the proceedings contain 19 papers. the topics discussed include: the Orc programming language;keep it small, keep it real: efficient run-time verification of web service compositions;approximated context-sensitive ana...
ISBN:
(纸本)3642021379
the proceedings contain 19 papers. the topics discussed include: the Orc programming language;keep it small, keep it real: efficient run-time verification of web service compositions;approximated context-sensitive analysis for parameterized verification;verification of parameterized systems with combinations of abstract domains;on model-checking optimistic replication algorithms;a software platform for timed mobility and timed interaction;modeling, validation, and verification of PCEP using the IF language;distinguing non-deterministic timed finite state machines;system model-based definition of modeling language semantics;typing component-based communication systems;epistemic logic for the applied Pi calculus;on process-algebraic proof methods for fault tolerant distributed systems;using first-order logic to reason about submodule construction;a model-checking approach for service component architectures;and dynamic symbolic execution of distributed concurrent objects.
this open access book constitutes the proceedings of the 29thinternationalconference on Automated Deduction, CADE 29, which took place in Rome, Italy, during July 2023.
ISBN:
(数字)9783031384998
ISBN:
(纸本)9783031384981
this open access book constitutes the proceedings of the 29thinternationalconference on Automated Deduction, CADE 29, which took place in Rome, Italy, during July 2023.
Recent advances in learning description logic (DL) concepts usually employ a downward refinement operator for space traversing and hypotheses construction. However, theoretical research proved that ideal refinement op...
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ISBN:
(数字)9783030492106
ISBN:
(纸本)9783030492090;9783030492106
Recent advances in learning description logic (DL) concepts usually employ a downward refinement operator for space traversing and hypotheses construction. However, theoretical research proved that ideal refinement operator does not exist for expressive DLs, including the language ALC. the state-of-the-art learning framework DL-Learner suggests to use a complete and proper refinement operator and to handle infiniteness algorithmically. For example, the CELOE algorithm follows an iterative widening approach to build a search tree of concept hypotheses. To select a tree node for expansion, CELOE adopts a simple greedy strategy that neglects the structure of the search tree. In this paper, we present the Rapid Restart Hill Climbing (RRHC) algorithm that selects a node for expansion by traversing the search tree in a hill climbing manner and rapidly restarts with one-step backtracking after each expansion. We provide an implementation of RRHC in the DL-Learner framework and compare its performance with CELOE using standard benchmarks.
ACL2 is the latest inception of the Boyer-Moore theorem prover, the 2005 recipient of the ACM Software System Award. In the hands of an expert, it feels like a finely tuned race car, and it has been used to prove some...
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ISBN:
(纸本)9780769528922
ACL2 is the latest inception of the Boyer-Moore theorem prover, the 2005 recipient of the ACM Software System Award. In the hands of an expert, it feels like a finely tuned race car, and it has been used to prove some of the most complex theorems ever proved about commercially designed systems. Unfortunately, ACL2 has a steep learning curve, and novices tend have a very different experience: they crash and bum. As part of a project to make ACL2 and formal reasoning accessible to the masses, we have developed ACL2s, the ACL2 sedan. ACL2s streamlines the learning process with features not previously available for ACL2. Our goal is to develop a tool that is "self-teaching," i.e., it should be possible for an undergraduate to sit down and play with it and learn how to program in ACL2 and how to reason about the programs she writes. the latest version of ACL2s is a significant step in that direction.
the issue of describing in a formal way solving algorithms in various fields such as Propositional Satisfiability (SAT), Quantified SAT, Satisfiability Modulo theories, Answer Set programming (ASP), and Constraint ASP...
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Symbolic execution tools query constraint solvers for tasks such as determining the feasibility of program paths. therefore, the effectiveness of such tools depends on their constraint solvers. Most modern constraint ...
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We recently proposed Acceleration Driven Clause Learning (ADCL), a novel calculus to analyze satisfiability of Constrained Horn Clauses (CHCs). Here, we adapt ADCL to transition systems and introduce ADCL-NT, a varian...
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ISBN:
(数字)9783031384998
ISBN:
(纸本)9783031384998;9783031384981
We recently proposed Acceleration Driven Clause Learning (ADCL), a novel calculus to analyze satisfiability of Constrained Horn Clauses (CHCs). Here, we adapt ADCL to transition systems and introduce ADCL-NT, a variant for disproving termination. We implemented ADCL-NT in our tool LoAT and evaluate it against the state of the art.
Recent development of logicprogramming languages based on linear logic suggests a successful direction to extend logicprogramming to be more expressive and more efficient. the treatment of formulasas- resources give...
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We consider the problem of obtaining an implementation of an algorithm from its specification. We assume that these specifications are written in answer set programming (ASP). ASP is an ideal formalism for writing spe...
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ISBN:
(纸本)9783030452599;9783030452605
We consider the problem of obtaining an implementation of an algorithm from its specification. We assume that these specifications are written in answer set programming (ASP). ASP is an ideal formalism for writing specifications due to its highly declarative and expressive nature. To obtain an implementation from its specification, we utilize the operational semantics of ASP implemented in the s(ASP) system. this operational semantics is used to transform the declarative specification written in ASP to obtain an equivalent efficient program that uses imperative control features. this work is inspired by our overarching goal of automatically deriving efficient concurrent algorithms from declarative specifications. this paper reports our first step towards achieving that goal where we restrict ourselves to simple sequential algorithms. We illustrate our ideas through several examples. Our work opens up a new approach to logic-based program synthesis not explored before.
Withthe rise of social networks, large-scale graph analysis becomes increasingly important. Because SQL lacks the expressiveness and performance needed for graph algorithms, lower-level, general-purpose languages are...
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ISBN:
(纸本)9781467349093;9781467349086
Withthe rise of social networks, large-scale graph analysis becomes increasingly important. Because SQL lacks the expressiveness and performance needed for graph algorithms, lower-level, general-purpose languages are often used instead. For greater ease of use and efficiency, we propose SociaLite, a high-level graph query language based on Datalog. As a logicprogramming language, Datalog allows many graph algorithms to be expressed succinctly. However, its performance has not been competitive when compared to low-level languages. With SociaLite, users can provide high-level hints on the data layout and evaluation order;they can also define recursive aggregate functions which, as long as they are meet operations, can be evaluated incrementally and efficiently. We evaluated SociaLite by running eight graph algorithms (shortest paths, PageRank, hubs and authorities, mutual neighbors, connected components, triangles, clustering coefficients, and betweenness centrality) on two real-life social graphs, Live-Journal and Last. fm. the optimizations proposed in this paper speed up almost all the algorithms by 3 to 22 times. SociaLite even outperforms typical Java implementations by an average of 50% for the graph algorithms tested. When compared to highly optimized Java implementations, SociaLite programs are an order of magnitude more succinct and easier to write. Its performance is competitive, giving up only 16% for the largest benchmark. Most importantly, being a query language, SociaLite enables many more users who are not proficient in software engineering to make social network queries easily and efficiently.
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