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Encoding Domain knowledge in Log Analysis 40

Encoding Domain Knowledge in Log Analysis

引用

40th international conference on software Maintenance and Evolution

作者： Zamfirov, Filip Dams, Dennis Seraj, Mazyar Serebrenik, Alexander Eindhoven Univ Technol Eindhoven Netherlands TNO ESI Eindhoven Netherlands

ISBN: (纸本)9798350395693;9798350395686

software developers often use logs to, e.g., investigate bugs, familiarize themselves with the underlying system, or improve performance. To do so, they commonly rely on text editors or their own scripts. this lack of appropriate tooling remains a primary challenge in the industrial application of log analysis (state-of-the-practice), despite many tools and techniques proposed by previous scientific studies (state-of-the-art). To aid in bridging this gap between industry and academia, between state-of-the-practice and state-of-the-art, we zoom in on the ways developers perform log analysis. In particular, we conduct an exploratory case study to understand what structures developers identify in logs and how they utilize their knowledge in this process. Based on the results of the case study, we identify two classes of features, one related to encoding domain knowledge and another one related to sharing domain knowledge. We implement two features from the first class in an open-source log analysis platform designed in collaboration with our industrial partner. To evaluate the impact of the implemented features on log analysis, we conduct a user evaluation with software developers from our industrial partner. During this evaluation developers complete several tasks using the features and complete a usability questionnaire. Results show that users are able to encode their domain knowledge about the logs during their analysis. Furthermore, we observe that participants value highly ease of use and indicate an interest in using the features in their current practice. this sentiment is reflected in the resulting scores of the usability questionnaire, indicating above-average usability. Our findings pave the way to bridge the gap between academia and industry and facilitate the application of advanced log analysis approaches in industry.

关键词： Log Analysis Event Logging Industry Domain software Logs

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An Industry Case Study on Adoption of AI-based Programming Assistants 44

An Industry Case Study on Adoption of AI-based Programming A...

引用

ACM/IEEE 46th international conference on software engineering - software engineering in Practice (ICSE-SEIP)

作者： Davila, Nicole Wiese, Igor Steinmacher, Igor da Silva, Lucas Lucio Kawamoto, Andre Peres Favaro, Gilson Jose Nunes, Ingrid Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil UTFPR Campo Mourao PR Brazil No Arizona Univ Flagstaff AZ USA Coamo Agroind Cooperat Campo Mourao PR Brazil Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9798400702174

Programming assistants based on artificial intelligence (AI), such as ChatGPT and Github Copilot, have gained worldwide popularity recently. Studies in software development have explored the adoption of these tools, investigating their characteristics and impacts and how practitioners interact and perceive them. To contribute to this growing body of knowledge, in this study, we aim to explore the adoption of AI-based programming assistants in the Brazilian industry. More specifically, we aim to understand how practitioners of a particular Brazilian agroindustry-related company perceive and use AI-based tools to develop software. Using an online survey, we collected and analyzed 72 responses from employees of the studied company. Our findings suggest that practitioners mainly adopt ChatGPT and Github Copilot, interacting with these tools to accelerate online searching, typing, and syntax recall. A recurrent difficulty is the lack of context in the suggestions provided by these tools, but participants work on detailed descriptions to contextualize and cope with this challenge. Among the reasons for not using AI-based tools, the most influential is that participants use a commercial programming language, i.e., Uniface, which these tools lack examples. Our results provide insights into the state of the practice related to AI-based programming assistants and discuss implications for practitioners and researchers.

关键词： Artificial Intelligence Generative AI ChatGPT Industry Case Study software Development

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Cluster Analysis in the Identification of Patterns in software Development with Agile Methodologies: A Systematic Literature Review 12

Cluster Analysis in the Identification of Patterns in Softwa...

