemented or improved for the analysis of geometries such as two unequal through cracks at a hole and two unequal corner cracks at a hole, as well as state-of-the-art weight function models capable of computing K in the presence of univariant and/or bivariant stress gradients and complicated residual stress distributions. Some historical background is provided to review how common K solutions have evolved over the years, including selective examples from the literature and from new research. Challenges and progress in rectifying discrepancies between older legacy solutions and newer models are reviewed as well as approaches and challenges for verification and validation of K solutions. Finally, a summary of current challenges and future research and development needs is presented. A key theme throughout the presentation of this paper will be how members of the aerospace industry have collaborated with software developers to develop a practical analysis tool that is used world-wide to support new design as well as the ongoing sustainment and airworthiness of commercial and military aircraft.

Cardinal, Joseph W.↗

NASA NTRS2009

Refactoring and Componentizing Legacy Codes: GMI Case Study

As Earth science applications grow increasingly complex over time, maintenance of such software becomes a significant challenge. In general, the software subsystems were designed, implemented and integrated (over an extended period of time) by different groups that did not follow the same software design standard. The objective was understandably to obtain scientific results quickly, but this goal was often achieved at the expense of good software practices. With that pattern of development, the cost of incremental changes to the applications grow ominously large. This increase in effort, tends to squeeze development resources and largely prevent any systematic attempt to reintroduce better software practices and thereby enhance the maintainability of the software. In this paper, we present the process we used to incrementally refactor and componentize the Global Modeling Initiative code to make it more understandable, maintainable, flexible and extensible. The resulting product not only preserves the scientific integrity of the original code but also extends the capabilities of the code for several applications.

Kouatchou, Jules↗

NASA NTRS1984

Measures and metrics for software development

The evaluations of and recommendations for the use of software development measures based on the practical and analytical experience of the Software Engineering Laboratory are discussed. The basic concepts of measurement and system of classification for measures are described. The principal classes of measures defined are explicit, analytic, and subjective. Some of the major software measurement schemes appearing in the literature are derived. The applications of specific measures in a production environment are explained. These applications include prediction and planning, review and assessment, and evaluation and selection.

Source record↗

NASA NTRS1976

Standardized development of computer software. Part 1: Methods

This work is a two-volume set on standards for modern software engineering methodology. This volume presents a tutorial and practical guide to the efficient development of reliable computer software, a unified and coordinated discipline for design, coding, testing, documentation, and project organization and management. The aim of the monograph is to provide formal disciplines for increasing the probability of securing software that is characterized by high degrees of initial correctness, readability, and maintainability, and to promote practices which aid in the consistent and orderly development of a total software system within schedule and budgetary constraints. These disciplines are set forth as a set of rules to be applied during software development to drastically reduce the time traditionally spent in debugging, to increase documentation quality, to foster understandability among those who must come in contact with it, and to facilitate operations and alterations of the program as requirements on the program environment change.

Tausworthe, R. C.↗

NASA NTRS2003

System and Software Reliability (C103)

Within the last decade better reliability models (hardware. software, system) than those currently used have been theorized and developed but not implemented in practice. Previous research on software reliability has shown that while some existing software reliability models are practical, they are no accurate enough. New paradigms of development (e.g. OO) have appeared and associated reliability models have been proposed posed but not investigated. Hardware models have been extensively investigated but not integrated into a system framework. System reliability modeling is the weakest of the three. NASA engineers need better methods and tools to demonstrate that the products meet NASA requirements for reliability measurement. For the new models for the software component of the last decade, there is a great need to bring them into a form that they can be used on software intensive systems. The Statistical Modeling and Estimation of Reliability Functions for Systems (SMERFS'3) tool is an existing vehicle that may be used to incorporate these new modeling advances. Adapting some existing software reliability modeling changes to accommodate major changes in software development technology may also show substantial improvement in prediction accuracy. With some additional research, the next step is to identify and investigate system reliability. System reliability models could then be incorporated in a tool such as SMERFS'3. This tool with better models would greatly add value in assess in GSFC projects.

