Tool support for the Java Modeling Language (JML) is a very pressing problem. A main issue with current tools is their architecture: the cost of keeping up with the evolution of Java is prohibitively high: e.g., almos...
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ISBN:
(纸本)9781595937216
Tool support for the Java Modeling Language (JML) is a very pressing problem. A main issue with current tools is their architecture: the cost of keeping up with the evolution of Java is prohibitively high: e.g., almost three years following its release, Java 5 has yet to be fully supported. This paper presents the architecture of JML4, an Integrated Verification Environment (IVE) for JML that builds upon Eclipse's support for Java, enhancing it with Extended Static Checking (ESC), an early form of Runtime Assertion Checking (RAC) and JML's non-null type system. Early results indicate that the synergy of complementary verification techniques (being made available within a single tool) can help developers be more effective;we demonstrate new bugs uncovered in JML annotated Java source - -like ESC/Java2 - -which is routinely verified using first generation JML tools. Copyright 2007 ACM.
In this paper, we propose a partially lexicalized parsing model utilizing rich features to improve the parsing ability and reduce the parsing cost. In order to disambiguate parse trees effectively, it employs several ...
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In this paper, we propose a partially lexicalized parsing model utilizing rich features to improve the parsing ability and reduce the parsing cost. In order to disambiguate parse trees effectively, it employs several useful features such as a syntactic label feature, a content feature, a functional feature, and a size feature. Besides, it is partially lexicalized so as to reduce the parsing cost closely connected with lexical information. Moreover, it is designed to be suitable for representing word order variation and constituent ellipsis in Korean sentences. Experimental results show that the proposed parsing model using more features performs better although it less depends on lexical information.
People spend a significant amount of time in indoor spaces (e.g., office buildings, subway systems, etc.) in their daily lives. Therefore, it is important to develop efficient indoor spatial query algorithms for suppo...
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The convergence of the Internet of Things (IoT) and foundation models, particularly Large Language Models (LLMs), heralds a new era of intelligent and adaptive systems. This investigation explores the integration of L...
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The convergence of the Internet of Things (IoT) and foundation models, particularly Large Language Models (LLMs), heralds a new era of intelligent and adaptive systems. This investigation explores the integration of LLMs and IoT for probabilistic vehicle trajectory prediction, a critical component in autonomous driving. Traditional deterministic models often fail to capture the complexity and uncertainty of real-world driving environments. To address these limitations, we propose an innovative approach that leverages LLM-driven spatio-temporal encoding and normalizing flows. The proposed method extracts latent motion patterns from historical trajectory data using LLMs, providing a nuanced understanding of vehicle dynamics. Advanced spatio-temporal encoders are employed for comprehensive feature extraction, capturing temporal dependencies and spatial relationships. Additionally, scaled dot-product attention is utilized for effective multimodal feature fusion, enhancing the integration of diverse data sources. The normalizing flows framework enhances the model's ability to capture complex, multimodal probability distributions of future trajectories by constructing an invertible transformation network. The network systematically maps simple base distributions to intricate target distributions through reversible transformations, significantly improving prediction accuracy. Evaluation of the nuScenes dataset demonstrates substantial improvements over existing methods. The results underscore the model's capability to generate diverse and realistic trajectory distributions, paving the way for safer and more efficient autonomous driving systems.
Graphical User Interface (GUI) designing and testing of different applications is significant from a user point of view. GUI testing ensures that the user interface of apps is visually appealing, user-friendly, and en...
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To build reliable avionic applications, we interconnect Integrated Modular Avionics (IMA) architectures with Time-Triggered Ethernet (TT-Ethernet). These systems have direct impacts on human lives where the failure is...
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The difficulty of writing, reading, and understanding formal specifications is one of the main obstacles in adopting formal verification techniques such as model checking and runtime verification. Introducing concepts...
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ISBN:
(纸本)9780769531441
The difficulty of writing, reading, and understanding formal specifications is one of the main obstacles in adopting formal verification techniques such as model checking and runtime verification. Introducing concepts in formal methods in an undergraduate program is essential for training a workforce that can develop and test high-assurance systems. This paper presents educational outcomes and outlines an instructive component that can be used in an undergraduate course to teach formal approaches and languages. The component uses a model checker and a specification tool to teach Linear Temporal Logic (LTL), a specification language that is widely used in a variety of verification tools. The paper also introduces a novel technique that analyzes LTL specifications by using the SPIN model checker to elucidate the behaviors accepted by the specifications.
The evolution of communication and information systems has raised the volume of data distributed through the internet. As an effect, a majority of digital resources have been increased, so does the challenge of cybers...
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In this paper, we propose a user-friendly tool that calibrates the coefficient variables of Steinhart-Hart equation used for the temperature measurement of NTC thermistor. The proposed tool provides automatic modifica...
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