引用

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

作者： Mercader-Olivares, Iskander E. Martinez-Moreno, Patricia Vergara-Camacho, Jose A. Sanchez-Garcia, Angel J. Ocharan-Hernandez, Jorge Octavio Universidad Veracruzana Facultad de Contaduría y Administración Veracruz Coatzacoalcos Mexico Universidad Veracruzana Facultad de Estadística e Informótica Veracruz Xalapa Mexico

ISBN: (纸本)9798331532116

software engineering is a discipline that aims to deliver quality software products. To this end, several development methodologies have been proposed, with agile methodologies being the most recently used, which promote the continuous delivery of functional software in short cycles called iterations or sprints. In these deliveries, there are activities where the identification of patterns in different software arti-facts is necessary. An example of this is the detection of similar artifacts to avoid redundancy or reuse artifacts. this study presents a systematic review of the literature that seeks to analyze the activities, development stages, benefits, and challenges that have been reported when applying various cluster analysis algorithms to identify patterns in agile methodologies. Fifteen primary studies selected through the Kitchenham methodology were analyzed. It was observed that k-means, k-medoids, and hierarchical clustering are the most used approaches in various stages of development such as requirements, design, and testing. Furthermore, the most analyzed artifacts were user stories. Finally, the studies reveal various advantages, such as pattern identification without a priori knowledge, variance reduction, and development time reduction, among others. However, the parameterization of these algorithms is still a fundamental challenge to be addressed in future work. © 2024 IEEE.

关键词： software quality

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knowledge Sharing in software Development: A Conceptual Framework 15

Knowledge Sharing in Software Development: A Conceptual Fram...

引用

15th international conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Chugh, Mitali UPES Dehradun India

ISBN: (纸本)9798331300579

software development is immensely dependent on knowledge. thus, software development organizations line up knowledge management (KM) to realistically apply the knowledge and renovate solutions for addressing challenges through the different stages of software development. KM facilitates these organizations to obtain and maintain a competitive advantage, specifically from the perspective of agile software development, wherever it nurtures collaboration and management among collocated or cross-functional development teams. the focus of this study is to investigate knowledge sharing in agile software projects and to identify the KS strategies and practices employed by agile teams and practitioners in the software development environment. A conceptual framework has been proposed to facilitate knowledge sharing within both collocated and distributed agile teams. this framework draws upon established theories and practices from knowledge management, organizational behavior, and agile methodologies. It presents a structured approach to understanding and addressing the various factors that influence knowledge sharing within agile teams. the conceptual framework covers elements such as communication, knowledge repositories, iterative development, customer collaboration, and engineering practices. In essence, this paper acts as a valued source for researchers, practitioners, and software development teams pursuing to enhance knowledge sharing in the agile context. By implementing the potential elements of the conceptual framework, organizations can unlock new possibilities for efficient knowledge transfer, collaboration, and innovation, ultimately driving the success of agile software development projects in an increasingly dynamic and technologically advanced world. © Grenze Scientific Society, 2024.

关键词： knowledge representation

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Design Principles for Collaborative Generative AI Systems in software Development 19th

Design Principles for Collaborative Generative AI Systems in...

引用

19th international conference on Design Science Research in Information Systems and Technology (DESRIST) - Design Science Research for a Resilient Future

作者： Chen, Johannes Zacharias, Jan Goethe Univ Frankfurt Chair Informat Syst & Informat Management Frankfurt Germany

ISBN: (纸本)9783031611742;9783031611759

Generative artificial intelligence (GAI) has the potential to transform software development practices with prior research indicating significant overall enhancements in developers' productivity. However, there exists a lack of design knowledge for organization-specific GAI systems to assist software development. To bridge this research gap, we derive a design framework for collaborative GAI systems in software development following design science research. Specifically, we conducted eight interviews with practitioners and reviewed extant literature to formulate design requirements and design principles. In our analysis of the literature and our qualitative data, we identify problems surrounding usability, data privacy, hallucination and transparency. To address these problems, we propose GAI system designs that enable user-centricity, data protection, quality control and communication. Our findings contribute valuable design knowledge to the field of generative AI and organizational software development practices.

