No description available.

Because of the importance of undecidability and the concern with the high complexity of automated reasoning, a few interval-based temporal description logics (ITDLs) have been designed. Moreover, most existing ITDLs are not able to specify the lengths of intervals. In other words, they are not metric. On the other hand, some domains (e.g., medicine) are inherently interval-based, and require a metric logic in order to formalize defined processes and to check process consistency. Hence, a metric interval-based temporal description logic is required. In this thesis, we introduce such a logic (MITDL) along with two algorithms for the satisfiability checking of its formulas. We first introduce an interval-based temporal logic, called IMPNL, inspired by Metric Propositional Neighbourhood Logic. We also present a sound, com- plete and terminating tableau-based algorithm for checking the satisfiability of IMPNL formulas. Afterwards, we combine a restricted version of IMPNL (IMPNL without a negation operator) with the ALC description logic to form a MITDL. We propose two tableau-based algorithms for checking the satisfia- bility of MITDL formulas. We show and prove they are sound, complete and terminate. These algorithms have PSpace and 2NExp-Time complexities. As a proof of concept, we use IMPNL and MITDL to model some clinical practice guidelines (CPG) and check their consistency. We compare MITDL with several languages commonly used for modeling CPGs. / Thesis / Doctor of Science (PhD)

Formal verification techniques are growing increasingly vital for the development of safety-critical software and hardware in practice. Techniques such as requirements-based design and model checking for system verification have been successfully used to verify systems for air traffic control, airplane separation assurance, autopilots, CPU logic designs, life-support, medical equipment, and other functions that ensure human safety. Formal behavioral specifications written early in the system-design process and communicated across all design phases increase the efficiency, consistency, and quality of the system under development. We argue that to prevent introducing design or verification errors, it is crucial to test specifications for satisfiability. We advocate for the adaptation of a new sanity check via satisfiability checking for property assurance. Our focus here is on specifications expressed in Linear Temporal Logic (LTL). We demonstrate that LTL satisfiability checking reduces to model checking and satisfiability checking for the specification, its complement, and a conjunction of all properties should be performed as a first step to LTL model checking. We report on an experimental investigation of LTL satisfiability checking. We introduce a large set of rigorous benchmarks to enable objective evaluation of LTL-to-automaton algorithms in terms of scalability, performance, correctness, and size of the automata produced. For explicit model checking, we use the Spin model checker; we tested all LTL-to-explicit automaton translation tools that were publicly available when we conducted our study. For symbolic model checking, we use CadenceSMV, NuSMV, and SAL-SMC for both LTL-to-symbolic automaton translation and to perform the satisfiability check. Our experiments result in two major findings. First, scalability, correctness, and other debilitating performance issues afflict most LTL translation tools. Second, for LTL satisfiability checking, the symbolic approach is clearly superior to the explicit approach. Ironically, the explicit approach to LTL-to-automata had been heavily studied while only one algorithm existed for LTL-to-symbolic automata. Since 1994, there had been essentially no new progress in encoding symbolic automata for BDD-based analysis. Therefore, we introduce a set of 30 symbolic automata encodings. The set consists of novel combinations of existing constructs, such as different LTL formula normal forms, with a novel transition-labeled symbolic automaton form, a new way to encode transitions, and new BDD variable orders based on algorithms for tree decomposition of graphs. An extensive set of experiments demonstrates that these encodings translate to significant, sometimes exponential, improvement over the current standard encoding for symbolic LTL satisfiability checking. Building upon these ideas, we return to the explicit automata domain and focus on the most common type of specifications used in industrial practice: safety properties. We show that we can exploit the inherent determinism of safety properties to create a set of 26 explicit automata encodings comprised of novel aspects including: state numbers versus state labels versus a state look-up table, finite versus infinite acceptance conditions, forward-looking versus backward-looking transition encodings, assignment-based versus BDD-based alphabet representation, state and transition minimization, edge abbreviation, trap-state elimination, and determinization either on-the-fly or up-front using the subset construction. We conduct an extensive experimental evaluation and identify an encoding that offers the best performance in explicit LTL model checking time and is constantly faster than the previous best explicit automaton encoding algorithm.