We introduce the notion of local completeness in abstract interpretation and define a logic for proving both the correctness and incorrectness of some program specification. Abstract interpretation ...is extensively used to design sound-by-construction program analyses that over-approximate program behaviours. Completeness of an abstract interpretation A for all possible programs and inputs would be an ideal situation for verifying correctness specifications, because the analysis can be done compositionally and no false alert will arise. Our first result shows that the class of programs whose abstract analysis on A is complete for all inputs has a severely limited expressiveness. A novel notion of local completeness weakens the above requirements by considering only some specific, rather than all, program inputs and thus finds wider applicability. In fact, our main contribution is the design of a proof system, parameterized by an abstraction A, that, for the first time, combines over- and under-approximations of program behaviours. Thanks to local completeness, in a provable triple ⊢A P c Q, the assertion Q is an under-approximation of the strongest post-condition postc(P) such that the abstractions in A of Q and postc(P) coincide. This means that Q is never too coarse, namely, under mild assumptions, the abstract interpretation of c does not yield false alerts for the input P iff Q has no alert. Thus, ⊢A P c Q not only ensures that all the alerts raised in Q are true ones, but also that if Q does not raise alerts then c is correct.
Most techniques to detect program errors, such as testing, code reviews, and static program analysis, do not fully verify all possible executions of a program. They leave executions unverified when ...they do not check certain properties, fail to verify properties, or check properties under certain unsound assumptions such as the absence of arithmetic overflow. In this paper, we present a technique to complement partial verification results by automatic test case generation. In contrast to existing work, our technique supports the common case that the verification results are based on unsound assumptions. We annotate programs to reflect which executions have been verified, and under which assumptions. These annotations are then used to guide dynamic symbolic execution toward unverified program executions. Our main technical contribution is a code instrumentation that causes dynamic symbolic execution to abort tests that lead to verified executions, to prune parts of the search space, and to prioritize tests that cover more properties that are not fully verified. We have implemented our technique for the .NET static analyzer Clousot and the dynamic symbolic execution tool Pex. It produces smaller test suites (by up to 19.2%), covers more unverified executions (by up to 7.1%), and reduces testing time (by up to 52.4%) compared to combining Clousot and Pex without our technique.
A smart contract is a computer program that allows users to automate their actions on the blockchain platform. Given the significance of smart contracts in supporting important activities across ...industry sectors including supply chain, finance, legal, and medical services, there is a strong demand for verification and validation techniques. Yet, the vast majority of smart contracts lack any kind of formal specification, which is essential for establishing their correctness. In this survey, we investigate formal models and specifications of smart contracts presented in the literature and present a systematic overview to understand the common trends. We also discuss the current approaches used in verifying such property specifications and identify gaps with the hope to recognize promising directions for future work.
CoVeriTeam Service: Verification as a Service Beyer, Dirk; Kanav, Sudeep; Wachowitz, Henrik
2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion),
05/2023
Conference Proceeding
Odprti dostop
The research community has developed numerous tools for solving verification problems, but we are missing a common web interface for executing them. This means, users have to commit to install and ...execute each new tool (version) on their local machine. We propose to use CoVeriTeam Service to make it easy for verification researchers to experiment with new verification tools. CoVeriTeam has already unified the command-line interface, and reduced the burden by taking care of tool installation and isolated execution. The new web service in addition enables tool developers to make their tools accessible on the web and users to include verification tools in their work flow. There are already further applications of our service: The 2023 competitions on software verification and testing used the service for their integration testing, and we propose to use CoVeriTeam Service for incremental verification as part of a continuous-integration process.
Demonstration video: https://youtu.be/0Ao0ZogSu1U
Demonstration service: https://coveriteam-service.sosy-lab.org
Efficient sampling of SAT solutions for testing Dutra, Rafael; Laeufer, Kevin; Bachrach, Jonathan ...
2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE),
05/2018
Conference Proceeding
Odprti dostop
In software and hardware testing, generating multiple inputs which satisfy a given set of constraints is an important problem with applications in fuzz testing and stimulus generation. However, it is ...a challenge to perform the sampling efficiently, while generating a diverse set of inputs which satisfy the constraints. We developed a new algorithm QuickSampler which requires a small number of solver calls to produce millions of samples which satisfy the constraints with high probability. We evaluate QuickSampler on large real-world benchmarks and show that it can produce unique valid solutions orders of magnitude faster than other state-of-the-art sampling tools, with a distribution which is reasonably close to uniform in practice.
Android smartphones are becoming increasingly popular. The open nature of Android allows users to install miscellaneous applications, including the malicious ones, from third-party marketplaces ...without rigorous sanity checks. A large portion of existing malwares perform stealthy operations such as sending short messages, making phone calls and HTTP connections, and installing additional malicious components. In this paper, we propose a novel technique to detect such stealthy behavior. We model stealthy behavior as the program behavior that mismatches with user interface, which denotes the user's expectation of program behavior. We use static program analysis to attribute a top level function that is usually a user interaction function with the behavior it performs. Then we analyze the text extracted from the user interface component associated with the top level function. Semantic mismatch of the two indicates stealthy behavior. To evaluate AsDroid, we download a pool of 182 apps that are potentially problematic by looking at their permissions. Among the 182 apps, AsDroid reports stealthy behaviors in 113 apps, with 28 false positives and 11 false negatives.
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