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IEEE Conference on Commerce and Enterprise Computing, CEC

作者： Elaheh Ordoni Jutta Mülle Klemens Böhm Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (数字)9781728199269

ISBN: (纸本)9781728199276

Verification techniques are fundamental to improve the reliability of process designs in practice. In application domains like auctions, the issue is extremely valuable; the goal of auction designers is to prevent undesirable executions and maximize certain outcome measures. Current verification approaches tend to be confined to control flows, even though data values play a significant role. We address this issue by proposing a new data-value-aware verification approach: We enhance process models with information on data values. Then we transform the data-value-aware process models to Petri Nets, respecting the semantics of data value usages. By employing an off-the-shelf model checker and specifying data-value centered properties, one can now verify data-value-aware process models. A distinctive feature of our approach is the specification of data values and of their modifications during the process. This enables the verification of interesting properties in many domains. We evaluate our approach against the use case of Simultaneous Multi-Round (SMR) spectrum auctions. We verify SMR auction models and compute extreme values of common auction measures such as revenue.

关键词： Petri nets data models Licenses Computational modeling Reliability engineering Space exploration

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NoRBERT: Transfer Learning for Requirements Classification

NoRBERT: Transfer Learning for Requirements Classification

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IEEE International Conference on Requirements Engineering

作者： Tobias Hey Jan Keim Anne Koziolek Walter F. Tichy Karlsruhe Institute of Technology (KIT) Institute for Program Structures and Data Organization Karlsruhe Germany

ISBN: (数字)9781728174389

ISBN: (纸本)9781728174396

Classifying requirements is crucial for automatically handling natural language requirements. The performance of existing automatic classification approaches diminishes when applied to unseen projects because requirements usually vary in wording and style. The main problem is poor generalization. We propose NoRBERT that fine-tunes BERT, a language model that has proven useful for transfer learning. We apply our approach to different tasks in the domain of requirements classification. We achieve similar or better results F 1 -scores of up to 94%) on both seen and unseen projects for classifying functional and non-functional requirements on the PROMISE NFR dataset. NoRBERT outperforms recent approaches at classifying non-functional requirements subclasses. The most frequent classes are classified with an average F 1 -score of 87%. In an unseen project setup on a relabeled PROMISE NFR dataset, our approach achieves an improvement of 15 percentage points in average F 1 score compared to recent approaches. Additionally, we propose to classify functional requirements according to the included concerns, i.e., function, data, and behavior. We labeled the functional requirements in the PROMISE NFR dataset and applied our approach. NoRBERT achieves an F 1 -score of up to 92%. Overall, NoRBERT improves requirements classification and can be applied to unseen projects with convincing results.

关键词： Bit error rate Task analysis Requirements engineering Machine learning Training Natural language processing

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Hybrid online autotuning for parallel ray tracing

Hybrid online autotuning for parallel ray tracing

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19th Eurographics Symposium on Parallel Graphics and Visualization, EGPGV 2019

作者： Herveau, K. Pfaffe, P. Tillmann, M. Tichy, W.F. Dachsbacher, C. Computer Graphics Group Karlsruhe Institute of Technology Germany Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Germany

ISBN: (纸本)9783038680796

Acceleration structures are key to high performance parallel ray tracing. Maximizing performance requires configuring the degrees of freedom (e.g., construction parameters) these data structures expose. Whether a parameter setting is optimal depends on the input (e.g., the scene and view parameters) and hardware. Manual selection is tedious, error prone, and is not portable. To automate the parameter selection task we use a hybrid of model-based prediction and online autotuning. The combination benefits from the best of both worlds: One-shot configuration selection when inputs are known or similar, effective exploration of the configuration space otherwise. Online tuning additionally serves to train the model on real inputs without requiring a-priori training samples. Online autotuning outperforms best-practice configurations recommended by the literature, by up to 11% median. The model predictions achieve 95% of the online autotuning performance while reducing 90% of the autotuner overhead. Hybrid online autotuning thus enables always-on tuning of parallel ray tracing. © 2019 Eurographics Association. All rights reserved.

关键词： Ray tracing

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Automatic generation of virtual assistants from databases using active ontologies 31

Automatic generation of virtual assistants from databases us...