关键词： Generative Artificial Intelligence Large Language Models Programming Assistant software Development Design Science Research

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Digital Supply Chain Management in Construction Materials in China: the Example of Glodon BIM software 6

Digital Supply Chain Management in Construction Materials in...

引用

6th international conference on Traffic engineering and Transportation System, ICTETS 2022

作者： Deng, Bin School of Housing Building and Planning Universiti Sains Malaysia USM Pinang Pulau11800 Malaysia

ISBN: (纸本)9781510663053

Computer technology in 19th-century project construction has been integrated into supply chain management, digital supply chain management is officially normalized in the 21st century, and Glodon BIM software has become a new type of practical supply chain management software. Traditional handwriting and Excel software supply chain records can no longer meet today's multiple types of diversified construction supply materials. Numerous scholars were studying BIM and supply chains, but the biggest difference in context is that this research is dedicated to addressing the supply chain model of some of the rough construction sites in China, with the aim of incorporating digital supply chain optimization management. the thesis takes a case study approach to research overall, using a housing construction project in a central Chinese city as an example to complete a digital simulation of the materials supply chain management for a construction project. this study reveals three new advantages of digital supply chain management for housing construction projects, namely efficient data collection and processes, organized records and fast search. the study shows that the application of Glodon BIM software is able to exploit these three new highlights and improve the speed and accuracy of supply chain management. © 2023 SPIE.

关键词： Supply chain management

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Automated Fault Detection Framework for Reliable Provision of IoT Applications in Agriculture 19

Automated Fault Detection Framework for Reliable Provision o...

引用

19th international conference on the Design of Reliable Communication Networks (DRCN)

作者： Attarha, Shadi Band, Saurabh Forster, Anna Univ Bremen Dept Commun Networks Bremen Germany

ISBN: (纸本)9781665475983

With the growth of Internet-of-things (IoT), smart agriculture has become one of the most compelling IoT applications that supports crop management and better resource utilization. In this context, the quality of data gathered by widely distributed IoT edge devices has become critical to guarantee the accuracy of decisions in data-driven applications and costeffectiveness. the data may be inaccurate and contain errors due to adverse environmental conditions or device faults. Supporting knowledge-based systems for monitoring and analyzing collected data to ensure the reliability of IoT services is vital. However, several challenges are encountered in fault detection for IoT applications, such as mimicking normal sensor behaviour by a faulty sensor, limited time and workforce. Also, the lack of labelled datasets containing both normal and real abnormal data points has affected the set of satisfactory data analysis methods. this work aims to propose a novel fault detection framework by utilizing a systematic feature engineering technique which is able to automatically identify abnormal data points, even nontrivial ones. the feature engineering technique helps to build a more reliable anomaly detection model, shortens the training phase, and preserves the sensor against unseen anomalies. Moreover, we provide collections of labelled datasets obtained from experimental situations from various sensors with and without sensor faults to evaluate our approach. the experimental results indicate that the proposed anomaly detection approach combined with the feature engineering technique outperforms established approaches, which are applied to the raw data without any features. It can be seen that extracting meaningful features is a pivotal step for having more precise anomaly detection.

关键词： Fault detection Time series data analysis Feature engineering Internet-of-things(IoT) Smart agriculture Smart Farming

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SeeHow: Workflow Extraction from Programming Screencasts through Action-Aware Video Analytics 23

SeeHow: Workflow Extraction from Programming Screencasts thr...

引用

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

作者： Zhao, Dehai Xing, Zhenchang Xia, Xin Ye, Deheng Xu, Xiwei Zhu, Liming Australian Natl Univ Canberra ACT Australia CSIRO Data61 Sydney NSW Australia Huawei Software Engn Applicat Technol Lab Shenzhen Peoples R China Tencent AI Lab Shenzhen Guangdong Peoples R China

