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检索条件"任意字段=19th International Conference on Software Engineering and Knowledge Engineering"

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Mapping software-engineering Industry AI Use to software-engineering Curriculum: Developing the AI-USE Framework 4

Mapping Software-Engineering Industry AI Use to Software-Eng...

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4th international conference on AI Research, ICAIR 2024

作者： Lilholt, Addison Heverin, thomas The Baldwin School Bryn Mawr United States

ISBN: (纸本)9798331309466

Estimates predict a global deficit of 4 million software engineers by 2025, further complicated by the software engineering (SE) industry's escalating use of artificial intelligence (AI). To tackle this issue, our research suggests that computer science (CS) curricula in middle and high schools need to be updated to incorporate SE industry segments that significantly employ AI. this strategic curriculum alignment is significant for preparing a workforce equipped to meet future industry demands. Our initial analysis involved reviewing nine international AI education guidelines to evaluate current methods for integrating AI into SE education. the findings indicated a pronounced lack of specific guidance connecting AI applications in the SE industry with educational content. To address this, we performed a systematic literature review of 12 research papers focusing on AI's role across the SE industry, followed by multiple rounds of inductive content analysis. An industry segment was deemed "essential" if it was referenced in 75% or more of the papers' findings. through this method, we identified 10 essential SE industry segments for inclusion in CS education: software development, software maintenance, process improvement, software economics, knowledge management, project management, software testing, software security, quality assurance, and deployment and operations (DevOps). these findings led to the creation of the AI-USE (Artificial Intelligence Usage in software engineering) framework, which maps these 10 key segments to the predominant uses of SE in the industry as identified in the literature. Further inductive content analysis helped us develop subsegments for these essential areas. Ongoing framework development involves refining these subsegments and gathering feedback from industry and academic professionals. We anticipate that the fully developed AI-USE framework will significantly enhance SE education, equipping the next generation of software engineers wi

关键词： Project management

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Log Parsing with Prompt-based Few-shot Learning 23

Log Parsing with Prompt-based Few-shot Learning

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45th IEEE/ACM international conference on software engineering (ICSE)

作者： Le, Van-Hoang Zhang, Hongyu Univ Newcastle Sch Informat & Phys Sci Callaghan NSW Australia Chongqing Univ Sch Big Data & Software Engn Chongqing Peoples R China

ISBN: (纸本)9781665457019

Logs generated by large-scale software systems provide crucial information for engineers to understand the system status and diagnose problems of the systems. Log parsing, which converts raw log messages into structured data, is the first step to enabling automated log analytics. Existing log parsers extract the common part as log templates using statistical features. However, these log parsers often fail to identify the correct templates and parameters because: 1) they often overlook the semantic meaning of log messages, and 2) they require domain-specific knowledge for different log datasets. To address the limitations of existing methods, in this paper, we propose LogPPT to capture the patterns of templates using prompt-based few-shot learning. LogPPT utilises a novel prompt tuning method to recognise keywords and parameters based on a few labelled log data. In addition, an adaptive random sampling algorithm is designed to select a small yet diverse training set. We have conducted extensive experiments on 16 public log datasets. the experimental results show that LogPPT is effective and efficient for log parsing.

关键词： log parsing few-shot learning prompt-tuning deep learning

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Evaluation of Approaches for Documentation in Continuous software Development 18

Evaluation of Approaches for Documentation in Continuous Sof...

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18th international conference on Evaluation of Novel Approaches to software engineering (ENASE)

作者： theunissen, theo Hoppenbrouwers, Stijn Overbeek, Sietse HAN Univ Appl Sci Dept ICT Arnhem Netherlands Radboud Univ Nijmegen Inst Comp & Informat Sci Nijmegen Netherlands Univ Utrecht Dept Informat & Comp Sci Utrecht Netherlands

ISBN: (纸本)9789897586477

With the adoption of values, principles, practices, tools and processes from Agile, Lean, and DevOps, knowledge preservation has become a serious issue because documentation is largely left out. We identify two questions that are relevant for knowledge acquisition and distribution concerning design decisions, rationales, or reasons for code change. the first concerns which knowledge is required upfront to start a project. the second question concerns continuation after initial development and addresses which knowledge is required by those who deploy, use or maintain a software product. We evaluate two relevant approaches for alleviating the issues, which are 'Just enough Upfront' and 'Executable Documentation' with a total of 25 related artifacts. For the evaluation, we conducted a case study supported by a literature review, organizational and project metrics, and a survey. We looked into closed source-code and closed classified source-code. We found two conclusive remarks. First, git commit messages typically contain what has been changed but not why source-code has been changed. Design decisions, rationale, or reasons for code change should be saved as close as possible to the source-code with Git Pull Requests. Second, knowledge about a software product is not only written down in artifacts but is also a social construction between team members.

关键词： Artifacts Continuous software Development Documentation Executable Documentation Just Enough Upfront

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Rural Building in Opole Silesia During the Period of the Frederician Colonization 5th

Rural Building in Opole Silesia During the Period of the Fre...