Wallace, Dolores↗

NASA NTRS2019

Benefits and Challenges of Model-based Software Engineering: Lessons Learned based on Qualitative and Quantitative Findings

Even though Model-based Software Engineering (MBSwE) techniques and Autogenerated Code (AGC) have been increasingly used to produce complex software systems, there is only anecdotal knowledge about the state-of-thepractice. Furthermore, there is a lack of empirical studies that explore the potential quality improvements due to the use of these techniques. This paper presents in-depth qualitative findings about development and Software Assurance (SWA) practices and detailed quantitative analysis of software bug reports of a NASA mission that used MBSwE and AGC. The mission’s flight software is a combination of handwritten code and AGC developed by two different approaches: one based on state chart models (AGC-M) and another on specification dictionaries (AGC-D). The empirical analysis of fault proneness is based on 380 closed bug reports created by software developers. Our main findings include: (1) MBSwE and AGC provide some benefits, but also impose challenges. (2) SWA done only at a model level is not sufficient. AGC code should also be tested and the models and AGC should always be kept in-sync. AGC must not be changed manually. (3) Fixes made to address an individual bug report were spread both across multiple modules and across multiple files. On average, for each bug report 1.4 modules, that is, 3.4 files were fixed. (4) Most bug reports led to changes in more than one type of file. The majority of changes to auto-generated source code files were made in conjunction to changes in either file with state chart models or XML files derived from dictionaries. (5) For newly developed files, AGC-M and handwritten code were of similar quality, while AGC-D files were the least fault prone.

Goseva-Popstojanova, Katerina↗

DOE OSTI2020

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2001

Report on Automated Semantic Analysis of Scientific and Engineering Codes

The loss of the Mars Climate Orbiter due to a software error reveals what insiders know: software development is difficult and risky because, in part, current practices do not readily handle the complex details of software. Yet, for scientific software development the MCO mishap represents the tip of the iceberg; few errors are so public, and many errors are avoided with a combination of expertise, care, and testing during development and modification. Further, this effort consumes valuable time and resources even when hardware costs and execution time continually decrease. Software development could use better tools! This lack of tools has motivated the semantic analysis work explained in this report. However, this work has a distinguishing emphasis; the tool focuses on automated recognition of the fundamental mathematical and physical meaning of scientific code. Further, its comprehension is measured by quantitatively evaluating overall recognition with practical codes. This emphasis is necessary if software errors-like the MCO error-are to be quickly and inexpensively avoided in the future. This report evaluates the progress made with this problem. It presents recommendations, describes the approach, the tool's status, the challenges, related research, and a development strategy.

Stewart. Maark E. M.↗

DOE OSTI2021

Automating Software Productivity Planning: Lightweight Tools for Upgrading Team Practices

A lightweight iterative workflow, called Productivity and Sustainability Improvement Planning (PSIP) has been developed to assist software teams with employing good software engineering practices. Three PSIP tools automate practice summarization, self-assessment, and progress tracking to enhance team engagement around software process improvement: Reposcanner, RateYourProject (RYP) and Progress Tracking Cards (PTCs) respectively. Reposcanner is a data analysis tool. RYP is an interactive self-assessment tool that provides an easy-to-use entry point to the PSIP process. Once process improvements are identified, PTCs are created by teams to measure outcomes and progression toward their goals. We present an exemplifying case study with a software team where these tools have been put to use, along with a description of the tools, and future plans for further improvements.

Raybourn, Elaine↗

NASA NTRS2004

A Multiagent Modeling Environment for Simulating Work Practice in Organizations

In this paper we position Brahms as a tool for simulating organizational processes. Brahms is a modeling and simulation environment for analyzing human work practice, and for using such models to develop intelligent software agents to support the work practice in organizations. Brahms is the result of more than ten years of research at the Institute for Research on Learning (IRL), NYNEX Science & Technology (the former R&D institute of the Baby Bell telephone company in New York, now Verizon), and for the last six years at NASA Ames Research Center, in the Work Systems Design and Evaluation group, part of the Computational Sciences Division (Code IC). Brahms has been used on more than ten modeling and simulation research projects, and recently has been used as a distributed multiagent development environment for developing work practice support tools for human in-situ science exploration on planetary surfaces, in particular a human mission to Mars. Brahms was originally conceived of as a business process modeling and simulation tool that incorporates the social systems of work, by illuminating how formal process flow descriptions relate to people s actual located activities in the workplace. Our research started in the early nineties as a reaction to experiences with work process modeling and simulation . Although an effective tool for convincing management of the potential cost-savings of the newly designed work processes, the modeling and simulation environment was only able to describe work as a normative workflow. However, the social systems, uncovered in work practices studied by the design team played a significant role in how work actually got done-actual lived work. Multi- tasking, informal assistance and circumstantial work interactions could not easily be represented in a tool with a strict workflow modeling paradigm. In response, we began to develop a tool that would have the benefits of work process modeling and simulation, but be distinctively able to represent the relations of people, locations, systems, artifacts, communication and information content.

