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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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DRMiner: Extracting Latent Design Rationale from Jira Issue Logs 24

DRMiner: Extracting Latent Design Rationale from Jira Issue ...

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39th ACM/IEEE international conference on Automated software engineering (ASE)

作者： Zhao, Jiuang Yang, Zitian Zhang, Li Lian, Xiaoli Yang, Donghao Tan, Xin Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China Beihang Univ Sch Software Beijing Peoples R China Beihang Univ CCSE Beijing Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

software architectures are usually meticulously designed to address multiple quality concerns and support long-term maintenance. However, there may be a lack of motivation for developers to document design rationales (i.e., the design alternatives and the underlying arguments for making or rejecting decisions) when they will not gain immediate benefit, resulting in a lack of standard capture of these rationales. With the turnover of developers, the architecture inevitably becomes eroded. this issue has motivated a number of studies to extract design knowledge from open-source communities in recent years. Unfortunately, none of the existing research has successfully extracted solutions alone with their corresponding arguments due to challenges such as the intricate semantics of online discussions and the lack of benchmarks for design rationale extraction. In this paper, we propose a novel approach, named DRMiner, to automatically mine latent design rationales from developers' live discussion in open-source community (i.e., issue logs in Jira). To better identify solutions and their relevant arguments, DRMiner skillfully decomposes the problem into multiple text classification tasks and tackles them using prompt tuning of large language models (LLMs) and specific heuristic features. To evaluate DRMiner, we acquire issue logs from Cassandra, Flink, and Solr repositories in Jira and form a dataset for design rationale mining. Experimental results show that DRMiner outperforms all baselines and achieves F1 improvements of 24%, 22%, and 20% for mining design rationales, solutions, and arguments, respectively, compared to the best baseline. Furthermore, we investigate the usefulness of the design rationales mined by DRMiner for automated program repair (APR) and find that advanced LLMs, when prompted with these extracted rationales, generate 10x-18x more full-match patches and achieve a 10%-13% gain in CodeBLEU scores.

关键词： Design rationale Issue logs Design discussion Design recovery Program maintenance

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Hybrid Resource Scheduling Model for Data Intensive Computing 19

Hybrid Resource Scheduling Model for Data Intensive Computin...

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19th international conference on Natural Computation, Fuzzy Systems and knowledge Discovery, ICNC-FSKD 2023

作者： Liu, Xiangsong Zhao, Hui Linyi University School of Information Science and Engineering Linyi China

ISBN: (纸本)9798350304398

In a large-scale cluster or cloud computing environment, the execution of data-intensive operations will cause a large amount of redundant energy consumption. In order to improve computing energy efficiency and ensure the service quality of users' operations, the computing resources are first divided into two categories: recyclable and non-recyclable, and a hybrid resource scheduling model is proposed. the two-layer scheduling strategy combining coarse and fine-grained size is adopted to realize coarse-grained energy quota scheduling in the upper layer through a periodic prediction model, so as to improve the utilization rate of computing energy efficiency;at the bottom level, the scheduling of virtual machines according to the scheduling signal and load information of energy quotas is sorted by weights. the simulation experiment results show that compared with other models, the scheduling performance has achieved a good optimization effect, the maximum operation completion time is 4.3%, and the cluster node power consumption is 5.1%. © 2023 IEEE.

关键词： Energy efficiency

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Correlation Learning with Enhanced Attention Mechanism of BERT for Multi-Label Text Classification 19

Correlation Learning with Enhanced Attention Mechanism of BE...

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19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Kato, Yusei Xu, Sheng Fukumoto, Fumiyo Suzuki, Yoshimi Interdisciplinary Graduate School of Medicine Engineering and Agricultural Sciences University of Yamanashi Kofu Japan Graduate Faculty of Interdisciplinary Research University of Yamanashi Kofu Japan

ISBN: (纸本)9798331507817

Semantic features encoded in the labels have a strong influence on multi-label text classification (MLTC) performance. this paper follows the assumption and proposes an MLTC approach with correlation learning. Unlike the existing work focusing on text representation learning, the method jointly learns word-word, label-label, and word-label correlations to classify text. We propose a correlation learning that enhances the attention mechanism of BERT. the experimental results of three benchmark datasets demonstrate that our approach is comparable to the state-of-the-art (SOTA) label-encoded method. Our source codes are available at https://***/ffukumoto/***. © 2025 IEEE.

