15,624 research outputs found
On Automated Lemma Generation for Separation Logic with Inductive Definitions
Separation Logic with inductive definitions is a well-known approach for
deductive verification of programs that manipulate dynamic data structures.
Deciding verification conditions in this context is usually based on
user-provided lemmas relating the inductive definitions. We propose a novel
approach for generating these lemmas automatically which is based on simple
syntactic criteria and deterministic strategies for applying them. Our approach
focuses on iterative programs, although it can be applied to recursive programs
as well, and specifications that describe not only the shape of the data
structures, but also their content or their size. Empirically, we find that our
approach is powerful enough to deal with sophisticated benchmarks, e.g.,
iterative procedures for searching, inserting, or deleting elements in sorted
lists, binary search tress, red-black trees, and AVL trees, in a very efficient
way
Doctor of Philosophy
dissertationTrusted computing base (TCB) of a computer system comprises components that must be trusted in order to support its security policy. Research communities have identified the well-known minimal TCB principle, namely, the TCB of a system should be as small as possible, so that it can be thoroughly examined and verified. This dissertation is an experiment showing how small the TCB for an isolation service is based on software fault isolation (SFI) for small multitasking embedded systems. The TCB achieved by this dissertation includes just the formal definitions of isolation properties, instruction semantics, program logic, and a proof assistant, besides hardware. There is not a compiler, an assembler, a verifier, a rewriter, or an operating system in the TCB. To the best of my knowledge, this is the smallest TCB that has ever been shown for guaranteeing nontrivial properties of real binary programs on real hardware. This is accomplished by combining SFI techniques and high-confidence formal verification. An SFI implementation inserts dynamic checks before dangerous operations, and these checks provide necessary invariants needed by the formal verification to prove theorems about the isolation properties of ARM binary programs. The high-confidence assurance of the formal verification comes from two facts. First, the verification is based on an existing realistic semantics of the ARM ISA that is independently developed by Cambridge researchers. Second, the verification is conducted in a higher-order proof assistant-the HOL theorem prover, which mechanically checks every verification step by rigorous logic. In addition, the entire verification process, including both specification generation and verification, is automatic. To support proof automation, a novel program logic has been designed, and an automatic reasoning framework for verifying shallow safety properties has been developed. The program logic integrates Hoare-style reasoning and Floyd's inductive assertion reasoning together in a small set of definitions, which overcomes shortcomings of Hoare logic and facilitates proof automation. All inference rules of the logic are proven based on the instruction semantics and the logic definitions. The framework leverages abstract interpretation to automatically find function specifications required by the program logic. The results of the abstract interpretation are used to construct the function specifications automatically, and the specifications are proven without human interaction by utilizing intermediate theorems generated during the abstract interpretation. All these work in concert to create the very small TCB
Deductive formal verification of embedded systems
We combine static analysis techniques with model-based deductive verification using SMT solvers to provide a framework that, given an analysis aspect of the source code, automatically generates an analyzer capable of inferring information about that aspect.
The analyzer is generated by translating the collecting semantics of a program to a formula in first order logic over multiple underlying theories. We import the semantics of the API invocations as first order logic assertions. These assertions constitute the models used by the analyzer. Logical specification of the desired program behavior is incorporated as a first order logic formula. An SMT-LIB solver treats the combined formula as a constraint and solves it. The solved form can be used to identify logical and security errors in embedded programs. We have used this framework to analyze Android applications and MATLAB code.
We also report the formal verification of the conformance of the open source Netgear WNR3500L wireless router firmware implementation to the RFC 2131. Formal verification of a software system is essential for its deployment in mission-critical environments. The specifications for the development of routers are provided by RFCs that are only described informally in English. It is prudential to ensure that a router firmware conforms to its corresponding RFC before it can be deployed for managing mission-critical networks. The formal verification process demonstrates the usefulness of inductive types and higher-order logic in software certification
Model checking for symbolic-heap separation logic with inductive predicates
We investigate the model checking problem for symbolic-heap separation logic with user-defined inductive predicates, i.e., the problem of checking that a given stack-heap memory state satisfies a given formula in this language, as arises e.g. in software testing or runtime verification.
First, we show that the problem is decidable; specifically, we present a bottom-up fixed point algorithm that decides the problem and runs in exponential time in the size of the problem instance.