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5th international Scientific conference on Environmental Challenges in Civil engineering, ECCE 2022

作者： Bajno, Dariusz Fiutak, Marcin Niedostatkiewicz, Maciej Faculty of Civil and Environmental Engineering and Architecture Department of Building Structures Bydgoszcz University of Science and Technology Bydgoszcz Poland Przedsiębiorstwo Projektowo-Uslugowo-Handlowe „MARDOM" Marcin Fiutak Byczyńska 27 Kluczbork46-200 Poland Faculty of Civil and Environmental Engineering Department of Engineering Construction Gdańsk University of Technology Gdańsk Poland

ISBN: (纸本)9783031268786

the aim of the article is to present the rural construction in the Opole countryside (Poland) during the "Frederician colonization". Showing socio-economic areas of Opole villages, differing from each other, the differences of which resulted from the environmental conditions influencing the processes of enfranchisement and industrialization. these processes at the turn of the 17th and 19th centuries influenced the image of the Opole and Upper Silesian villages as well as the development of skeleton and brick construction. By gradually analyzing individual regions of Opole Silesia, one can notice large-scale changes in rural construction, differences in the population density and multiculturalism of the inhabitants of the Opole region, showing the complex settlement process, the effects of which can be seen in the Opole countryside to the present day. the article will discuss the process of "Frederician colonization" and its impact on the change of architecture in the region, as well as the accompanying construction and conservation techniques. A look at regional construction from the turn of the 17th and 19th centuries brings closer the cultural heritage of the region's architecture, allows you to deepen your knowledge of architectural forms and techniques of erecting objects of a bygone era, thus enabling the protection of the historical substance of rural regions of Opole Silesia. the article will also discuss the degree of preservation of the historic substance described above along with the forecast of their durability in the further period of operation. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Brick construction

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If it's not SBOM, then what? How Italian Practitioners Manage the software Supply Chain 40

If it's not SBOM, then what? How Italian Practitioners Manag...

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40th international conference on software Maintenance and Evolution

作者： Nocera, Sabato Di Pentat, Massimiliano Francese, Rita Romano, Simone Scanniello, Giuseppe Univ Salerno Fisciano Italy Univ Sannio Benevento Italy

ISBN: (纸本)9798350395693;9798350395686

A software Bill of Materials (SBOM) describes, in a structured, machine-readable format, the open-source and proprietary components that constitute a software product, including their licenses, versions, vendors, vulnerabilities, and dependency relationships. SBOMs enable practitioners to gain visibility into the software supply chain and monitor any risks associated with software security, licensing, and more. In this industry paper, we present the findings of 10 semi-structured interviews with practitioners with different roles in six different software companies operating in Italy, some of which being very large multinationals. the gathered information indicates that the adoption of SBOMs is low, yet the attention of the software industry to software supply chain-related challenges is high. A possible reason behind this outcome is that the software industry has limited knowledge of SBOMs and software supply chain regulations. Although some participants showed a growing interest in SBOMs, the Italian software industry seems to respond less promptly to this technology. We plan to use these results and those from past research to design a survey with practitioners to have a complete picture of SBOM usage in the software industry.

关键词： software Bill of Materials SBOM software Supply Chain Interviews

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RSChat:Intelligent Question Answering Model for Railway Safety knowledge 24

RSChat:Intelligent Question Answering Model for Railway Safe...

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24th IEEE/ACIS international conference on Computer and Information Science, ICIS 2024

作者： Li, Jinyu Li, Chao Niu, Sen Dai, Bingrong School of Computer and Information Engineering Shanghai Polytechnic University Shanghai China Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (纸本)9798350376647

the release of ChatGPT heralds a new era in artificial intelligence, as large language models (LLMs) empower myriad industries. this paper introduces RSChat, a model based on supervised fine-tuning of multiple large language models (LLMs), exploring a novel paradigm for applying knowledge in railway safety. Initially, we perform prompt engineering using collected domain data, including key information extraction and knowledge expansion. Subsequently, leveraging the constructed fine-tuning datasets, we conduct supervised fine-tuning using multiple large language models (LLMs) as base models. Finally, experimental evaluations demonstrate that RSChat can generate more professional responses in the railway safety domain, exhibiting robust potential for application. © 2024 IEEE.

关键词： Railroad accidents

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AI-Driven Approach to Detect Equivalent Elements within Domain Models 15

AI-Driven Approach to Detect Equivalent Elements within Doma...

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15th international conference on Information and knowledge Technology, IKT 2024

作者： Kasaei, Mohammad-Sajad Sharbaf, Mohammadreza Fatemi, Afsaneh Zamani, Bahman MDSE Research Group Department of Software Engineering University of Isfahan Isfahan Iran

ISBN: (纸本)9798331522254

Domain model stands as a crucial part of software engineering, emerging from collaborative team efforts. Domain modeling involves creating a conceptual representation of a specific problem domain to determine the concepts and relationships. A pivotal step in domain modeling is reviewing the domain model to identify errors and abnormalities. Typically, software engineers engage in a manual review of the domain model diagrams for refinement purposes. However, the process of detecting errors and abnormalities can be time-consuming and error prone. Furthermore, it relies heavily on the expertise of software engineers. A primary concern in domain modeling is the repetition of concepts, which often occurs due to the involvement of multiple engineers. Recently, AI techniques have exhibited remarkable ability in modeling domain. this paper proposes an approach, called ARDEMIS, for equivalence checking that aims to detect semantically similar concepts within domain models. ARDEMIS utilizes the combination of pre-trained model and dictionary to identify equivalent elements. We assess our approach using a real-world case study in the transportation domain. Our findings reveal the ability of ARDEMIS to identify potential equivalent elements. © 2024 IEEE.