关键词： Contrastive Learning

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Secure Cryptography Usage in software Development: A Systematic Literature Review 12

Secure Cryptography Usage in Software Development: A Systema...

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12th international conference in software engineering Research and Innovation, CONISOFT 2024

作者： Hernandez-Marcial, Bryan-Josue Limon, Xavier Sanchez-Garcia, Angel J. Perez-Arriaga, Juan Carlos Universidad Veracruzana Facultad de Estadística e Informática Xalapa Mexico

ISBN: (纸本)9798331532116

Cryptography plays a significant role in software engineering, its application is paramount for the security of software systems. However, comprehending and securely utilizing cryptography in software development is complicated and prone to error. To mitigate these challenges, it is crucial to know best practices and utilize appropriate tools to aid in the implementation of secure and accurate cryptography in software projects. Unfortunately, this insightful guidance is frequently fragmented to developers and software engineering students seeking to integrate these principles into their projects. With this problem in mind, we conducted a Systematic Literature Review, yielding 52 primary studies. the review uncovered a range of essential tools, including cryptographic APIs, Integrated Development Environments, and static anal-ysis tools, designed to identify vulnerabilities in the initial phases of software development. Furthermore, we emphasized the importance of implementing effective strategies, such as regularly updating libraries and selecting appropriate cryp-tographic algorithms. On the contrary, we also underscored detrimental practices, such as utilizing outdated functions and depending on unreliable sources like online forums. Many studies mention that tools are being developed and tested for elementary or high school students to start learning basic cybersecurity topics, including cryptography. there is also a trend for developers to use these tools to mitigate vulnerabilities in software developments, highlighting the importance of this topic. © 2024 IEEE.

关键词： Cryptography Secure development Security software engineering

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An Ontology of Cyberspace as a Basis for Decision-Making in Cyberoperations

An Ontology of Cyberspace as a Basis for Decision-Making in ...

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19th international conference on Cyber Warfare and Security

作者： Grandin, Alexander Finnish Def Res Agcy Riihimaki Finland

ISBN: (纸本)9781914587962;9781914587979

In the cyberoperations community there is a commonly accepted starting point for describing cyberspace as comprising of multiple planes through which information flows. However, the model is not a tool that facilitates planning and executing cyberoperations. Tools do exist in the form of technical cybersecurity ontologies. At the moment the link between technical ontologies, that are the tools of experts, and the operational planning process is limited. these technical ontologies provide automated information that would support operational planning. At the moment cybersecurity experts translate the information that military professionals need, which may cause insufficiencies or distortions in communication or cause inconsistencies in the planning process. this paper presents the ongoing work of developing a model of cyberspace in the form of a core ontology. the ontology describes the flow of digital information between persons and the enabling technology as well as geographical data. It is intended as a tool that supports operational planning and decision-making in and through cyberspace, by enabling automation and reasoning. the model is created using the well-established Constructive Research Approach (CRA) methodology, and is developed on earlier research. CRA consists of six phases in which (1) the problem is defined, (2) an understanding of the topic is generated, (3) a solution (model) is constructed which then is (4) demonstrated. then the models (5) theoretical connections are presented and the (6) scope of applicability is assessed. the challenges of developing an ontology of cyberspace as part of the third phase of the methodology are in focus. the ontology serves as an operational core ontology, aiming to link cybersecurity domain ontologies to the DOLCE+DnS Ultralite (DUL) foundational ontology. the ontology is based on research in Cyberspace Geography and Cyber Terrain. No earlier attempts at creating a core ontology of cyberspace grounded in a foundat

关键词： Cyberspace Cybersecurity Ontology Semantic web knowledge engineering

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Chord Generation Based on Transformer and Color Harmony theory 19

Chord Generation Based on Transformer and Color Harmony Theo...

