More Like this

1. Modular Answer Set Programming as a Formal Specification Language

   https://doi.org/10.1017/S1471068420000265  

   CABALAR, PEDRO; FANDINNO, JORGE; LIERLER, YULIYA (September 2020, Theory and Practice of Logic Programming)

   null (Ed.)

   Abstract In this paper, we study the problem of formal verification for Answer Set Programming (ASP), namely, obtaining a formal proof showing that the answer sets of a given (non-ground) logic program P correctly correspond to the solutions to the problem encoded by P , regardless of the problem instance. To this aim, we use a formal specification language based on ASP modules, so that each module can be proved to capture some informal aspect of the problem in an isolated way. This specification language relies on a novel definition of (possibly nested, first order) program modules that may incorporate local hidden atoms at different levels. Then, verifying the logic program P amounts to prove some kind of equivalence between P and its modular specification. 

   more » « less
2. Towards Building Verifiable CPS using Lingua Franca

   https://doi.org/10.1145/3609134  

   Lin, Shaokai; Manerkar, Yatin A.; Lohstroh, Marten; Polgreen, Elizabeth; Yu, Sheng-Jung; Jerad, Chadlia; Lee, Edward A.; Seshia, Sanjit A. (October 2023, ACM Transactions on Embedded Computing Systems)

   Formal verification of cyber-physical systems (CPS) is challenging because it has to consider real-time and concurrency aspects that are often absent in ordinary software. Moreover, the software in CPS is often complex and low-level, making it hard to assure that a formal model of the system used for verification is a faithful representation of the actual implementation, which can undermine the value of a verification result. To address this problem, we propose a methodology for building verifiable CPS based on the principle that a formal model of the software can be derivedautomaticallyfrom its implementation. Our approach requires that the system implementation is specified inLingua Franca(LF), a polyglot coordination language tailored for real-time, concurrent CPS, which we made amenable to the specification of safety properties via annotations in the code. The program structure and the deterministic semantics of LF enable automatic construction of formal axiomatic models directly from LF programs. The generated models are automatically checked using Bounded Model Checking (BMC) by the verification engineUclid5using theZ3SMT solver. The proposed technique enables checking a well-defined fragment of Safety Metric Temporal Logic (Safety MTL) formulas. To ensure the completeness of BMC, we present a method to derive an upper bound on the completeness threshold of an axiomatic model based on the semantics of LF. We implement our approach in the LF Verifierand evaluate it using a benchmark suite with 22 programs sampled from real-life applications and benchmarks for Erlang, Lustre, actor-oriented languages, and RTOSes. The LF Verifiercorrectly checks 21 out of 22 programs automatically. 

   more » « less
3. Deductive Synthesis of Reinforcement Learning Agents for Infinite Horizon Tasks

   Wang, Yuning; Zhu, He (July 2025, 37th International Conference on Computer Aided Verification (CAV))

   We propose a deductive synthesis framework for construct- ing reinforcement learning (RL) agents that provably satisfy temporal reach-avoid specifications over infinite horizons. Our approach decomposes these temporal specifications into a sequence of finite-horizon subtasks, for which we synthesize individual RL policies. Using formal verification techniques, we ensure that the composition of a finite number of subtask policies guarantees satisfaction of the overall specification over infinite horizons. Experimental results on a suite of benchmarks show that our synthesized agents outperform standard RL methods in both task performance and compliance with safety and temporal requirements. 

   more » « less
4. Deductive Synthesis of Reinforcement Learning Agents for Infinite Horizon Tasks

   https://doi.org/10.1007/978-3-031-98685-7_4  

   Wang, Yuning; Zhu, He (July 2025, Springer Nature Switzerland)

   Abstract We propose a deductive synthesis framework for constructing reinforcement learning (RL) agents that provably satisfy temporal reach-avoid specifications over infinite horizons. Our approach decomposes these temporal specifications into a sequence of finite-horizon subtasks, for which we synthesize individual RL policies. Using formal verification techniques, we ensure that the composition of a finite number of subtask policies guarantees satisfaction of the overall specification over infinite horizons. Experimental results on a suite of benchmarks show that our synthesized agents outperform standard RL methods in both task performance and compliance with safety and temporal requirements. 

   more » « less
5. MLTL Multi-type: A Typed Logic for Cyber-Physical Systems

   https://doi.org/10.1145/3704809  

   Hariharan, Gokul; Kempa, Brian; Wongpiromsarn, Tichakorn; Jones, Phillip; Rozier, Kristin (November 2024, ACM Transactions on Embedded Computing Systems)

   Modern cyber-physical systems-of-systems (CPSoS) operate in complex systems-of-systems that must seamlessly work together to control safety- or mission-critical functions. Linear Temporal Logic (LTL) and Mission-time Linear Temporal logic (MLTL) intuitively express CPSoS requirements for automated system verification and validation. However, both LTL and MLTL presume that all signals populating the variables in a formula are sampled over the same rate and type (e.g., time or distance), and agree on a standard “time” step. Formal verification of cyber-physical systems-of-systems needs validate-able requirements expressed over (sub-)system signals of different types, such as signals sampled at different timescales, distances, or levels of abstraction, expressed in the same formula. Previous works developed more expressive logics to account for types (e.g., timescales) by sacrificing the intuitive simplicity of LTL. However, a legible direct one-to-one correspondence between a verbal and formal specification will ease validation, reduce bugs, increase productivity, and linearize the workflow from a project’s conception to actualization. Validation includes both transparency for human interpretation, and tractability for automated reasoning, as CPSoS often run on resource-limited embedded systems. To address these challenges, we introduced Mission-time Linear Temporal Logic Multi-type (Hariharan et al., Numerical Software Verification Workshop, 2022), a logic building on MLTL. MLTLM enables writing formal requirements over finite input signals (e.g., sensor signals and local computations) of different types, while maintaining the same simplicity as LTL and MLTL. Furthermore, MLTLM maintains a direct correspondence between a verbal requirement and its corresponding formal specification. Additionally, reasoning a formal specification in the intended type (e.g., hourly for an hourly rate, and per second for a seconds rate) will use significantly less memory in resource-constrained hardware. This article extends the previous work with (1) many illustrated examples on types (e.g., time and space) expressed in the same specification, (2) proofs omitted for space in the workshop version, (3) proofs of succinctness of MLTLM compared to MLTL, and (4) a minimal translation to MLTL of optimal length. 

   more » « less