Second, we show that, while model checking for the full language is EXPTIME-complete, the problem becomes NP-complete or PTIME-solvable when we impose natural syntactic restrictions on the schemata defining the inductive predicates. We additionally present NP and PTIME algorithms for these restricted fragments.
Finally, we report on the experimental performance of our procedures on a variety of specifications extracted from programs, exercising multiple combinations of syntactic restrictions
Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis
Even with impressive advances in automated formal methods, certain problems
in system verification and synthesis remain challenging. Examples include the
verification of quantitative properties of software involving constraints on
timing and energy consumption, and the automatic synthesis of systems from
specifications. The major challenges include environment modeling,
incompleteness in specifications, and the complexity of underlying decision
problems.
This position paper proposes sciduction, an approach to tackle these
challenges by integrating inductive inference, deductive reasoning, and
structure hypotheses. Deductive reasoning, which leads from general rules or
concepts to conclusions about specific problem instances, includes techniques
such as logical inference and constraint solving. Inductive inference, which
generalizes from specific instances to yield a concept, includes algorithmic
learning from examples. Structure hypotheses are used to define the class of
artifacts, such as invariants or program fragments, generated during
verification or synthesis. Sciduction constrains inductive and deductive
reasoning using structure hypotheses, and actively combines inductive and
deductive reasoning: for instance, deductive techniques generate examples for
learning, and inductive reasoning is used to guide the deductive engines.
We illustrate this approach with three applications: (i) timing analysis of
software; (ii) synthesis of loop-free programs, and (iii) controller synthesis
for hybrid systems. Some future applications are also discussed
Model checking for symbolic-heap separation logic with inductive predicates
We investigate the *model checking* problem for symbolic-heap separation logic with user-defined inductive predicates, i.e., the problem of checking that a given stack-heap memory state satisfies a given formula in this language, as arises e.g. in software testing or runtime verification. First, we show that the problem is *decidable*; specifically, we present a bottom-up fixed point algorithm that decides the problem and runs in exponential time in the size of the problem instance. Second, we show that, while model checking for the full language is EXPTIME-complete, the problem becomes NP-complete or PTIME-solvable when we impose natural syntactic restrictions on the schemata defining the inductive predicates. We additionally present NP and PTIME algorithms for these restricted fragments. Finally, we report on the experimental performance of our procedures on a variety of specifications extracted from programs, exercising multiple combinations of syntactic restrictions
Invariant Synthesis for Incomplete Verification Engines
We propose a framework for synthesizing inductive invariants for incomplete
verification engines, which soundly reduce logical problems in undecidable
theories to decidable theories. Our framework is based on the counter-example
guided inductive synthesis principle (CEGIS) and allows verification engines to
communicate non-provability information to guide invariant synthesis. We show
precisely how the verification engine can compute such non-provability
information and how to build effective learning algorithms when invariants are
expressed as Boolean combinations of a fixed set of predicates. Moreover, we
evaluate our framework in two verification settings, one in which verification
engines need to handle quantified formulas and one in which verification
engines have to reason about heap properties expressed in an expressive but
undecidable separation logic. Our experiments show that our invariant synthesis
framework based on non-provability information can both effectively synthesize
inductive invariants and adequately strengthen contracts across a large suite
of programs
Model Checking Linear Logic Specifications
The overall goal of this paper is to investigate the theoretical foundations
of algorithmic verification techniques for first order linear logic
specifications. The fragment of linear logic we consider in this paper is based
on the linear logic programming language called LO enriched with universally
quantified goal formulas. Although LO was originally introduced as a
theoretical foundation for extensions of logic programming languages, it can
also be viewed as a very general language to specify a wide range of
infinite-state concurrent systems.
Our approach is based on the relation between backward reachability and
provability highlighted in our previous work on propositional LO programs.
Following this line of research, we define here a general framework for the
bottom-up evaluation of first order linear logic specifications. The evaluation
procedure is based on an effective fixpoint operator working on a symbolic
representation of infinite collections of first order linear logic formulas.
The theory of well quasi-orderings can be used to provide sufficient conditions
for the termination of the evaluation of non trivial fragments of first order
linear logic.Comment: 53 pages, 12 figures "Under consideration for publication in Theory
and Practice of Logic Programming
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