Scalable Design Space Exploration via Answer Set Programming

The design of embedded systems is becoming continuously more complex such that the application of efficient high level design methods are crucial for competitive results regarding design time and performance. Recently, advances in Boolean constraint solvers for Answer Set Programming (ASP) allow for easy integration of background theories and more control over the solving process. The goal of this research is to leverage those advances for system level design space exploration while using specialized techniques from electronic design automation that drive new application-originated ideas for multi-objective combinatorial optimization

On Deciding Local Theory Extensions via E-matching

Satisfiability Modulo Theories (SMT) solvers incorporate decision procedures for theories of data types that commonly occur in software. This makes them important tools for automating verification problems. A limitation frequently encountered is that verification problems are often not fully expressible in the theories supported natively by the solvers. Many solvers allow the specification of application-specific theories as quantified axioms, but their handling is incomplete outside of narrow special cases. In this work, we show how SMT solvers can be used to obtain complete decision procedures for local theory extensions, an important class of theories that are decidable using finite instantiation of axioms. We present an algorithm that uses E-matching to generate instances incrementally during the search, significantly reducing the number of generated instances compared to eager instantiation strategies. We have used two SMT solvers to implement this algorithm and conducted an extensive experimental evaluation on benchmarks derived from verification conditions for heap-manipulating programs. We believe that our results are of interest to both the users of SMT solvers as well as their developers

Inspecting rewriting logic computations (in a parametric and stepwise way)

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54624-2_12Trace inspection is concerned with techniques that allow the trace content to be searched for specific components. This paper presents a rich and highly dynamic, parameterized technique for the trace inspection of Rewriting Logic theories that allows the non-deterministic execution of a given unconditional rewrite theory to be followed up in different ways. Using this technique, an analyst can browse, slice, filter, or search the traces as they come to life during the program execution. Starting from a selected state in the computation tree, the navigation of the trace is driven by a user-defined, inspection criterion that specifies the required exploration mode. By selecting different inspection criteria, one can automatically derive a family of practical algorithms such as program steppers and more sophisticated dynamic trace slicers that facilitate the dynamic detection of control and data dependencies across the computation tree. Our methodology, which is implemented in the Anima graphical tool, allows users to capture the impact of a given criterion thereby facilitating the detection of improper program behaviors.This work has been partially supported by the EU (FEDER), the Spanish MEC project ref. TIN2010-21062-C02-02, the Spanish MICINN complementary action ref. TIN2009-07495-E, and by Generalitat Valenciana ref. PROMETEO2011/052. This work was carried out during the tenure of D. Ballis’ ERCIM “Alain Bensoussan ”Postdoctoral Fellowship. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 246016. F. Frechina was supported by FPU-ME grant AP2010-5681.Alpuente Frasnedo, M.; Ballis, D.; Frechina, F.; Sapiña Sanchis, J. (2014). Inspecting rewriting logic computations (in a parametric and stepwise way). En Specification, algebra, and software: essays dedicated to Kokichi Futatsugi. Springer Verlag (Germany). 229-255. https://doi.org/10.1007/978-3-642-54624-2_12S229255Alpuente, M., Ballis, D., Baggi, M., Falaschi, M.: A Fold/Unfold Transformation Framework for Rewrite Theories extended to CCT. In: Proc. PEPM 2010, pp. 43–52. ACM (2010)Alpuente, M., Ballis, D., Espert, J., Romero, D.: Model-checking Web Applications with Web-TLR. In: Bouajjani, A., Chin, W.-N. (eds.) ATVA 2010. LNCS, vol. 6252, pp. 341–346. Springer, Heidelberg (2010)Alpuente, M., Ballis, D., Espert, J., Romero, D.: Backward Trace Slicing for Rewriting Logic Theories. In: Bjørner, N., Sofronie-Stokkermans, V. (eds.) CADE 2011. LNCS, vol. 6803, pp. 34–48. Springer, Heidelberg (2011)Alpuente, M., Ballis, D., Frechina, F., Sapiña, J.: Slicing-Based Trace Analysis of Rewriting Logic Specifications with iJulienne. In: Felleisen, M., Gardner, P. (eds.) ESOP 2013. LNCS, vol. 7792, pp. 121–124. Springer, Heidelberg (2013)Alpuente, M., Ballis, D., Frechina, F., Romero, D.: Using Conditional Trace Slicing for improving Maude programs. Science of Computer Programming (2013) (to appear)Alpuente, M., Ballis, D., Romero, D.: A Rewriting Logic Approach to the Formal Specification and Verification of Web applications. Science of Computer Programming (2013) (to appear)Baggi, M., Ballis, D., Falaschi, M.: Quantitative Pathway Logic for Computational Biology. In: Degano, P., Gorrieri, R. (eds.) CMSB 2009. LNCS, vol. 5688, pp. 68–82. Springer, Heidelberg (2009)Bruni, R., Meseguer, J.: Semantic Foundations for Generalized Rewrite Theories. Theoretical Computer Science 360(1-3), 386–414 (2006)Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C.: Maude Manual (Version 2.6). Technical report, SRI Int’l Computer Science Laboratory (2011), http://maude.cs.uiuc.edu/maude2-manual/Clements, J., Flatt, M., Felleisen, M.: Modeling an Algebraic Stepper. In: Sands, D. (ed.) ESOP 2001. LNCS, vol. 2028, pp. 320–334. Springer, Heidelberg (2001)Durán, F., Meseguer, J.: A Maude Coherence Checker Tool for Conditional Order-Sorted Rewrite Theories. In: Ölveczky, P.C. (ed.) WRLA 2010. LNCS, vol. 6381, pp. 86–103. Springer, Heidelberg (2010)Eker, S.: Associative-Commutative Matching via Bipartite Graph Matching. The Computer Journal 38(5), 381–399 (1995)Eker, S.: Associative-Commutative Rewriting on Large Terms. In: Nieuwenhuis, R. (ed.) RTA 2003. LNCS, vol. 2706, pp. 14–29. Springer, Heidelberg (2003)Klop, J.W.: Term Rewriting Systems. In: Abramsky, S., Gabbay, D., Maibaum, T. (eds.) Handbook of Logic in Computer Science, vol. I, pp. 1–112. Oxford University Press (1992)Martí-Oliet, N., Meseguer, J.: Rewriting Logic: Roadmap and Bibliography. Theoretical Computer Science 285(2), 121–154 (2002)Meseguer, J.: Conditional Rewriting Logic as a Unified Model of Concurrency. Theoretical Computer Science 96(1), 73–155 (1992)Meseguer, J.: The Temporal Logic of Rewriting: A Gentle Introduction. In: Degano, P., De Nicola, R., Meseguer, J. (eds.) Montanari Festschrift. LNCS, vol. 5065, pp. 354–382. Springer, Heidelberg (2008)Plotkin, G.D.: The Origins of Structural Operational Semantics. The Journal of Logic and Algebraic Programming 60-61(1), 3–15 (2004)Riesco, A., Verdejo, A., Caballero, R., Martí-Oliet, N.: Declarative Debugging of Rewriting Logic Specifications. In: Corradini, A., Montanari, U. (eds.) WADT 2008. LNCS, vol. 5486, pp. 308–325. Springer, Heidelberg (2009)Riesco, A., Verdejo, A., Martí-Oliet, N.: Declarative Debugging of Missing Answers for Maude. In: Proc. RTA 2010. LIPIcs, vol. 6, pp. 277–294 (2010)TeReSe. Term Rewriting Systems. Cambridge University Press (2003