ISBN: (纸本)9781665457019

Programming screencasts (e.g., video tutorials on Youtube or live coding stream on Twitch) are important knowledge source for developers to learn programming knowledge, especially the workflow of completing a programming task. Nonetheless, the image nature of programming screencasts limits the accessibility of screencast content and the workflow embedded in it, resulting in a gap to access and interact with the content and workflow in programming screencasts. Existing non-intrusive methods are limited to extract either primitive human-computer interaction (HCI) actions or coarse-grained video fragments. In this work, we leverage Computer Vision (CV) techniques to build a programming screencast analysis tool which can automatically extract code-line editing steps (enter text, delete text, edit text and select text) from screencasts. Given a programming screencast, our approach outputs a sequence of coding steps and code snippets involved in each step, which we refer to as programming workflow. the proposed method is evaluated on 41 hours of tutorial videos and live coding screencasts with diverse programming environments. the results demonstrate our tool can extract code-line editing steps accurately and the extracted workflow steps can be intuitively understood by developers.

关键词： Screencast Computer vision Workflow extraction Action recognition

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Lattice-Based Decomposition of Transitive Homogeneous Class Hierarchies∗ 20

Lattice-Based Decomposition of Transitive Homogeneous Class ...

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20th IEEE international conference on Intelligent Computer Communication and Processing conference, ICCP 2024

作者： Terletskyi, Dmytro O. V. M. Glushkov Institute of Cybernetics of Nas of Ukraine Department of Methods and Technological Tools for Creating Intelligent Software Systems Kyiv Ukraine

ISBN: (纸本)9798331539979

the decomposition of conceptual hierarchies is a significant task in knowledge engineering and software engineering, allowing the extraction of hidden or non-obvious knowledge pieces, or software subsystems, and the relations between them. During the last decades, many different approaches to the analysis and decomposition of conceptual hierarchies were developed, however, most of them do not pay enough attention to the semantic consistency of the decomposition, considering the internal semantic dependencies between the class attributes. Consequently, extracted knowledge items and software subsystems, can be semantically inconsistent due to the contradiction with such dependencies and model unrealistic or impossible entities or subsystems within a particular domain. therefore, we propose a new approach to conceptual hierarchy decomposition based on the internal semantic dependencies between the properties and methods of the hierarchy members. Implementing the approach, an appropriate algorithm was developed for the decomposition of class hierarchies within the object-oriented dynamic networks, that constructs only semantically consistent subclasses and sub hierarchies. To demonstrate the main scenarios of algorithm application, we provided a comprehensive example of the decomposition of conceptual hierarchy, consisting of homogeneous classes of objects. © 2024 IEEE.

关键词： class decom-position Conceptual hierarchies decomposition decomposition consistency internal semantic dependencies

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Detecting Scattered and Tangled Quality Concerns in Source Code to Aid Maintenance and Evolution Tasks 23

Detecting Scattered and Tangled Quality Concerns in Source C...

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

作者： Krasniqi, Rrezarta Univ North Texas Dept Comp Sci & Engn Denton TX 76203 USA

ISBN: (纸本)9798350322637

Quality concerns, such as reliability, security, usability concerns, among others, are typically well-defined and prioritized at the requirement level with the set goal of achieving high quality, robust, user-friendly, and trustworthy systems. However, quality concerns are challenging to address at the implementation level. Often they are scattered across multiple modules in the codebase. In other instances, they are tangled with functional ones within a single module. Reasoning about quality concerns and their interactions with functional ones while being hindered by the effects of scattered and tangled code can only yield to more unseen problems. For example, developers can inadvertently retrofit new bugs or wrongly implement new features that deviate from original system requirement specifications. the goal of this thesis is twofold. First, we aim to detect quality concerns implemented at code level to differentiate them from functional ones when they are scattered across the codebase. Second, we aim to untangle quality concerns from unrelated changes to gain a detailed knowledge about the history of specific quality changes. this knowledge is crucial to support consistency between the requirements-and-design and to verify architecture conformance. From the practical stance, developers could gain a breadth of understanding about quality concerns and their relations with other artifacts. thus, with more confidence, they could perform code modifications, improve module traceability, and provide a better holistic assessment of change impact analysis.

关键词： Quality Concerns Quality Bugs Tangled Quality Concerns Scattered Quality Concerns software Maintenance

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