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International Symposium on Digital Forensic and Security (ISDFS)

作者： Bahaddin Erdem Murat Karabatak Department of Computer Programming Bitlis Eren University Bitlis Turkey Department of Software Engineering Firat University Elaziğ Turkey

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

This study aims to reveal the best deep learning models that are improved and optimized by predicting undesirable behavior patterns using a dataset consisting of artificial and real exam data of students taking online distance education courses in an online environment through the distance education system. Using online exam data of 129 students, the researchers conducted analysis with two different scenarios to determine the best prediction performance through regression and classification models. The model we proposed was determined as a four-layer DNN with 80.4% test performance in detecting students who “cheated” from undesirable behavior patterns, which was performed with K-10, K-5 and K-3 cross-validation. The results prove that students' online distance education exam data can be easily applied to the DNN model. The models presented in the study provide a roadmap for educational institutions to evaluate their online examination practices and develop more effective strategies for academic honesty.

关键词： Deep learning Analytical models Digital forensics Predictive models Nonhomogeneous media Data models Educational courses Fraud Security

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Optimistic Versioning for Conflict-tolerant Collaborative Blended Modeling 10

Optimistic Versioning for Conflict-tolerant Collaborative Bl...

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STAF 2022 Workshop: 10th International Workshop on Bidirectional Transformations, BX 2022, 2nd International Workshop on Foundations and Practice of Visual Modeling, FPVM 2022 and 2nd International Workshop on MDE for Smart IoT Systems, MeSS 2022

作者： Exelmans, Joeri Pietron, Jakob Raschke, Alexander Vangheluwe, Hans Tichy, Matthias Department of Computer Science University of Antwerp - Flanders Make Antwerp Belgium Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

Optimistic versioning is a key component in supporting collaborative workflows. Text-based versioning has been widely adopted for versioning code, but in model-driven engineering, dealing with visual concrete syntaxes, new methods are required. In the case of blended modeling, a mixture of both textual and visual syntaxes, concurrently editable and synchronizable, introduces additional challenges. We propose a type of operation-based versioning to record not only user edits, but also bi-directional change propagations between concrete and abstract syntax. This way we can support blended modeling with layout continuity, and flexible handling of missing information (e. g., layout information) when rendering changes from abstract to concrete syntax. In addition, the proposed versioning approach enables collaborative conflict resolution by allowing partial conflict resolution, thus deferring a final resolution. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Abstracting

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A Comparative Analysis of Multi-agent Simulation Platforms for Energy and Mobility Management 20th

A Comparative Analysis of Multi-agent Simulation Platforms ...

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Proceedings of the 20th European Conference on Multi-Agent Systems, EUMAS 2023

作者： Ali, Aliyu Tanko Leucker, Martin Schuldei, Andreas Stellbrink, Leonard Sachenbacher, Martin Institute for Software Engineering and Programming Languages University of Lübeck Ratzeburger Allee 160 Lübeck Germany Institute for Multimedia and Interactive Systems University of Lübeck Ratzeburger Allee 160 Lübeck Germany

ISBN: (纸本)9783031432637

Effective energy and mobility management benefits from multi-agent simulations (MAS) to model complex interactions among various agent types. Selecting the optimal MAS platform to implement and simulate these interactions is vital for achieving accurate results, scalability to realistic problem sizes, and efficient computational performance. This paper investigates the energy and mobility domain and identifies key parameters such as the number and complexity of agents, parallel computing power, CPU requirements etc., for developing MAS in the context of this domain. It then presents a comprehensive evaluation of various MAS development platforms. Using a multi-level selection and elimination approach, we narrowed down our evaluation to two final candidates. We then implemented key aspects of our model in both platforms to compare them in terms of practical relevance. Our findings reveal that the *** platform outperforms the Mesa platform in terms of runtime performance, has a smaller memory footprint for large numbers of agents, and offers scalability, making it the most suitable choice for developing MAS for integrated energy and mobility models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Scalability

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Research and Development of Kubernetes Operator for Machine Learning Pipelines

Research and Development of Kubernetes Operator for Machine ...

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2025 International Russian Smart Industry Conference, SmartIndustryCon 2025

作者： Trapezin, Andrey Filianin, Ivan ITMO University Faculty of Programming and Infocommunications St. Petersburg Russia ITMO University Faculty of Software Engineering and Computer Engineering St. Petersburg Russia

ISBN: (纸本)9798331511241

The current research work addresses the problem of automating the delivery of machine learning models from MLflow to Kubernetes infrastructure. To solve the mentioned problem, a Kubernetes operator has been developed to automate the delivery of machine learning models to production by integrating MLflow for model tracking and Seldon Core for model serving. The developed operator allows data scientists to deploy models while maintaining the familiar MLflow environment. The operator's automatic deployment triggers upon tagging models in MLflow, greatly simplifying engineers' tasks and minimizing the need for manual infrastructure configuration. By automating configuration tasks and optimizing deployment workflows, the solution achieves a 40-50% reduction in model time to deployment (TTD) metric compared to manual processes and decreases error rates from 15% to around 3%. The practical relevance of the work is that it simplifies collaboration between data and infrastructure teams by providing a unified deployment framework, resulting in faster, more reliable, and automated integration of machine learning models into an organisation's business processes. © 2025 IEEE.

