Abstraction in directed model checking

Abstraction is one of the most important issues to cope with large and infinite state spaces in model checking and to reduce the verification efforts. The abstract system is smaller than the original one and if the abstract system satisfies a correctness specification, so does the concrete one. However, abstractions may introduce a behavior violating the specification that is not present in the original system. This paper bypasses this problem by proposing the combination of abstraction with heuristic search to improve error detection. The abstract system is explored in order to create a database that stores the exact distances from abstract states to the set of abstract error states. To check, whether or not the abstract behavior is present in the original system, effcient exploration algorithms exploit the database as a guidance

Differentially Testing Soundness and Precision of Program Analyzers

In the last decades, numerous program analyzers have been developed both by academia and industry. Despite their abundance however, there is currently no systematic way of comparing the effectiveness of different analyzers on arbitrary code. In this paper, we present the first automated technique for differentially testing soundness and precision of program analyzers. We used our technique to compare six mature, state-of-the art analyzers on tens of thousands of automatically generated benchmarks. Our technique detected soundness and precision issues in most analyzers, and we evaluated the implications of these issues to both designers and users of program analyzers

SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer

We describe and evaluate a bug refutation extension for the Clang Static Analyzer (CSA) that addresses the limitations of the existing built-in constraint solver. In particular, we complement CSA's existing heuristics that remove spurious bug reports. We encode the path constraints produced by CSA as Satisfiability Modulo Theories (SMT) problems, use SMT solvers to precisely check them for satisfiability, and remove bug reports whose associated path constraints are unsatisfiable. Our refutation extension refutes spurious bug reports in 8 out of 12 widely used open-source applications; on average, it refutes ca. 7% of all bug reports, and never refutes any true bug report. It incurs only negligible performance overheads, and on average adds 1.2% to the runtime of the full Clang/LLVM toolchain. A demonstration is available at {\tt https://www.youtube.com/watch?v=ylW5iRYNsGA}.Comment: 4 page

Towards Vulnerability Discovery Using Staged Program Analysis

Eliminating vulnerabilities from low-level code is vital for securing software. Static analysis is a promising approach for discovering vulnerabilities since it can provide developers early feedback on the code they write. But, it presents multiple challenges not the least of which is understanding what makes a bug exploitable and conveying this information to the developer. In this paper, we present the design and implementation of a practical vulnerability assessment framework, called Melange. Melange performs data and control flow analysis to diagnose potential security bugs, and outputs well-formatted bug reports that help developers understand and fix security bugs. Based on the intuition that real-world vulnerabilities manifest themselves across multiple parts of a program, Melange performs both local and global analyses. To scale up to large programs, global analysis is demand-driven. Our prototype detects multiple vulnerability classes in C and C++ code including type confusion, and garbage memory reads. We have evaluated Melange extensively. Our case studies show that Melange scales up to large codebases such as Chromium, is easy-to-use, and most importantly, capable of discovering vulnerabilities in real-world code. Our findings indicate that static analysis is a viable reinforcement to the software testing tool set.Comment: A revised version to appear in the proceedings of the 13th conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), July 201

Boosting Multi-Core Reachability Performance with Shared Hash Tables

This paper focuses on data structures for multi-core reachability, which is a key component in model checking algorithms and other verification methods. A cornerstone of an efficient solution is the storage of visited states. In related work, static partitioning of the state space was combined with thread-local storage and resulted in reasonable speedups, but left open whether improvements are possible. In this paper, we present a scaling solution for shared state storage which is based on a lockless hash table implementation. The solution is specifically designed for the cache architecture of modern CPUs. Because model checking algorithms impose loose requirements on the hash table operations, their design can be streamlined substantially compared to related work on lockless hash tables. Still, an implementation of the hash table presented here has dozens of sensitive performance parameters (bucket size, cache line size, data layout, probing sequence, etc.). We analyzed their impact and compared the resulting speedups with related tools. Our implementation outperforms two state-of-the-art multi-core model checkers (SPIN and DiVinE) by a substantial margin, while placing fewer constraints on the load balancing and search algorithms.Comment: preliminary repor