Boosting local search thanks to {CDCL}

International audienceIn this paper, a novel hybrid and complete approach for propositional satisfiability, called SAT HYS (Sat Hybrid Solver), is introduced. It efficiently combines the strength of both local search and CDCL based SAT solvers. Considering the consistent partial assignment under construction by the CDCL SAT solver, local search is used to extend it to a model of the Boolean formula, while the CDCL component is used by the local search one as a strategy to escape from a local minimum. Additionally, both solvers heavily cooperate thanks to relevant information gathered during search. Experimentations on SAT instances taken from the last competitions demonstrate the efficiency and the robustness of our hybrid solver with respect to the state-of-the-art CDCL based, local search and hybrid SAT solvers

Logic Programming Applications: What Are the Abstractions and Implementations?

This article presents an overview of applications of logic programming, classifying them based on the abstractions and implementations of logic languages that support the applications. The three key abstractions are join, recursion, and constraint. Their essential implementations are for-loops, fixed points, and backtracking, respectively. The corresponding kinds of applications are database queries, inductive analysis, and combinatorial search, respectively. We also discuss language extensions and programming paradigms, summarize example application problems by application areas, and touch on example systems that support variants of the abstractions with different implementations

A Survey of Symbolic Execution Techniques

Many security and software testing applications require checking whether certain properties of a program hold for any possible usage scenario. For instance, a tool for identifying software vulnerabilities may need to rule out the existence of any backdoor to bypass a program's authentication. One approach would be to test the program using different, possibly random inputs. As the backdoor may only be hit for very specific program workloads, automated exploration of the space of possible inputs is of the essence. Symbolic execution provides an elegant solution to the problem, by systematically exploring many possible execution paths at the same time without necessarily requiring concrete inputs. Rather than taking on fully specified input values, the technique abstractly represents them as symbols, resorting to constraint solvers to construct actual instances that would cause property violations. Symbolic execution has been incubated in dozens of tools developed over the last four decades, leading to major practical breakthroughs in a number of prominent software reliability applications. The goal of this survey is to provide an overview of the main ideas, challenges, and solutions developed in the area, distilling them for a broad audience. The present survey has been accepted for publication at ACM Computing Surveys. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing this survey, we would appreciate if you could use the following BibTeX entry: http://goo.gl/Hf5Fv

Anwendungen von #SAT Solvern für Produktlinien: Masterarbeit

Product lines are widely used for managing families of similar products. Typically, product lines are complex and infeasible to analyze manually. In the last two decades, product-line analyses have been reduced to satisfiability problems which are well understood. However, there are methods for which satisfiability is not sufficient. Recently, researchers begun to reduce other problems to #SAT. Yet, only few applications have been considered and those are fairly limited in their scope. Furthermore, the authors mainly propose ad-hoc solutions that are only applicable under certain restrictions or do not scale to large product lines. In this thesis, we aim show the benefits of applying #SAT for the analysis of product lines. To this end, we make the following contributions: First, we summarize applications dependent on #AT considered in the literature and propose new applications to motivate the usage of #SAT technology. Second, we present a variety of algorithms and optimizations for these applications including new proposals. Third, we empirically evaluate 10 proposed algorithms with 14 off-the-shelf #SAT solvers on 131 industrial feature models to identify the fastest algorithms and solvers. Our results show that for each analysis at least one algorithm and solver scale on a vast majority of the feature models, whereas Linux and an automotive model not be analyzed at all. In addition, our results further reveal the benefits of knowledge compilation to deterministic decomposable negation normal form for performing counting-based analyses. Overall, our work shows that #SAT dependent analyses for feature models open a new variety of different applications and scale to a large number of industrial feature models.Produktlinien sind weit verbreitet für die Verwaltung von Familien verwandter Pro- dukte. In der Regel sind Produktlinien komplex und manuell schwer zu analysieren. In den letzten zwei Jahrzehnten wurden Produktlinienanalysen auf Erfüllbarkeit- sprobleme reduziert, für welche es eine Vielzahl an effizienten Werkzeugen gibt. Allerdings ist Erfüllbarkeit nicht für alle Analysen hinreichend. Kürzlich haben Forscher damit begonnen, andere Probleme auf #SAT zu reduzieren. Es wur- den jedoch nur wenige Anwendungen in Betracht gezogen und auch der Anwen- dungsbereich ist begrenzt. Darüber hinaus schlagen die Autoren hauptsächlich Ad-hoc-Lösungen vor, die nur unter bestimmten Einschränkungen der Produktlin- ien anwendbar sind oder nicht für große Produktlinien skalieren. In dieser Arbeit zeigen wir die Vorteile von #SAT Anwendungen für Produtlinien auf. Unser wis- senschaftlicher Beitrag besteht aus den folgenden drei Punkten: Zuerst fassen wir die in der Literatur betrachteten #SAT-Anwendungen zusammen und schlagen neue Anwendungen vor, um den Einsatz von #SAT-Technologien zu motivieren. Zweit- ens stellen wir eine Vielzahl von Algorithmen und Optimierungen für diese Anwen- dungen vor, einschließlich neuer Vorschläge. Drittens führen wir eine empirische Evaluation von 10 der vorgeschlagenen Algorithmen mit 14 #SAT-Solvern auf 131 industriellen Feature-Modellen aus, um die schnellsten Algorithmen und Solver zu identifizieren. Die Ergebnisse der Evaluation zeigen, dass wir für jede Analyse wenig- stens einen Algorithmus und Solver identifiziert haben, die für industrielle Feature- Modelle skalieren. Dazu sind die Ergebnisse ein starker Indikator für die Vorteile des Einsatzes von d-DNNFs bei #SAT-Anwendungen. Insgesamt zeigt unsere Ar- beit, dass #SAT-abhängige Analysen für Feature-Modelle eine Vielzahl neuer un- terschiedlicher Anwendungen ermöglicht und für viele industirelle Feature-Modelle skaliert

Time-Space Efficient Regression Testing for Configurable Systems

Configurable systems are those that can be adapted from a set of options. They are prevalent and testing them is important and challenging. Existing approaches for testing configurable systems are either unsound (i.e., they can miss fault-revealing configurations) or do not scale. This paper proposes EvoSPLat, a regression testing technique for configurable systems. EvoSPLat builds on our previously-developed technique, SPLat, which explores all dynamically reachable configurations from a test. EvoSPLat is tuned for two scenarios of use in regression testing: Regression Configuration Selection (RCS) and Regression Test Selection (RTS). EvoSPLat for RCS prunes configurations (not tests) that are not impacted by changes whereas EvoSPLat for RTS prunes tests (not configurations) which are not impacted by changes. Handling both scenarios in the context of evolution is important. Experimental results show that EvoSPLat is promising. We observed a substantial reduction in time (22%) and in the number of configurations (45%) for configurable Java programs. In a case study on a large real-world configurable system (GCC), EvoSPLat reduced 35% of the running time. Comparing EvoSPLat with sampling techniques, 2-wise was the most efficient technique, but it missed two bugs whereas EvoSPLat detected all bugs four times faster than 6-wise, on average.Comment: 14 page