Automated Test Generation for Performance Portable Programs Using Clang/LLVM and Formal Methods .
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Literature on the specification, design, verification, testing, and evaluation of avionics systems was surveyed, providing 655 citations. Journal papers, conference papers, and technical reports are included. Manual and computer-based methods were employed. Keywords used in the online search are listed.
One of the most basic questions anyone can ask is, 'How do I know that what I think I know is true?' The study of this question is called epistemology. Traditionally, epistemology has been considered to be of legitimate interest only to philosophers, theologians, and three year old children who respond to every statement by asking, 'Why?' Software engineers need to be interested in the subject, however, because a lack of sufficient understanding of epistemology contributes to many of the current problems in the field.
Reverse engineering of program code is the process of constructing a higher level abstraction of an implementation in order to facillitate the understanding of a system that may be in a.
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In this position statement I briefly describe how the software reliability problem has changed over the years, and the primary reasons for the recent creation of the Laboratory for Reliable Software at JPL.
A technique based on the use of a quantifier elimination decision procedure for real closed fields and simple theorem proving to construct a series of successively finer qualitative abstractions of hybrid automata is taught. The resulting abstractions are always discrete transition systems which can then be used by any traditional analysis tool. The constructed abstractions are conservative and can be used to establish safety properties of the original system. The technique works on linear and non-linear polynomial hybrid systems: the guards on discrete transitions and the continuous flows in all modes can be specified using arbitrary polynomial expressions over the continuous variables. An exemplar tool in the SAL environment built over the theorem prover PVS is detailed. The technique scales well to large and complex hybrid systems.
NASA is investigating new paradigms for future space exploration, heavily focused on the (still) emerging technologies of autonomous and autonomic systems [47, 48, 49]. Missions that rely on multiple, smaller, collaborating spacecraft, analogous to swarms in nature, are being investigated to supplement and complement traditional missions that rely on one large spacecraft [16]. The small spacecraft in such missions would each be able to operate on their own to accomplish a part of a mission, but would need to interact and exchange information with the other spacecraft to successfully execute the mission.
The invention relates to the use of model checkers to generate efficient test sets for hardware and software systems. The method provides for extending existing tests to reach new coverage targets; searching *to* some or all of the uncovered targets in parallel; searching in parallel *from* some or all of the states reached in previous tests; and slicing the model relative to the current set of coverage targets. The invention provides efficient test case generation and test set formation. Deep regions of the state space can be reached within allotted time and memory. The approach has been applied to use of the model checkers of SRI's SAL system and to model-based designs developed in Stateflow. Stateflow models achieving complete state and transition coverage in a single test case are reported.
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Requirements and design specifications are a high priority candidate for better software engineering techniques. Most hazardous software safety errors found during system integration and test of two NASA spacecraft were the result of requirements discrepancies or interface specifications. The highest density of major defects found through the use of software inspections was during the requirements phase. This was seven times higher than the density of major defects found in code inspections. Requirements errors are between 10 and 100 times more costly to fix at later phases of the software lifecycle than at the requirements phase itself. One study found that early lifecycle errors are the most likely to lead to catastrophic failures.
Correctness is paramount for safety-critical software control systems. Critical software failures in medical radiation treatment, communications, and defencse are familiar to the public.
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Automated planning systems (APS) are gaining acceptance for use on NASA missions as evidenced by APS flown On missions such as Orbiter and Deep Space 1 both of which were commanded by onboard planning systems. The planning system takes high level goals and expands them onboard into a detailed of action fiat the spacecraft executes. The system must be verified to ensure that the automatically generated plans achieve the goals as expected and do not generate actions that would harm the spacecraft or mission. These systems are typically tested using empirical methods. Formal methods, such as model checking, offer exhaustive or measurable test coverage which leads to much greater confidence in correctness. This paper describes a formal method based on the SPIN model checker. This method guarantees that possible plans meet certain desirable properties. We express the input model in Promela, the language of SPIN and express the properties of desirable plans formally.
The DARPA Assured Micropatching (AMP) program focuses on creating the capability for rapid patching of legacy binaries in mission critical systems leveraging the field of formal methods. NREL's Cyber Resilient TLDRD effort, focuses on leveraging the field of formal methods to develop tools and methods for formally verifiable implementations of security architectures such as Zero Trust Architecture. The presentation at the DARPA AMP PI meeting is primarily inspired by common interests and ongoing work on leveraging Formal Methods for OT cybersecurity.
The First Tri-Lab Workshop on Formal Verification was held in Santa Fe, New Mexico, on December 5th, 2023. This workshop gathered staff from Sandia, Los Alamos, and Lawrence Livermore National Laboratories and NASA’s Jet Propulsion Laboratory. This report summarizes and expands on the presentations given and discussion had at this workshop. In this report, we describe the current capabilities and research needs related to formal methods at the NNSA labs. In particular, we identify medium-term and long-term research gaps in programming languages, formalization efforts of complex systems, embedded systems verification, hardware verification, cybersecurity, formal methods usability, workflows, numerical methods, the use of formal methods for artificial intelligence (and its converse, artificial intelligence for formal methods), and collaboration opportunities and considerations on these topics. We conclude with a small number of exemplar research problems related to these topics.
A brief example of the use of formal methods techniques in the specification of a software system is presented. The report is part of a larger effort targeted at defining a formal methods pilot project for NASA. One possible application domain that may be used to demonstrate the effective use of formal methods techniques within the NASA environment is presented. It is not intended to provide a tutorial on either formal methods techniques or the application being addressed. It should, however, provide an indication that the application being considered is suitable for a formal methods by showing how such a task may be started. The particular system being addressed is the Structured File Services (SFS), which is a part of the Data Storage and Retrieval Subsystem (DSAR), which in turn is part of the Data Management System (DMS) onboard Spacestation Freedom. This is a software system that is currently under development for NASA. An informal mathematical development is presented. Section 3 contains the same development using Penelope (23), an Ada specification and verification system. The complete text of the English version Software Requirements Specification (SRS) is reproduced in Appendix A.