Martina Seidl

A survey on model versioning approaches

Purpose – The purpose of this paper is to provide a feature‐based characterization of version control systems (VCSs), providing an overview about the state‐of‐the‐art of versioning systems dedicated to modeling artifacts.Design/methodology/approach – Based on a literature study of existing approaches, a description of the features of versioning systems is established. Special focus is set on three‐way merging which is an integral component of optimistic versioning. This characterization is employed on current model versioning systems, which allows the derivation of challenges in this research area.Findings – The results of the evaluation show that several challenges need to be addressed in future developments of VCSs and merging tools in order to allow the parallel development of model artifacts.Practical implications – Making model‐driven engineering (MDE) a success requires supporting the parallel development of model artifacts as is done nowadays for text‐based artifacts. Therefore, model versioning ca...

Blocked clause elimination for QBF

Quantified Boolean formulas (QBF) provide a powerful framework for encoding problems from various application domains, not least because efficient QBF solvers are available. Despite sophisticated evaluation techniques, the performance of such a solver usually depends on the way a problem is represented. However, the translation to processable QBF encodings is in general not unique and may either introduce variables and clauses not relevant for the solving process or blur information which could be beneficial for the solving process. To deal with both of these issues, preprocessors have been introduced which rewrite a given QBF before it is passed to a solver. In this paper, we present novel preprocessing methods for QBF based on blocked clause elimination (BCE), a technique successfully applied in SAT. Quantified blocked clause elimination (QBCE) allows to simulate various structural preprocessing techniques as BCE in SAT. We have implemented QBCE and extensions of QBCE in the preprocessor bloqqer. In our experiments we show that preprocessing with QBCE reduces formulas substantially and allows us to solve considerable more instances than the previous state-of-the-art.

An Example Is Worth a Thousand Words: Composite Operation Modeling By-Example

Predefined composite operations are handy for efficient modeling, e.g., for the automatic execution of refactorings, and for the introduction of patterns in existing models. Some modeling environments provide an initial set of basic refactoring operations, but hardly offer any extension points for the user. Even if extension points exist, the introduction of new composite operations requires programming skills and deep knowledge of the respective metamodel. In this paper, we introduce a method for specifying composite operations within the users modeling language and environment of choice. The user models the composite operation by-example, which enables the semi-automatic derivation of a generic composite operation specification. This specification may be used in various modeling scenarios, like model refactoring and model versioning. We implemented the approach in the Operation Recorder and performed an evaluation by defining multiple complex refactorings for UML diagrams.

SAT-Based Synthesis Methods for Safety Specs

Automatic synthesis of hardware components from declarative specifications is an ambitious endeavor in computer aided design. Existing synthesis algorithms are often implemented with Binary Decision Diagrams BDDs, inheriting their scalability limitations. Instead of BDDs, we propose several new methods to synthesize finite-state systems from safety specifications using decision procedures for the satisfiability of quantified and unquantified Boolean formulas SAT-, QBF- and EPR-solvers. The presented approaches are based on computational learning, templates, or reduction to first-order logic. We also present an efficient parallelization, and optimizations to utilize reachability information and incremental solving. Finally, we compare all methods in an extensive case study. Our new methods outperform BDDs and other existing work on some classes of benchmarks, and our parallelization achieves a super-linear speedup.

An introduction to model versioning

With the emergence of model-driven engineering (MDE), software models are considered as central artifacts in the software engineering process, going beyond their traditional use as sketches. In MDE, models rather act as the single source of information for automatically generating executable software. This shift poses several new research challenges. One of these challenges constitutes model versioning, which targets at enabling efficient team-based development of models. This compelling challenge induced a very active research community, who yielded remarkable methods and techniques ranging from model differencing to merging of models. In this tutorial, we give an introduction to the foundations of model versioning, the underlying technologies for processing models and their evolution, as well as the state of the art in model versioning. Thereby, we aim at equipping students and researchers alike that are new to this domain with enough information for commencing to contribute to this challenging research area.

Comparing different prenexing strategies for quantified Boolean formulas

The majority of the currently available solvers for quantified Boolean formulas (QBFs) process input formulas only in prenex conjunctive normal form. However, the natural representation of practicably relevant problems in terms of QBFs usually results in formulas which are not in a specific normal form. Hence, in order to evaluate such QBFs with available solvers, suitable normal-form translations are required. In this paper, we report experimental results comparing different prenexing strategies on a class of structured benchmark problems. The problems under consideration encode the evaluation of nested counterfactuals over a propositional knowledge base, and span the entire polynomial hierarchy. The results show that different prenexing strategies influence the evaluation time in different ways across different solvers. In particular, some solvers are robust to the chosen strategies while others are not.

A posteriori operation detection in evolving software models

Highlights ► Detection of applications of composite operations in evolving software models. ► Automatic generation of detection rules from executable operation specifications. ► Real-world study showing that 70% of all applied composite operations can be detected. ► Performance analysis showing that detection algorithm scales well for large models.

Resolution-based certificate extraction for QBF

A certificate of (un)satisfiability for a quantified Boolean formula (QBF) represents concrete assignments to the variables, which act as witnesses for its truth value. Certificates are highly requested for practical applications of QBF like formal verification and model checking. We present an integrated set of tools realizing resolution-based certificate extraction for QBF in prenex conjunctive normal form. Starting from resolution proofs produced by the solver DepQBF, we describe the workflow consisting of proof checking, certificate extraction, and certificate checking. We implemented the steps of that workflow in stand-alone tools and carried out comprehensive experiments. Our results demonstrate the practical applicability of resolution-based certificate extraction.

A Unified Proof System for QBF Preprocessing

For quantified Boolean formulas (QBFs), preprocessing is essential to solve many real-world formulas. The application of a preprocessor, however, prevented the extraction of proofs for the original formula. Such proofs are required to independently validate correctness of the preprocessor’s rewritings and the solver’s result. Especially for universal expansion proof checking was not possible so far. In this paper, we introduce a unified proof system based on three simple and elegant quantified resolution asymmetric tautology (QRAT) rules. In combination with an extended version of universal reduction, they are sufficient to efficiently express all preprocessing techniques used in state-of-the-art preprocessors including universal expansion. Moreover, these rules give rise to new preprocessing techniques. We equip our preprocessor bloqqer with QRAT proof logging and provide a proof checker for QRAT proofs.

Bridging the gap between dual propagation and CNF-based QBF solving

Conjunctive Normal Form (CNF) representation as used by most modern Quantified Boolean Formula (QBF) solvers is simple and powerful when reasoning about conflicts, but is not efficient at dealing with solutions. To overcome this inefficiency a number of specialized non-CNF solvers were created. These solvers were shown to have great advantages. Unfortunately, non-CNF solvers cannot benefit from sophisticated CNF-based techniques developed over the years. This paper demonstrates how the power of non-CNF structure can be harvested without the need for specialized solvers; in fact, it is easily incorporated into most existing CNF-based QBF solvers using a pre-existing mechanism of cube learning. We demonstrate this using a state-of-the-art QBF solver DepQBF, and experimentally show the effectiveness of our approach.