Model-based symbolic design space exploration at the electronic system level: a systematic approach

In this thesis, a novel, fully systematic approach is proposed that addresses the automated design space exploration at the electronic system level. The problem is formulated as multi-objective optimization problem and is encoded symbolically using Answer Set Programming (ASP). Several specialized solvers are tightly coupled as background theories with the foreground ASP solver under the ASP modulo Theories (ASPmT) paradigm. By utilizing the ASPmT paradigm, the search is executed entirely systematically and the disparate synthesis steps can be coupled to explore the search space effectively.In dieser Arbeit wird ein vollständig systematischer Ansatz präsentiert, der sich mit der Entwurfsraumexploration auf der elektronischen Systemebene befasst. Das Problem wird als multikriterielles Optimierungsproblem formuliert und symbolisch mit Hilfe von Answer Set Programming (ASP) kodiert. Spezialisierte Solver sind im Rahmen des ASP modulo Theories (ASPmT) Paradigmas als Hintergrundtheorien eng mit dem ASP Solver gekoppelt. Durch die Verwendung von ASPmT wird die Suche systematisch ausgeführt und die individuellen Schritte können gekoppelt werden, um den Suchraum effektiv zu durchsuchen

Inductive logic programming as satisfiability modulo theories

At the intersection of machine learning, program synthesis and automated reasoning lies the field of Inductive Logic Programming (ILP). The aim of ILP is to automatically learn relational programs from input/output examples, typically through logic-based techniques. Inspired by Karl Popper’s falsification perspective on science, this dissertation sets out a new approach to ILP: Learning From Failures (LFF). In science, starting from a huge set of a priori viable hypotheses, we select a hypothesis to test. This hypothesis typically gets falsified due to failing in some specific way. By examining the failure we learn that an entire space of related hypotheses is now ruled out. Having thus reduced our set of viable hypotheses, we subsequently select from just those that remain. LFF applies this methodology to program induction, codifying it as a three-stage loop. The generate stage maintains a formula whose satisfying assignments correspond to the set of viable hypotheses. The test stage takes a satisfying assignment, interprets it as a logic program and tests it against training examples – imperfect fit is considered a failure. The constrain stage turns a failure into constraints to add to the generate stage’s formula, thereby eliminating a class of hypotheses which will fail for the same reason. The thesis of this dissertation is three-fold. The first claim is that LFF frames the ILP problem as one of Satisfiability Modulo Theories (SMT). With the search for viable hypotheses handed-off to a SAT-solver, the test stage can be regarded as a theory solver collaborating with the SAT-solver, effectively making ILP’s notion of background knowledge into a (Horn) background theory. The second claim is that LFF’s three-stage loop is an effective basis for falsification-based program induction. Chapter 4 develops the above correspondence into a feature-rich and flexible three-stage ILP system. Experimental evidence is provided for this system going beyond the state-of-the-art in ILP, e.g., by supporting large hypothesis spaces and large domains. The third claim is that the LFF-as-SMT-perspective helps apply satisfiability solving techniques to ILP, in particular to reduce hypothesis space exploration. In Chapter 5, we show that SMT-based techniques for explaining conflicts have a natural analog in terms of explaining which parts of a hypothesis are responsible for its failure. In Chapter 6, we incorporate other theory solvers alongside the test stage to reason about the (satisfiability of) over-approximating properties of hypotheses. We show that both of these techniques can significantly reduce the number of iterations of the three-stage loop