Sierhuis, Maarten↗

NASA NTRS2015

Planning the Unplanned Experiment: Towards Assessing the Efficacy of Standards for Safety-Critical Software

Safe use of software in safety-critical applications requires well-founded means of determining whether software is fit for such use. While software in industries such as aviation has a good safety record, little is known about whether standards for software in safety-critical applications 'work' (or even what that means). It is often (implicitly) argued that software is fit for safety-critical use because it conforms to an appropriate standard. Without knowing whether a standard works, such reliance is an experiment; without carefully collecting assessment data, that experiment is unplanned. To help plan the experiment, we organized a workshop to develop practical ideas for assessing software safety standards. In this paper, we relate and elaborate on the workshop discussion, which revealed subtle but important study design considerations and practical barriers to collecting appropriate historical data and recruiting appropriate experimental subjects. We discuss assessing standards as written and as applied, several candidate definitions for what it means for a standard to 'work,' and key assessment strategies and study techniques and the pros and cons of each. Finally, we conclude with thoughts about the kinds of research that will be required and how academia, industry, and regulators might collaborate to overcome the noted barriers.

Graydon, Patrick J.↗

NASA NTRS2006

Software Reuse Within the Earth Science Community

Scientific missions in the Earth sciences frequently require cost-effective, highly reliable, and easy-to-use software, which can be a challenge for software developers to provide. The NASA Earth Science Enterprise (ESE) spends a significant amount of resources developing software components and other software development artifacts that may also be of value if reused in other projects requiring similar functionality. In general, software reuse is often defined as utilizing existing software artifacts. Software reuse can improve productivity and quality while decreasing the cost of software development, as documented by case studies in the literature. Since large software systems are often the results of the integration of many smaller and sometimes reusable components, ensuring reusability of such software components becomes a necessity. Indeed, designing software components with reusability as a requirement can increase the software reuse potential within a community such as the NASA ESE community. The NASA Earth Science Data Systems (ESDS) Software Reuse Working Group is chartered to oversee the development of a process that will maximize the reuse potential of existing software components while recommending strategies for maximizing the reusability potential of yet-to-be-designed components. As part of this work, two surveys of the Earth science community were conducted. The first was performed in 2004 and distributed among government employees and contractors. A follow-up survey was performed in 2005 and distributed among a wider community, to include members of industry and academia. The surveys were designed to collect information on subjects such as the current software reuse practices of Earth science software developers, why they choose to reuse software, and what perceived barriers prevent them from reusing software. In this paper, we compare the results of these surveys, summarize the observed trends, and discuss the findings. The results are very similar, with the second, larger survey confirming the basic results of the first, smaller survey. The results suggest that reuse of ESE software can drive down the cost and time of system development, increase flexibility and responsiveness of these systems to new technologies and requirements, and increase effective and accountable community participation.

Marshall, James J.↗

NASA NTRS1999

Panel: Practical Issues in Implementing Software Reliability Measurement

Many ways of estimating software systems' reliability, or reliability-related quantities, have been developed over the past several years. In this panel, we discuss practical issues to be addressed in implementing software reliabilty measurement techniques in a production development environment.

software reliability software measurement software↗

DOE OSTI2020

Air compressor load forecasting using artificial neural network

Air compressor systems are responsible for approximately 10% of the electricity consumed in United States and European Union industry. As many researches have proven the effectiveness of using Artificial Neural Network inair compressor performance prediction, there is still a need to forecast the air compressor electrical load profile. The objective of this study is to predict compressed air systems’ electrical load profile, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load managementand look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Networkand Long Short-Term Memory were used to predict an air compressors electrical load. Compressors with three different control mechanisms are evaluated with a total number of 11,874 observations. Here, the forecasts were validated using out-of-sample datasets with 5-fold cross-validation. Models produced average coefficient ofdetermination values from 0.24 to 0.94, average root-mean-square errors from 0.05 kW - 5.83 kW, and meanabsolute scaled errors from 0.20 to 1.33. The results indicate that both artificial neural networks yield goodresults for compressors using variable speed drive (average R 2 = 0.8 and no naïve forecasting), only the longshort-term memory model gives acceptable results for compressors using on/off control (average R 2 = 0.82 and no naïve forecasting), and no satisfactory results are obtained for load/unload type air compressors (models constituting active forecasting).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1976

Software production methodology tested project

The history and results of a 3 1/2-year study in software development methodology are reported. The findings of this study have become the basis for DSN software development guidelines and standard practices. The article discusses accomplishments, discoveries, problems, recommendations and future directions.

Tausworthe, R. C.↗