Software development cost estimation
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Viewgraphs from the Information Security and Integrity Systems seminar held at the University of Houston-Clear Lake on May 15-16, 1990 are presented. A tutorial on computer security is presented. The goals of this tutorial are the following: to review security requirements imposed by government and by common sense; to examine risk analysis methods to help keep sight of forest while in trees; to discuss the current hot topic of viruses (which will stay hot); to examine network security, now and in the next year to 30 years; to give a brief overview of encryption; to review protection methods in operating systems; to review database security problems; to review the Trusted Computer System Evaluation Criteria (Orange Book); to comment on formal verification methods; to consider new approaches (like intrusion detection and biometrics); to review the old, low tech, and still good solutions; and to give pointers to the literature and to where to get help. Other topics covered include security in software applications and development; risk management; trust: formal methods and associated techniques; secure distributed operating system and verification; trusted Ada; a conceptual model for supporting a B3+ dynamic multilevel security and integrity in the Ada runtime environment; and information intelligence sciences.
The project team, including the University of Arkansas (UA) as the lead, the University of Arkansas at Little Rock (UALR), Network Perception (NP), and Bastazo, has successfully researched, developed, and demonstrated the V-INT toolset, and also integrated it into the commercial products of NP (i.e., NP-View) and Bastazo (i.e., Spartan). The end product is a cybersecurity software tool for energy utilities that can automatically assess the risks of software vulnerabilities in an organization’s assets considering the organization’s firewall policies. It allows security operators to identify the small portion of vulnerabilities that poses true threats to their system (i.e., those that are not protected by firewall policies) and prioritize the mitigation of these vulnerabilities to minimize risks. It also allows security operators to identify the vulnerability-induced attack paths under their organization’s firewall policy, providing effective decision supports for mitigating potential attacks.
The Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) software has seen various improvements and additional physics capabilities since validation against experimental data was last published for HyRAM v3.1. Notably, HyRAM+ now includes four models allowing for the calculation of overpressure resulting from vapor cloud explosions from unconfined jet releases. As with the previous HyRAM validation report, validation data was gathered from available published literature and tested against HyRAM+ capabilities. The validation comparisons include tank blowdown, unignited dispersion jet plume, ignited jet flame, and enclosed accumulation and overpressure. The unconfined overpressure calculations in HyRAM+ v5.1.1 generally show good agreement with many of the experimental data sets for all four unconfined overpressure models, though HyRAM+ overpredicts the experimental data for small and cryogenic hydrogen releases. The comparisons for the other HyRAM+ physics models are largely unchanged from the previously published validation report.
Experiments on decision making in planning problems are described. Executives were tested in dealing with capital investments and competitive pricing decisions under conditions of uncertainty. A software package, the interactive risk analysis model system, was developed, and two controlled experiments were conducted. It is concluded that planning models can aid management, and predicted uses of the models are as a central tool, as an educational tool, to improve consistency in decision making, to improve communications, and as a tool for consensus decision making.
The utility of the Space Station is improved, the ability to manage and integrate its development and operation enhanced, and the cost and risk of developing the software for it is minimized by three major information systems. The Space Station Information System (SSIS) provides for the transparent collection and dissemination of operational information to all users and operators. The Technical and Management Information System (TMIS) provides all the developers with timely and consistent program information and a project management 'window' to assess the project status. The Software Support Environment (SSE) provides automated tools and standards to be used by all software developers. Together, these three systems are vital to the successful execution of the program.
Current system simulations are mature, difficult to modify, and poorly documented. Probabilistic life prediction techniques for space applications are in their early application stage. Many parts of the full system, variable fidelity simulation, have been demonstrated individually or technology is available from aeronautical applications. A 20% reduction in time to design with improvements in performance and risk reduction is anticipated. GRC software development will proceed with similar development efforts in aeronautical simulations. Where appropriate, parallel efforts will be encouraged/tracked in high risk areas until success is assured.
An assessment methodology is described and illustrated.
Over the past several years, we have developed techniques to discriminate between fault-prone software modules and those that are not, to estimate a software system's residual fault content, to identify those portions of a software system having the highest estimated number of faults, and to estimate the effects of requirements changes on software quality.