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31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019

作者： Blersch, Martin Weigelt, Sebastian Tichy, Walter F. Angele, Kevin Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Karlsruhe Germany Semantic Technology Institute University of Innsbruck Innsbruck Austria ONLIM GmbH Telfs Austria

ISBN: (纸本)1891706489

Virtual assistants such as Siri or Google Assistant are omnipresent. However, their development remains costly. One must either manually model the problem domain or provide thousands of labeled samples. We propose to automatically create virtual assistants based on Active Ontologies for interacting with databases. Our approach generates Active Ontologies;we use the database structure to derive a concept hierarchy and database values together with synonyms to extract information from user queries. Our approach also learns common phrases from samples, e.g. from existing Dialogflow agents. We extract pre- and postfixes and attach them to concepts, e.g. at to detect a succeeding location. The generated Active Ontologies reply to previously unseen and composed requests. The approach is not limited to virtual assistants but can be applied to any system with a textual or voice-based conversational interface such as chatbots. We evaluate our approach in three domains: tourism, hotel, and web cams. The study shows that automatically generated Active Ontologies extract relevant information from user utterances with a precision of 58%. The precision increases to 79% (recall 46%, F1 58%) when we use sample utterances. Our approach successfully transfers between domains, e.g. we learn phrases from the tourism domain and use them to reply to hotel requests without any adjustments. © 2019 Knowledge Systems institute Graduate School. All rights reserved.

关键词： Ontology

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Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits

arXiv

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arXiv 2021年

作者： Komiyama, Junpei Fouché, Edouard Honda, Junya Stern School of Business New York University 44 West 4th Street New YorkNY United States Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe76131 Germany Department of Systems Science Graduate School of Informatics Kyoto University Yoshida Honmachi Sakyo-ku Kyoto606-8501 Japan

We consider nonstationary multi-armed bandit problems where the model parameters of the arms change over time. We introduce the adaptive resetting bandit (ADR-bandit), a bandit algorithm class that leverages adaptive windowing techniques from literature on data streams. We first provide new guarantees on the quality of estimators resulting from adaptive windowing techniques, which are of independent interest. Furthermore, we conduct a finite-time analysis of ADR-bandit in two typical environments: an abrupt environment where changes occur instantaneously and a gradual environment where changes occur progressively. We demonstrate that ADR-bandit has nearly optimal performance when abrupt or gradual changes occur in a coordinated manner that we call global changes. We demonstrate that forced exploration is unnecessary when we assume such global changes. Unlike the existing nonstationary bandit algorithms, ADR-bandit has optimal performance in stationary environments as well as nonstationary environments with global changes. Our experiments show that the proposed algorithms outperform the existing approaches in synthetic and real-world environments. © 2021, CC BY.

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Collaborative modeling enabled by version control

Collaborative modeling enabled by version control

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Fachtagung Modellierung, 2018

作者： Kuryazov, Dilshod Winter, Andreas Reussner, Ralf University of Oldenburg Software Engineering Group Uhlhornsweg 84 Oldenburg26111 Germany Karlsruhe Institute of Technology Institute for Program Structures and Data Organization Postfach 6980 KarlsruheD-76128 Germany

ISBN: (纸本)9783885796749

Model-Driven Software Development is a key field in software development activities which is well-suited to design and develop large-scale software systems. Developing and maintaining large-scale model-driven software systems entail a need for collaborative modeling by a large number of software designers and developers. As long as software models are constantly changed during development and maintenance, collaborative modeling requires frequently sharing of model changes between collaborators. Thereby, a solid change representation support for model changes plays an essential role for collaborative modeling systems. This paper focuses on the problem of model change representation for collaborative modeling. It introduces a meta-model generic, operation-based and textual difference language to represent model changes in collaborative modeling. This paper also demonstrates a collaborative modeling application Kotelett. © 2018 Gesellschaft fur Informatik (GI).

关键词： Software design

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Detection of Conditionals in Spoken Utterances

Detection of Conditionals in Spoken Utterances

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International Conference on Semantic Computing

作者： Sebastian Weigelt Tobias Hey Vanessa Steurer Karlsruhe Institute of Technology Institute for Program Structures and Data Organization Karlsruhe Germany

State-of-the-art intelligent assistant systems such as Siri & Co. struggle with conditionals. They reliably react to ordinary commands. However, their architectures are not designed to cope with complex conditional queries. We propose a system to overcome these limitations. Our approach models if-then-else constructs in spoken utterances explicitly. The model bridges the gap between linguistic and programmatic semantics. To proof our concept, we apply a rule-based approach to extract conditionals. For our prototype we use part-of-speech and chunk tags provided by NLP tools. We make use of coreference information to determine the reference frame of a condition. The explicit modeling of conditionals allows us to evaluate the accuracy of our approach independently from other language understanding tasks. The prototype works well in the domain of humanoid robotics. In a user study we achieve F1 scores of 0.783 (automatic speech recognition) up to 0.898 (manual transcripts) on unrestricted utterances.

