13th International Conference on Tools and Algorithms for the Construction and Analysis of Systems

TACAS is a forum for researchers, developers and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference serves to bridge the gaps between different communities that share common interests in, and techniques for, tool development and its algorithmic foundations. The research areas covered by such communities include but are not limited to formal methods, software and hardware verification, static analysis, programming languages, software engineering, real-time systems, communications protocols, and biological systems. The TACAS forum provides a venue for such communities at which common problems, heuristics, algorithms, data structures and methodologies can be discussed and explored. In doing so, TACAS aims to support researchers in their quest to improve the utility, reliability, flexibility and efficiency of tools and algorithms for building systems.
Tool descriptions and case studies with a conceptual message, as well as theoretical papers with clear relevance for tool construction are all encouraged. The specific topics covered by the conference include, but are not limited to, the following:
* Specification and verification techniques for finite and
infinite-state systems
* Software and hardware verification
* Theorem-proving and model-checking
* System construction and transformation techniques
* Static and run-time analysis
* Abstraction techniques for modeling and validation
* Compositional and refinement-based methodologies
* Testing and test-case generation
* Analytical techniques for secure, real-time, hybrid, critical,
biological or dependable systems
* Integration of formal methods and static analysis in high-level
hardware design or software environments
* Tool environments and tool architectures
* SAT solvers
* Applications and case studies
As TACAS addresses a heterogeneous audience, potential authors are strongly encouraged to write about their ideas and findings in general and jargon- independent, rather than in application- and domain-specific, terms. Authors reporting on tools or case studies are strongly encouraged to indicate how their experimental results can be reproduced and confirmed independently.