Machine Learning (ML) is revolutionizing many technological fields, but its use in aviation remains restricted due to stringent certification requirements. Efforts by the aviation community to establish standards for certifying ML-based systems are progressing, yet challenges persist, particularly with safety assessment methods for ML-based systems. This research addresses these challenges through a case study of an autonomous emergency braking system utilizing a computer vision deep neural network (DNN). We demonstrate a safety assessment process tailored to ML-specific concerns, such as low integrity and performance variability in quantitative safety analysis. This study can serve as an illustrative example to facilitate the discussion and convergence on certification aspects for ML-based systems within the aviation community.
The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.
Development of NASA's Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for National Aeronautics and Space Administration (NASA) space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module - which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions.
Development of NASAs Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for NASA space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and have provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions
This paper introduces a new trade analysis software called the Space Mission Architecture and Risk Analysis Tool (SMART). This tool supports a high-level system trade study on a complex mission, such as a potential Mars Sample Return (MSR) mission, in an intuitive and quantitative manner. In a complex mission, a common approach to increase the probability of success is to have redundancy and prepare backups. Quantitatively evaluating the utility of adding redundancy to a system is important but not straightforward, particularly when the failure of parallel subsystems are correlated.
An interactive computerized project management software package (RISKNET) is designed to analyze the effect of the risk involved in each specific activity on the results of the total SEASAT-A program. Both the time and the cost of each distinct activity can be modeled with an uncertainty interval so as to provide the project manager with not only the expected time and cost for the completion of the total program, but also with the expected range of costs corresponding to any desired level of significance. The nature of the SEASAT-A program is described. The capabilities of RISKNET and the implementation plan of a RISKNET analysis for the development of SEASAT-A are presented.
At NASA's Jet Propulsion Laboratory (JPL), NASA-developed Video Imaging Communication and Retrieval (VICAR) software laid the groundwork for analyzing images of all kinds. A project seeking to use imaging technology for health care diagnosis began when the imaging team considered using the VICAR software to analyze X-ray images of soft tissue. With marginal success using X-rays, the team applied the same methodology to ultrasound imagery, which was already digitally formatted. The new approach proved successful for assessing amounts of plaque build-up and arterial wall thickness, direct predictors of heart disease, and the result was a noninvasive diagnostic system with the ability to accurately predict heart health. Medical Technologies International Inc. (MTI) further developed and then submitted the technology to a vigorous review process at the FDA, which cleared the software for public use. The software, patented under the name Prowin, is being used in MTI's patented ArterioVision, a carotid intima-media thickness (CIMT) test that uses ultrasound image-capturing and analysis software to noninvasively identify the risk for the major cause of heart attack and strokes: atherosclerosis. ArterioVision provides a direct measurement of atherosclerosis by safely and painlessly measuring the thickness of the first two layers of the carotid artery wall using an ultrasound procedure and advanced image-analysis software. The technology is now in use in all 50 states and in many countries throughout the world.
RISK D/C is prototype computer program assisting in attempts to do program risk modeling for Space Exploration Initiative (SEI) architectures proposed in Synthesis Group Report. Risk assessment performed with respect to risk events, probabilities, and severities of potential results. Enables ranking, with respect to effectiveness, of risk-mitigation strategies proposed for exploration program architecture. Allows for fact that risk assessment in early phases of planning subjective. Although specific to SEI in present form, also used as software framework for development of risk-assessment programs for other specific uses. Developed for Macintosh(TM) series computer. Requires HyperCard(TM) 2.0 or later, as well as 2 Mb of random-access memory and System 6.0.8 or later.
This paper describes the new process used by the Project Design Center at NASA's Jet Propulsion Laboratory for the identification, assessment and communication of risk elements throughout the lifecycle of a mission design. This process includes a software tool, 'RAP' that collects and communicates risk information between the various designers and a 'risk expert' who mediates this process. The establishment of this process is an attempt towards the systematic consideration of risk in the design decision making process. Using this process, we are able to better keep track of the risks associated with the design decisions. Furthermore, it helps us develop better risk profiles for the studies under consideration. We aim to refine and expand the current process to enable more thorough risk analysis capabilities in the future.