Fast Automatic Verification of Large-Scale Systems with Lookup Tables

Modern safety-critical systems are difficult to formally verify, largely due to their large scale. In particular, the widespread use of lookup tables in embedded systems across diverse industries, such as aeronautics and automotive systems, create a critical obstacle to the scalability of formal verification. This paper presents a novel approach for the formal verification of large-scale systems with lookup tables. We use a learning-based technique to automatically learn abstractions of the lookup tables and use the abstractions to then prove the desired property. If the verification fails, we propose a falsification heuristic to search for a violation of the specification. In contrast with previous work on lookup table verification, our technique is completely automatic, making it ideal for deployment in a production environment. To our knowledge, our approach is the only technique that can automatically verify large-scale systems lookup with tables. We illustrate the effectiveness of our technique on a benchmark which cannot be handled by the commercial tool SLDV, and we demonstrate the performance improvement provided by our technique

Osiris: A Tool for Abstraction and Verification of Control Software with Lookup Tables

Some industrial systems are difficult to formally verify due to their large scale. In particular, the widespread use of lookup tables in embedded systems across diverse industries, such as aeronautics and automotive systems, create a critical obstacle to the scalability of formal verification. This paper presents Osiris, a tool that automatically computes abstractions of lookup tables. Osiris uses these abstractions to verify a property in first order logic. If the verification fails, Osiris uses a falsification heuristic to search for a violation of the specification. We validate our technique on a public benchmark of an adaptive cruise controller with lookup tables

Fast Automatic Verification of Large-Scale Systems with Lookup Tables

Modern safety-critical systems are difficult to formally verify, largely due to their large scale. In particular, the widespread use of lookup tables in embedded systems across diverse industries, such as aeronautics and automotive systems, create a critical obstacle to the scalability of formal verification. This paper presents a novel approach for the formal verification of large-scale systems with lookup tables. We use a learning-based technique to automatically learn abstractions of the lookup tables and use the abstractions to then prove the desired property. If the verification fails, we propose a falsification heuristic to search for a violation of the specification. In contrast with previous work on lookup table verification, our technique is completely automatic, making it ideal for deployment in a production environment. To our knowledge, our approach is the only technique that can automatically verify large-scale systems lookup with tables. We illustrate the effectiveness of our technique on a benchmark which cannot be handled by the commercial tool SLDV, and we demonstrate the performance improvement provided by our technique

Pivalic acid assisted Biginelli reaction for synthesis of dihydropyrimidinones and dihydrothiopyrimidinones

Herein is provided an alternate, simple, multigram scale, efficient route for Biginelli reaction for synthesis of dihydropyrimidinones using urea, ethylacetatoacetate, and benzaldehyde with pivalic acid

Pivalic acid assisted Biginelli reaction for synthesis of dihydropyrimidinones and dihydrothiopyrimidinones

677-681Herein is provided an alternate, simple, multigram scale, efficient route for Biginelli reaction for synthesis of dihydropyrimidinones using urea, ethylacetatoacetate, and benzaldehyde with pivalic acid