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19th international conference on Natural Computation, Fuzzy Systems and knowledge Discovery, ICNC-FSKD 2023

作者： Li, Shuyu Hong, Yun Wei, Xinyue Wu, Tingyu Xi'an Jiaotong University Faculty of Electronic and Information Engineering Xi'an China

ISBN: (纸本)9798350304398

Artificial intelligence has been widely used in the field of music and achieved good results. As an important concept in music, chord generation is one of the basic tasks in composition. the application of machine learning in music is of great significance to human's understanding of artificial intelligence and music, and artificial intelligence technology can also enrich people's research in music. In this paper, a chord generation model is constructed based on Transformer to further dig into the internal structure of chords and consider chords from the aspect of chord notes, hoping to generate more delicate and flexible chords. At the same time, combined with the color harmony theory, the evaluation method and mapping method meeting the rules of music theory are constructed, hoping to get better output effect through a simple model, and the template mapping method is used to improve the actual effect and extensibility of the model. © 2023 IEEE.

关键词： Music

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Design of A FFT Processor Based on the Variable Mixed-radix Algorithm 19

Design of A FFT Processor Based on The Variable Mixed-radix ...

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19th international conference on Natural Computation, Fuzzy Systems and knowledge Discovery, ICNC-FSKD 2023

作者： Liu, Youyao Gai, Shihao Liu, Ping Huang, Haimei Xi'an University of Posts and Telecommunication School of Electronic Engineering Xi'an China

ISBN: (纸本)9798350304398

FFT processors are widely used in digital signal processing, but they cause a lot of hardware consumption when computing large point sequences. this paper introduces a high-performance, low-complexity, and the configurable number of points FFT processors. At the algorithm level, a Variable Mixed-radix algorithm is proposed to reduce the computation of complex multiplication by 10-20% and improve the throughput rate by sequence advance splitting method;at the hardware level, a parallel iterative architecture and array processing architecture are combined to enhance the processor operation efficiency by RAM reconfiguration method. After experimental verification and analysis, it is concluded that the design finally supports 1k-32k points sequence FFT computation. the computation speed at processing 32k points is improved by 11.14% compared with the same processor type. © 2023 IEEE.

关键词： Fast Fourier transforms

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the FormAI Dataset: Generative AI in software Security through the Lens of Formal Verification 19

The FormAI Dataset: Generative AI in Software Security throu...

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19th international conference on Predictive Models and Data Analytics in software engineering (PROMISE)

作者： Tihanyi, Norbert Bisztray, Tamas Jain, Ridhi Ferrag, Mohamed Amine Cordeiro, Lucas C. Mavroeidis, Vasileios Technol Innovat Inst Abu Dhabi U Arab Emirates Univ Oslo Oslo Norway Univ Manchester Manchester Lancs England

ISBN: (纸本)9798400703751

this paper presents the FormAI dataset, a large collection of 112, 000 AI-generated compilable and independent C programs with vulnerability classification. We introduce a dynamic zero-shot prompting technique constructed to spawn diverse programs utilizing Large Language Models (LLMs). the dataset is generated by GPT-3.5-turbo and comprises programs with varying levels of complexity. Some programs handle complicated tasks like network management, table games, or encryption, while others deal with simpler tasks like string manipulation. Every program is labeled with the vulnerabilities found within the source code, indicating the type, line number, and vulnerable function name. this is accomplished by employing a formal verification method using the Efficient SMT-based Bounded Model Checker (ESBMC), which uses model checking, abstract interpretation, constraint programming, and satisfiability modulo theories to reason over safety/security properties in programs. this approach definitively detects vulnerabilities and offers a formal model known as a counterexample, thus eliminating the possibility of generating false positive reports. We have associated the identified vulnerabilities with Common Weakness Enumeration (CWE) numbers. We make the source code available for the 112, 000 programs, accompanied by a separate file containing the vulnerabilities detected in each program, making the dataset ideal for training LLMs and machine learning algorithms. Our study unveiled that according to ESBMC, 51.24% of the programs generated by GPT-3.5 contained vulnerabilities, thereby presenting considerable risks to software safety and security.

