MythSim is a cross-platform control-code simulator being used at the University of Illinois at Chicago. This mythical 8-bit processor gives students experience with concepts in computer architecture. MythSim has been ...
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MythSim is a cross-platform control-code simulator being used at the University of Illinois at Chicago. This mythical 8-bit processor gives students experience with concepts in computer architecture. MythSim has been redesigned from the ground up based on the changing needs of instructors and students. An improved multiwindowed interface, color-coding system and reference card allows students to learn the architecture quickly so they can focus on developing and debugging their programs. To facilitate future development, the source code is hosted online in a distributed development environment. Feedback from instructors and students has been positive. This paper presents improvements made in the new version, feedback from students and the support we provide for instructors.
We present a logic-based approach for query refinement in ontology-based information portal. The approach enables a user to navigate through the information content incrementally and interactively. In each refinement ...
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We present a logic-based approach for query refinement in ontology-based information portal. The approach enables a user to navigate through the information content incrementally and interactively. In each refinement step a user is provided with a complete but minimal set of refinements, which enables him to develop/express his information need in a step-by-step fashion. The approach is based on the model-theoretic interpretation of the refinement problem, so that the query refinement process can be considered as the process of inferring all queries which are subsumed by a given query. Moreover, query refinements are ranked according to their relevance to user's needs, whereas these needs are online discovered by analysing a user's behaviour. The approach is very suitable for modelling information retrieval tasks based on the database repositories, like searching product catalogues.
TheoSim is a symbolic verification tool that fills the gap between the simulation of test cases, and the use of theorem provers, for the validation of initial specifications, and the exploration of the very first desi...
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TheoSim is a symbolic verification tool that fills the gap between the simulation of test cases, and the use of theorem provers, for the validation of initial specifications, and the exploration of the very first design steps of digital integrated systems. The principles of Theosim are presented, followed by its application to the verification of the first design step of a state-of-the-art network on chip architecture.
We propose a novel method, called PathCrawler, for the automatic generation of structural tests satisfying the all-paths criterion or its k-path variant. The source code is instrumented so as to recover the symbolic e...
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ISBN:
(纸本)9780769521312
We propose a novel method, called PathCrawler, for the automatic generation of structural tests satisfying the all-paths criterion or its k-path variant. The source code is instrumented so as to recover the symbolic execution path each time that the program under test is executed. This code is first executed using inputs arbitrarily selected from the input domain. The resulting symbolic path is transformed into a path predicate by projection of the conditions onto the input variables. The next test is obtained by using constraint logic programming to find new input values outside the domain of the path which is already covered. The instrumented code is then executed on this test and so on, until all feasible paths have been covered. Our method combines static and dynamic analysis in a way that avoids the disadvantages of both. It is currently being implemented for the C language.
Inductive logic programming (ILP) is a well known machine learning technique in learning concepts from relational data. Nevertheless, ILP systems are not robust enough to noisy or unseen data in real world domains. Fu...
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Inductive logic programming (ILP) is a well known machine learning technique in learning concepts from relational data. Nevertheless, ILP systems are not robust enough to noisy or unseen data in real world domains. Furthermore, in multiclass problems, if the example is not matched with any learned rules, it cannot be classified. This paper presents a novel hybrid learning method to alleviate this restriction by enabling neural networks to handle first-order logic programs directly. The proposed method, called first-order logical neural network (FOLNN), is based on feedforward neural networks and integrates inductive learning from examples and background knowledge. We also propose a method for determining the appropriate variable substitution in FOLNN learning by using multiple-instance learning (MIL). In the experiments, the proposed method has been evaluated on two first-order learning problems, i.e., the finite element mesh design and mutagenesis and compared with the state-of-the-art, the PROGOL system. The experimental results show that the proposed method performs better than PROGOL.
We present a logical foundation for object-oriented specifications which supports a rigorous formal development of object-oriented systems. In this setting, we study two different views on a system, the implementor...
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We present a logical foundation for object-oriented specifications which supports a rigorous formal development of object-oriented systems. In this setting, we study two different views on a system, the implementor's view (glass-box view) and the user's view (black-box view) which both are founded on a model-theoretic semantics. We also discuss the hierarchical construction of specifications and realisations. Our approach is abstract in the sense that it can be instantiated by various concrete specification formalisms like OCL or JML.
This paper investigates an approach to solve the access gate misalignment issues linked to the poly-CMP process of compact cells. The process of this self-aligned access gate approach is be detailed and measurements d...
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This paper investigates an approach to solve the access gate misalignment issues linked to the poly-CMP process of compact cells. The process of this self-aligned access gate approach is be detailed and measurements demonstrate the viability of this approach and show that the issues associated with access gate misalignment, such as parameter spread among cells during source side injection programming, are gone. This paves the way for aggressively scaled low power embedded nonvolatile memories for the next CMOS generations.
Reactive systems are the systems that maintain some interaction with their environment. Temporal logic is one of the methods for formal specification descriptions of reactive systems. The formal specifications of reac...
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Reactive systems are the systems that maintain some interaction with their environment. Temporal logic is one of the methods for formal specification descriptions of reactive systems. The formal specifications of reactive systems enables to check the consistency of the specifications and whether they contain defects. By using a synthesis algorithm we also obtain reactive system programs from the formal specifications and prevent programming bugs. Thus, it is important to describe reactive system formal specifications. However, it is difficult to describe realizable reactive system specifications and it is necessary to find the causes of unrealizable reactive system specifications. In previous research, three properties have been introduced into unrealizable reactive system specifications and we suppose that this classification gives the hists of finding the causes of unrealizability. In this paper we propose several heuristics of finding the causes of unrealizability of reactive system formal specifications. To find the causes, we use tableau methods and the classification of the reactive system specifications.
Evolution is an important subarea of study in biological science, where given a set of species, the goal is to reconstruct their evolutionary history, or phylogeny. Many kinds of data associated with the species can b...
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Evolution is an important subarea of study in biological science, where given a set of species, the goal is to reconstruct their evolutionary history, or phylogeny. Many kinds of data associated with the species can be deployed for this task and many reconstruction methods have been proposed and examined in the literature. One very recent approach is to build a local phylogeny for every subset of 4 species, which is called a quartet for these 4 species, and then to assemble a phylogeny for the whole set of species satisfying these predicted quartets. In general, those predicted quartets might not always agree each other; and thus the objective function becomes to satisfy a maximum number of predicted quartets. This is the well-known maximum quartet consistency (MQC) problem, which is studied by a lot of researchers in the last two decades. We present a new equivalent representation for the MQC problem, that is, to search for an ultrametric matrix to satisfy the maximum number of those predicted quartets. We examine a few number of structural properties of the MQC problem in this new representation, through formulating it into answer set programming (ASP), a recent powerful logic programming tool for modeling and solving searching problems. The efficiency and usefulness of our approach are confirmed by our computational experiments on the artificial data as well as two real datasets.
Peculiarity rules are a new type of interesting rules which can be discovered by searching the relevance among peculiar data. A main task of mining peculiarity rules is the identification of peculiarity. Traditional m...
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Peculiarity rules are a new type of interesting rules which can be discovered by searching the relevance among peculiar data. A main task of mining peculiarity rules is the identification of peculiarity. Traditional methods of finding peculiar data are attribute-based approaches. This paper extends peculiarity oriented mining to relational peculiarity oriented mining. Peculiar data are identified on record level, and peculiar rules are mined and explained in a relational mining framework. The results from preliminary experiments show that relational peculiarity oriented mining is very effective.
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