关键词： Errors

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Evaluation Methods and Replicability of software Architecture Research Objects

Evaluation Methods and Replicability of Software Architectur...

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2023 Fachtagung des GI-Fachbereichs softwaretechnik, software engineering 2023 - 2023 conference of the GI software engineering Division, software engineering 2023

作者： Konersmann, Marco Kaplan, Angelika Kühn, thomas Heinrich, Robert Koziolek, Anne Reussner, Ralf Jürjens, Jan al-Doori, Mahmood Boltz, Nicolas Ehl, Marco Fuchß, Dominik Großer, Katharina Hahner, Sebastian Keim, Jan Lohr, Matthias Sağlam, Timur Schulz, Sophie Töberg, Jan-Philipp Software Engineering RWTH Aachen University Germany Karlsruhe Institute of Technology Germany University of Koblenz-Landau Germany Fraunhofer Institute for Software and Systems Engineering ISST Germany

ISBN: (纸本)9783885797265

Our paper at the 19th IEEE international conference on software Architecture (ICSA 2022) started by noticing that software Architecture (SA) as research area experienced an increase in empirical research. Empirical research builds a sound foundation for validity and comparability. A current overview of the evaluation and replicability of SA research objects could help to discuss our empirical standards as a community. However, no current overview existed. We assessed the current state of practice of evaluating SA research objects and replication artifact provision in full technical conference papers from ICSA and the European conference on software Architecture (ECSA) 2017-2021. We first developed a categorization schema for SA research object evaluation and artifact provisioning. In a systematic literature review with 153 papers, we then classified the papers according to that schema. From our findings we derive and describe four proposals for improving the state of practice in evaluating SA research objects. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： software architecture

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Joint Extraction of Interaction Features and Attention Mechanism Fused with Entity-Relations 36

Joint Extraction of Interaction Features and Attention Mecha...

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36th international conference on software engineering and knowledge engineering, SEKE 2024

作者： Su, Lisha Yan, Rong College of Computer Science Inner Mongolia University Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot010021 China

ISBN: (纸本)1891706594

Joint extraction of entities and relations is an essential task in information extraction. Recently, tagging-based models have gained attention but with poor performance on overlapping triplets, which confronted the issues like cascading errors, information redundancy, and sensitivity to subject extraction. To solve the issue of overlapping triplets, we propose a model combined Gated Attention Unit (GAU) and Multi-head Attention Mechanism (MHA) in this paper. this model distinguishes features for entities and relations, and performs entity recognition for each head entity, different head entities are matched to the same or different tail entities. then specific tail entity tagging is applied to determine all possible relations and corresponding tails. At the same time, in order to better solve the long-distance dependence and complex multiple relations between entities, GAU and MHA are used to enhance the semantic representation, effectively identify entities and relations, and enhance the learning ability and generalization ability of the model. Experiment results on the public datasets DuIE2.0 and CMeIE show that our model performs better than baselines. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Semantics

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Optimization of Methods for Querying Formal Ontologies in Natural Language Using a Neural Network 16

Optimization of Methods for Querying Formal Ontologies in Na...

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16th international conference on knowledge engineering and Ontology Development, KEOD 2024 as part of 16th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2024

作者： Ondo, Anicet Lepetit Capus, Laurence Bousso, Mamadou Dep. of Computer and Software Engineering Laval University QuebecQCG1V 0A6 Canada Dep. Computer Science Iba Der Thiam University Thies967 Senegal

ISBN: (纸本)9789897587160

A well-designed ontology must be capable of addressing all the needs it is intended to satisfy. this complex task involves gathering all the potential questions from future users that the ontology should answer in order to respond precisely to these requests. However, variations in the questions asked by users for the same need complicate the interrogation process. Consequently, the use of a question-answering system seems to be a more efficient option for translating user queries into the formal SPARQL language. Current methods face significant challenges, including their reliance on predefined patterns, the quality of models and training data, ontology structure, resource complexity for approaches integrating various techniques, and their sensitivity to linguistic variations for the same user need. To overcome these limitations, we propose an optimal classification approach to classify user queries into corresponding SPARQL query classes. this method uses a neural network based on Transformer encoder-decoder architectures, improving both the understanding and generation of SPARQL queries while better adapting to variations in user queries. We have developed a dataset on estate liquidation and Python programming, built from raw data collected from specialist forums and websites. Two transformer models, GPT-2 and T5, were evaluated, with the basic T5 model obtaining a satisfactory score of 97.22%. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Structured Query Language

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