关键词： Dataset Vulnerability Classification Large Language Models Formal Verification software Security Artificial Intelligence

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Agile Requirements engineering in a Distributed Environment: Experiences from the software Industry during Unprecedented Global Challenges 48

Agile Requirements Engineering in a Distributed Environment:...

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48th Annual IEEE international Computers, software, and Applications conference (COMPSAC) - Digital Development for a Better Future

作者： Li, Yishu Keung, Jacky Bennin, Kwabena Ebo Ma, Xiaoxue Zhang, Jingyu Yang, Zhen City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Wageningen Univ & Res Informat Technol Grp Wageningen Netherlands Shandong Univ Sch Comp Sci & Technol Qingdao Peoples R China

ISBN: (纸本)9798350376975;9798350376968

Unprecedented global challenges such as the COVID-19 pandemic necessitated a widespread transition to Work-From-Home (WFH) arrangements for project teams, posing significant challenges in conveying requirements within agile Requirements engineering (RE). While numerous studies have examined the impact of transitioning work routines during the pandemic, limited research exists on the specific challenges of agile RE operating within the WFH context. Given the pervasive shift in the software development ecosystem worldwide, where WFH is projected to persist even in the post-COVID era, it is imperative to ascertain the challenges associated with WFH-based agile RE. During the pandemic, we collaborated with startups to conduct an industry-academia project. By adopting the methodology of action research, this study comprehensively analyzed agile RE practices and reported the key challenges encountered within the WFH context. To mitigate these challenges, several collaborative RE techniques were employed in three intervention cycles. Interviews were conducted to thoroughly analyze the results. this study also provides insights into collaborative RE techniques and valuable lessons learned. Considering the increasing prevalence of WFH as a working mode in the post-pandemic era, this study equips the community with practical strategies to navigate agile RE challenges and better prepare for unprecedented challenges in the future.

关键词： Agile requirements engineering challenges Work from home software startup Action research

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Language, Camera, Autonomy! Prompt-engineered Robot Control for Rapidly Evolving Deployment 24

Language, Camera, Autonomy! Prompt-engineered Robot Control ...

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19th Annual ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Macdonald, Jacob P. Mallick, Rohit Wollaber, Allan B. Pena, Jaime D. McNeese, Nathan Siu, Ho Chit MIT Lincoln Lab Lexington MA 02421 USA Clemson Univ Clemson SC USA

ISBN: (纸本)9798400703232

the Context-observant LLM-Enabled Autonomous Robots (CLEAR) platform offers a general solution for large language model (LLM)-enabled robot autonomy. CLEAR-controlled robots use natural language to perceive and interact with their environment: contextual description deriving from computer vision and optional human commands prompt intelligent LLM responses that map to robotic actions. By emphasizing prompting, system behavior is programmed without manipulating code, and unlike other LLM-based robot control methods, we do not perform any model fine-tuning. CLEAR employs of-the-shelf pre-trained machine learning models for controlling robots ranging from simulated quadcopters to terrestrial quadrupeds. We provide the open-source CLEAR platform, along with sample implementations for a Unity-based quadcopter and Boston Dynamics Spot (R) robot. Each LLM used, GPT-3.5, GPT-4, and LLaMA2, exhibited behavioral differences when embodied by CLEAR, contrasting in actuation preference, ability to apply new knowledge, and receptivity to human instruction. GPT-4 demonstrates best performance compared to GPT-3.5 and LLaMA2, showing successful task execution 97% of the time. the CLEAR platform contributes to HRI by increasing the usability of robotics for natural human interaction.

关键词： large language models computer vision robotics software

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