关键词： Semantics Task analysis Robots Linguistics Tools Ontologies

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Context model acquisition from spoken utterances 29

Context model acquisition from spoken utterances

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29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017

作者： Weigelt, Sebastian Hey, Tobias Tichy, Walter F. Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)1891706411

Current systems with spoken language interfaces do not leverage contextual information. Therefore, they struggle with understanding speakers' intentions. We propose a system that creates a context model from user utterances to overcome this lack of information. It comprises eight types of contextual information organized in three layers: individual, conceptual, and hierarchical. We have implemented our approach as a part of the project PARSE. It aims at enabling laypersons to construct simple programs by dialog. Our implementation incrementally generates context including occurring entities and actions as well as their conceptualizations, state transitions, and other types of contextual information. Its analyses are knowledge- or rulebased (depending on the context type), but we make use of many well-known probabilistic NLP techniques. In a user study we have shown the feasibility of our approach, achieving F1 scores from 72% up to 98% depending on the type of contextual information. The context model enables us to resolve complex identity relations. However, quantifying this effect is subject to future work. Likewise, we plan to investigate whether our context model is useful for other language understanding tasks, e.g., anaphora resolution, topic analysis, or correction of automatic speech recognition errors.

关键词： Speech recognition

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Architecture-driven reduction of specification overhead for verifying confidentiality in component-based software systems

Architecture-driven reduction of specification overhead for ...

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2017 MODELS Satellite Event: Workshops (ModComp, ME, EXE, COMMitMDE, MRT, MULTI, GEMOC, MoDeVVa, MDETools, FlexMDE, MDEbug), Posters, Doctoral Symposium, Educator Symposium, ACM Student Research Competition, and Tools and Demonstrations, MODEL-SSE 2017

作者： Yurchenko, Kateryna Behr, Moritz Klare, Heiko Kramer, Max Reussner, Ralf Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Karlsruhe Germany

Code verification techniques can be used to guarantee that some of the information processed in software systems remains confidential. For this, allowed information flows have to be specified for the system under analysis. Reducing the specification overhead could render code verification feasible where verification was considered too complex or costly so far. In this paper, we introduce a model-driven approach to reduce the overhead for creating and maintaining such specifications. Independent of the verification input format, developers can specify confidentiality for component-based architecture models, which are kept consistent with object-oriented code. They are supported in adapting the specifications to evolving systems in order to detect information leaks with less e ort and in earlier development stages.

关键词： Specifications

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An Empirical Study on the Current and Future Challenges of Automotive Software Release and Configuration Management

An Empirical Study on the Current and Future Challenges of A...

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Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Houssem Guissouma Heiko Klare Eric Sax Erik Burger Institute for Information Processing Technologies Karlsruhe Institute of Technology Germany Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Germany

ISBN: (纸本)9781538673843

Current automotive trends, such as autonomous and connected driving, are mainly enabled by embedded software that is deployed on a network of several, often more than one hundred, electronic control units. These software parts are responsible for many complex tasks concerning safety, comfort, energy management, and vehicle dynamics. Currently, they are deployed to the units at the end of the assembly line. Although a new software baseline of electronic control units is released in regular terms, normally six months, updates during after-sales are mostly conducted only in urgent cases, such as recall campaigns. Upcoming over-the-air services will enable more frequent updates to fix bugs and add new functionality. The possible alternatives of engines, chassis, and customer wishes lead to a high number of existing vehicle variants, so that the management of releases and configurations becomes more complex and costly. In a survey, we asked participants from different automotive institutions about the current state of practice, and the challenges they face during release development and management. This paper presents and discusses the main results of this survey: We have identified that field updates will be deployed more frequently in the future, and that over-the-air communication is an efficient way to realize them. The reported main update reasons are bug fixes and function improvement. However, the shortening release and update cycles, the increasing number of variants, and the multidisciplinarity in the automotive field are major challenges requiring suitable processes, methods, and tools to achieve software that operates correctly.

关键词： Software Automotive engineering Computer bugs Automobiles Market research Computer architecture Industries

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