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An investigation into the areas having an impact on producing reliable software including automated verification tools, software modeling, testing techniques, structured programming, and management techniques is presented. This final report contains the results of this investigation, analysis of each technique, and the definition of a methodology for producing reliable software.
Developing flight software for small-scale missions such as CubeSats and SmallSats is challenging. These missions typically have ambitious goals, modest budgets, and tight schedules. To meet these challenges, a good flight software framework is essential. Frameworks can provide an architecture, infrastructure, tools, and reusable software components, all of which can help developers deliver their code on time and on budget. In this paper we present F Prime, a free, open-source flight software framework developed at JPL and tailored to small-scale systems such as CubeSats, SmallSats, and instruments. F Prime comprises several elements: (1) an architecture that decomposes flight software into discrete components with well-defined interfaces; (2) a C++ framework that provides core capabilities such as message queues and threads; (3) tools for specifying components and connections and automatically generating code; (4) a growing collection of ready-to-use components; and (5) tools for testing flight software at the unit and integration levels.We describe the F Prime framework and tools and present our experience using them. We describe several enhancements to the framework currently underway in the areas of software design, software verification, and ground data systems for testing.
The objective of the Environmental Control and Life Support System (ECLSS) Advanced Automation Project is to recommend and develop advanced software for the initial and evolutionary Space Station Freedom (SSF) ECLS system which will minimize the crew and ground manpower needed for operations. Another objective includes capturing ECLSS design and development knowledge for future missions. This report summarizes our results from Phase I, the ECLSS domain analysis phase, which we broke down into three steps: 1) Analyze and document the baselined ECLS system, 2) envision as our goal an evolution to a fully automated regenerative life support system, built upon an augmented baseline, and 3) document the augmentations (hooks and scars) and advanced software systems which we see as necessary in achieving minimal manpower support for ECLSS operations. In addition, Phase I included development of an advanced software life cycle testing tools will be used in the development of the software. In this way, we plan in preparation for phase II and III, the development and integration phases, respectively. Automated knowledge acquisition, engineering, verification, and can capture ECLSS development knowledge for future use, develop more robust and complex software, provide feedback to the KBS tool community, and insure proper visibility of our efforts.
Two automated software verification and testing systems were developed for use in the analysis of computer programs. An evaluation of the static analyzer DAVE and the dynamic analyzer PET, which are used in the analysis of FORTRAN programs on Control Data (CDC) computers, are described. Both systems were found to be effective and complementary, and are recommended for use in testing FORTRAN programs.
Software quality is of primary concern in all large-scale expert system development efforts. Building appropriate validation and test tools for ensuring software reliability of expert systems is therefore required. The Expert Systems Validation Associate (EVA) is a validation system under development at the Lockheed Artificial Intelligence Center. EVA provides a wide range of validation and test tools to check correctness, consistency, and completeness of an expert system. Testing a major function of EVA. It means executing an expert system with test cases with the intent of finding errors. In this paper, we describe many different types of testing such as function-based testing, structure-based testing, and data-based testing. We describe how appropriate test cases may be selected in order to perform good and thorough testing of an expert system.
The objective of the environmental control and life support system (ECLSS) Advanced Automation Project is to influence the design of the initial and evolutionary Space Station Freedom Program (SSFP) ECLSS toward a man-made closed environment in which minimal flight and ground manpower is needed. Another objective includes capturing ECLSS design and development knowledge future missions. Our approach has been to (1) analyze the SSFP ECLSS, (2) envision as our goal a fully automated evolutionary environmental control system - an augmentation of the baseline, and (3) document the advanced software systems, hooks, and scars which will be necessary to achieve this goal. From this analysis, prototype software is being developed, and will be tested using air and water recovery simulations and hardware subsystems. In addition, the advanced software is being designed, developed, and tested using automation software management plan and lifecycle tools. Automated knowledge acquisition, engineering, verification and testing tools are being used to develop the software. In this way, we can capture ECLSS development knowledge for future use develop more robust and complex software, provide feedback to the knowledge based system tool community, and ensure proper visibility of our efforts.
Symbolic Analysis is a methodology first applied as an aid in selecting and generating test cases for 'white box' type testing of computer software programs. The feasibility of automating this analysis process has recently been demonstrated through the development of a CLIPS-based prototype tool. Symbolic analysis is based on separating the logic flow diagram of a computer program into its basic elements, and then systematically examining those elements and their relationships to provide a detailed static analysis of the process that those diagrams represent. The basic logic flow diagram elements are flow structure (connections), predicates (decisions), and computations (actions). The symbolic analysis approach supplies a disciplined step-by-step process to identify all executable program paths and produce a truth table that defines the input and output domains for each path identified. The resulting truth table is the tool that allows software test cases to be generated in a comprehensive manner to achieve total program path, input domain, and output domain coverage. Since the manual application of symbolic analysis is extremely labor intensive and is itself error prone, automation of the process is highly desirable. Earlier attempts at automation, utilizing conventional software approaches, had only limited success. This paper briefly describes the automation problems, the symbolic analysis expert's problem solving heuristics, and the implementation of those heuristics as a CLIPS based prototype, and the manual augmentation required. A simple application example is also provided for illustration purposes. The paper concludes with a discussion of implementation experiences, automation limitations, usage experiences, and future development suggestions.
The Customer Avionics Interface Development and Analysis (CAIDA) team helps to provide modeling and simulation software for the verification of the Launch Control System (LCS). With a new iteration of telemetry tools being developed, extensive work must be done to ensure features are implemented in an efficient manner. The authors worked to develop new functionalities in the telemetry tools, update documentation, and perform various tests on the CAIDA Advanced Telemetry Tool (CATT). This was accomplished with Python through built-in library frameworks. In addition, work needed to be performed to set up a training document for new engineers and interns joining the team in the future. The outcome of this internship was the completion of several new features, unit and functional tests on CATT, thorough documentation, and a developer’s guide to programming under CAIDA.