关键词： engineering education

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WIP: An Engaging Undergraduate Intro to Model Checking in software engineering Using TLA+

arXiv

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arXiv 2024年

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Software and Systems Laboratory Department of Computer Science Loyola University Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one’s undergraduate studies, (3) demonstrate how to address successive "failures" through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Research and Development of Kubernetes Operator for Machine Learning Pipelines

Research and Development of Kubernetes Operator for Machine ...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Andrey Trapezin Ivan Filianin Faculty of Programming and Infocommunications ITMO University St. Petersburg Russia Faculty of Software Engineering and Computer Engineering ITMO University St. Petersburg Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

关键词： Production systems Error analysis Machine learning Manuals Tagging Data models Reliability Research and development Load modeling Resilience

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Effectiveness of Performance Visualizations for Declarative Model Transformations

Effectiveness of Performance Visualizations for Declarative ...

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IEEE International Workshop on Visualizing software for Understanding and Analysis (VISSOFT)

作者： Raffaela Groner Matthias Tichy Dept. of Computer Science and Engineering Chalmers | University of Gothenburg Gothenburg Sweden Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

ISBN: (数字)9798331528485

ISBN: (纸本)9798331528492

Several profilers for general-purpose languages like Java offer visualizations to support users in understanding the execution of a program and identifying the causes of a performance issue. Unfortunately, these performance visualizations are difficult to reuse in profilers for declarative model transformations since they cannot display transformation-specific information. For example, a profiler for a declarative model transformation language must provide information on the traversal of the input model since it impacts the performance but is hidden from the developer. Moreover, the respective visualization must scale for input models that consist of several thousand model elements. Hence, we developed performance visualizations for the declarative model transformation language Henshin that provide insights into the transformation execution. Subsequently, we performed a mixed methods study with 18 Henshin novices to evaluate the effectiveness of our visualizations. In our study, the participants tried to improve the execution performance of four transformations by performing a root cause analysis using our visualizations. The results of our study show that depending on the task, between 16 and 18 participants understood the execution of a transformation correctly based on our visualizations. Moreover, between 12 and 18 participants proposed effective optimizations using our visualizations.

关键词： Visualization Root cause analysis Java Color software Encoding Data mining Optimization

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Realizing Scenario-Based Verification Tests of Automated Vehicles With an Ai-Controlled Surrounding Vehicle in a Practice-Relevant Context

Realizing Scenario-Based Verification Tests of Automated Veh...

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International Conference on Intelligent Transportation

作者： Felix Beringhoff Joel Greenyer Christian Roesener Matthias Tichy Volkswagen AG Wolfsburg Germany FHDW Hannover Hannover Germany Institute for Software Engineering and Programming Languages Ulm University Germany

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Scenario-based testing is seen as a key for the verification and validation of automated vehicles (AV). In a test scenario, the AV is tested under pre-defined traffic conditions. However, realizing those traffic conditions is challenging due to the autonomously behaving AV. The AV decides on its own, whether it gets into the test scenario conditions at all, e.g., by deciding on which lane it wants to drive or at which velocity it is driving. In order to influence the AV's decision making in a required way to realize a test scenario condition, we implement a novel AI method for controlling a surrounding vehicle (SV) of the AV. The AI-controlled SV (AISV) consists of a reinforcement learning (RL) agent which is trained to, e.g., nudge the AV into changing lanes. In contrast to current common practice, this approach does not require the manual tailoring of triggers and actions for controlling the SV. In this paper, we report on a working design of the RL framework and experiments regarding three different training scopes for the RL agent. We distinguish specialized agents which are trained to reach a single scenario condition and two sorts of generalized agents which shall be capable of reaching a set of scenario conditions. The results show that specialized agents perform the best with a success rate of up to 100 %. However, the generalized agents perform better in realizing scenario conditions which are not known to the agent from training. We also report on an implementation of the approach in a hardware-in-the-loop-simulation (HIL) test bench used in industrial practice and discuss a first try-out.

关键词： Training Symbiosis Roads XML Prototypes Reinforcement learning Manuals Artificial intelligence Intelligent transportation systems Testing

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FreeCHR: An Algebraic Framework for CHR-Embeddings

arXiv

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arXiv 2023年

作者： Rechenberger, Sascha Frühwirth, Thom Institute for Software Engineering and Programming Languages Ulm University Albert-Einstein-Allee 11 Ulm89069 Germany

We introduce the framework FreeCHR which formalizes the embedding of Constraint Handling Rules (CHR) into a host language, using the concept of initial algebra semantics from category theory, to establish a high-level implementation scheme for CHR as well as a common formalization for both theory and practice. We propose a lifting of the syntax of CHR via an endofunctor in the category Set and a lifting of the very abstract operational semantics of CHR into FreeCHR, using the free algebra, generated by the endofunctor and give proofs for soundness and completeness w.r.t. their original definition. © 2023, CC BY.

关键词： Semantics

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Spam Detection With Fasttext Based Features

Spam Detection With Fasttext Based Features

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Innovations in Intelligent Systems and Applications Conference

作者： Talha Karadeniz Gül Tokdemir H. Hakan Maraş Department of Software Engineering Çankaya University Ankara Turkey Department of Computer Engineering Çankaya University Ankara Turkey Department of Computer Programming Çankaya University Ankara Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

Fasttext is a powerful word representation method that creates word representations based on vectors of character n-grams. In this work, we propose a method that utilizes fasttext features for a novel feature engineering model for the spam detection problem. In the feature engineering method, the combination of average, mean of second derivative; mean peak and standard deviation of fasttext features are computed. Finally, tf-idf features are also considered for the modeling process. The success of each feature engineering technique is measured and reported. The combination of the five feature extraction methods, tested on two spam detection datasets, yielded promising results with an accuracy of 0.978 on e-mail spam detection and an accuracy of 0.986 on sms spam classification.

关键词： Technological innovation Accuracy Unsolicited e-mail Computational modeling Feature extraction Vectors Intelligent systems Standards Postal services

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