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Abstract. The introduction of Past Operators enables to produce more natural formulation of a wide class of properties of reactive systems, compared to traditional pure future temporal logics. For this reason, past temporal logics are gaining increasing interest in several application areas, ranging from Requirement Engineering to Formal Verification and Model Checking. We show how SAT-based Bounded Model Checking techniques can be extended to deal with Linear Temporal Logics with Past Operators (PLTL). Though apparently simple, this task turns out to be absolutely non-trivial when tackled in its full generality. We discuss a bounded semantics for PLTL, we show that it is correct (and complete), and propose an encoding scheme able to cope with PLTL formulas. Finally, we implement the encoding in NuSMV, and present a first experimental evaluation of the approach.

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The language of Quantified Boolean Formulas (QBF) has a lot of potential applications to Formal Verification (FV) tasks, as it captures many of these tasks in a natural and compact way. Practical experience has been disappointing though. When compared with contending approaches such as SAT, QBF-based FV has invariably yielded unfavorable experimental results. This paper makes two contributions. We first provide an account of the status quo in QBF-based FV. We examine commonly adopted formalizations and the relative strengths of different decision procedures. In the second part of this paper, we investigate for the first time the relevance of some advanced QBF techniques to FV tasks. In particular, we describe the use and the benefits of restricted quantifiers, QBF certificates, alternative encodings for classical model checking problems, and encodings with free variables. These promising research perspectives seem to reverse the negative standing of QBF applied to FV, as confirmed by the experimental evidence we discuss. Experiments are conducted by extending the publicly available solver sKizzo in several ways, and they include the first case studies where QBF compares favorably to SAT, its traditional competitor. QBF turns out to be an order of magnitude faster than SAT in some tasks (e.g., automated design debugging of large circuits). Moreover, as the size of the problems grows, the SAT encodings result in excessive memory requirements leading to out-of-memory conditions, while the more compact QBF encodings continue to be manageable and solvable.