This update reports a state-of-the-art discrete ordinate algorithm for monochromatic unpolarized radiative transfer in non-isothermal, vertically inhomogeneous, but horizontally homogeneous media. The physical processes included are Planckian thermal emission, scattering with arbitrary phase function, absorption, and surface bidirectional reflection. The system may be driven by parallel or isotropic diffuse radiation incident at the top boundary, as well as by internal thermal sources and thermal emission from the boundaries. Radiances, fluxes, and mean intensities are returned at user-specified angles and levels. DISORT has enjoyed considerable popularity in the atmospheric science and other communities since its introduction in 1988. Several new DISORT features are described in this update: intensity correction algorithms designed to compensate for the 8-M forward-peak scaling and obtain accurate intensities even in low orders of approximation; a more general surface bidirectional reflection option; and an exponential-linear approximation of the Planck function allowing more accurate solutions in the presence of large temperature gradients. DISORT has been designed to be an exemplar of good scientific software as well as a program of intrinsic utility. An extraordinary effort has been made to make it numerically well-conditioned, error-resistant, and user-friendly, and to take advantage of robust existing software tools. A thorough test suite is provided to verify the program both against published results, and for consistency where there are no published results. This careful attention to software design has been just as important in DISORT's popularity as its powerful algorithmic content.
The Customer Avionics Interface Development and Analysis (CAIDA) team provides modeling and simulation software for the verification of the Launch Control System (LCS). In late 2015, CAIDA began development of the Data Exchange Message (DEM) Generator (DEMGen) and development of the DEM Modifier (DEMMod) in early 2017. DEMGen is able to mimic the telemetry streams normally sent by different simulators allowing increased user control and more telemetry instances. DEMMod takes in a telemetry stream and allows the modification of entire packets or simple measurement values. Together, these tools provide the capabilities to simulate and test complex launch scenarios to ensure LCS is fully prepared for any anomalous behavior during an actual launch. In early 2018, CAIDA began a new project called the CAIDA Advanced Telemetry Tool (CATT), which combined the code and documentation of DEMGen and DEMMod. CATT now allows the integration of new tools into a singular program providing compact and easy access. In the fall of 2018, the author worked with another intern, Antonio Negron, to develop several new CATT features along with proper documentation and unit testing. In the following spring, the author continued that work by integrating the features into CATT, solidifying the documentation, and expanding the testing to cover more cases. The outcome of both semesters includes an inspection engine for automated packet analysis, a packet-masking feature, and a multi-measurement sequencing feature.
The Enhanced Master Controller Unit Tester (EMUT) software is a tool for development and testing of software for a master controller (MC) flight computer. The primary function of the EMUT software is to simulate interfaces between the MC computer and external analog and digital circuitry (including other computers) in a rack of equipment to be used in scientific experiments. The simulations span the range of nominal, off-nominal, and erroneous operational conditions, enabling the testing of MC software before all the equipment becomes available.
Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.
The NASA Langley Research Center (LaRC) Cockpit Motion Facility (CMF) motion base has provided many design and analysis challenges. In the process of addressing these challenges, a comprehensive suite of software tools was developed. The software tools development began with a detailed MATLAB/Simulink model of the motion base which was used primarily for safety loads prediction, design of the closed loop compensator and development of the motion base safety systems1. A Simulink model of the digital control law, from which a portion of the embedded code is directly generated, was later added to this model to form a closed loop system model. Concurrently, software that runs on a PC was created to display and record motion base parameters. It includes a user interface for controlling time history displays, strip chart displays, data storage, and initializing of function generators used during motion base testing. Finally, a software tool was developed for kinematic analysis and prediction of mechanical clearances for the motion system. These tools work together in an integrated package to support normal operations of the motion base, simulate the end to end operation of the motion base system providing facilities for software-in-the-loop testing, mechanical geometry and sensor data visualizations, and function generator setup and evaluation.
Virtual Real Time (VRT) is a computer program for testing embedded flight software by computational simulation in a workstation, in contradistinction to testing it in its target central processing unit (CPU). The disadvantages of testing in the target CPU include the need for an expensive test bed, the necessity for testers and programmers to take turns using the test bed, and the lack of software tools for debugging in a real-time environment. By virtue of its architecture, most of the flight software of the type in question is amenable to development and testing on workstations, for which there is an abundance of commercially available debugging and analysis software tools. Unfortunately, the timing of a workstation differs from that of a target CPU in a test bed. VRT, in conjunction with closed-loop simulation software, provides a capability for executing embedded flight software on a workstation in a close-to-real-time environment. A scale factor is used to convert between execution time in VRT on a workstation and execution on a target CPU. VRT includes high-resolution operating- system timers that enable the synchronization of flight software with simulation software and ground software, all running on different workstations.
Since the early 2000s, a resource management team at Marshall Space Flight Center has developed and improved the Schedule Test and Assessment Tool, a software add-on capable of analyzing, summarizing, and finding logic gaps in project schedules. Companies like Lanham, Maryland-based Vantage Systems Inc. use the tool to manage NASA projects, but it has also been released for free to more than 200 US companies, agencies, and other entities.
Ways in which parallel hardware development and high level requirements changes have influenced Mars Observer Payload Data Subsystem (PDS) flight software development are discussed. Particular attention is given to ways in which the evolving hardware product and changing requirements have led to repeated modification to software requirements, design, code, and test tools and a delay in the closure of corresponding phases of the software development life cycle. Design and implementation problems which were encountered during the PDS software development effort are described.
On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.
In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.