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Real-time Estimation Approach to Scrum Projects Effort: Task Point and Individual Reliability 35

Real-time Estimation Approach to Scrum Projects Effort: Task...

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35th international conference on software engineering and knowledge engineering, SEKE 2023

作者： Guo, Yu Guo, Jun Shi, Mohan Dong, Aixuan School of Software College Northeastern University Shenyang China

In software project management, it is a useful method to control the progress of the project through effort estimation. How to estimate the effort in real time in the Agile software development has always been a difficulty faced by Agile teams. Aiming at the current mainstream Agile software Development techniques, Scrum framework, this paper puts forward the calculation approach for reliability of Scrum team members and the Sprint development time estimation approach based on individual reliability, i.e., the total working time estimation of the next Sprint is realized by estimating and adjusting the working time of the team individuals. 51 development teams with 5-9 people have put this method into practice for experimental verification, and the results show that the highest estimation accuracy of this approach can reach 84.1%. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： software design

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Can ChatGPT emulate humans in software engineering surveys? 24

Can ChatGPT emulate humans in software engineering surveys?

引用

18th ACM/IEEE international Symposium on Empirical software engineering and Measurement, ESEM 2024

作者： Steinmacher, Igor Penney, Jacob McAuley Felizardo, Katia Romero Garcia, Alessandro F. Gerosa, Marco A. Northern Arizona University United States UTFPR-CP Brazil PUC-Rio Brazil Northern Arizona University FlagstaffAZ United States

ISBN: (纸本)9798400710476

Context: there is a growing belief in the literature that large language models (LLMs), such as ChatGPT, can mimic human behavior in surveys. Gap: While the literature has shown promising results in social sciences and market research, there is scant evidence of its effectiveness in technical fields like software engineering. Objective: Inspired by previous work, this paper explores ChatGPT's ability to replicate findings from prior software engineering research. Given the frequent use of surveys in this field, if LLMs can accurately emulate human responses, this technique could address common methodological challenges like recruitment difficulties, representational shortcomings, and respondent fatigue. Method: We prompted ChatGPT to reflect the behavior of a 'mega-persona' representing the demographic distribution of interest. We replicated surveys from 2019 to 2023 from leading SE conferences, examining ChatGPT's proficiency in mimicking responses from diverse demographics. Results: Our findings reveal that ChatGPT can successfully replicate the outcomes of some studies, but in others, the results were not significantly better than a random baseline. Conclusions: this paper reports our results so far and discusses the challenges and potential research opportunities in leveraging LLMs for representing humans in software engineering surveys. © 2024 Owner/Author.

关键词： Market Research

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Detecting Code Smells using ChatGPT: Initial Insights 24

Detecting Code Smells using ChatGPT: Initial Insights

引用

18th ACM/IEEE international Symposium on Empirical software engineering and Measurement, ESEM 2024

作者： Silva, Luciana Lourdes Silva, Janio Rosa Da Montandon, Joao Eduardo Andrade, Marcus Valente, Marco Tulio Computer Science Federal University of Minas Gerais Brazil

ISBN: (纸本)9798400710476

this paper presents initial insights into the effectiveness of ChatGPT in detecting code smells in Java projects. We utilize a large dataset comprising four code smells - Blob, Data Class, Feature Envy, and Long Method - classified into three severity levels. To assess ChatGPT's proficiency, we employ two different prompts: (i) a generic prompt and (ii) a prompt specifying the smells selected for our research. We evaluate ChatGPT's abilities using metrics such as precision, recall, and F-measure. Our results reveal that the odds of ChatGPT providing a correct outcome with a specific prompt are 2.54 times higher compared to a generic one. Furthermore, ChatGPT is more effective at detecting smells with critical severity (F-measure = 0.52) than those with minor severity (F-measure = 0.43). Finally, we discuss the implications of our findings and suggest future research directions for leveraging large language models to detect code smells. © 2024 ACM.

关键词： Computer software selection and evaluation

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MODELING OF EXPERIMENTAL SHEAR STRENGth OF GYPSIFEROUS CLAY SOIL 18th

MODELING OF EXPERIMENTAL SHEAR STRENGTH OF GYPSIFEROUS CLAY ...

引用

18th international Middle Eastern Simulation and Modelling conference, MESM 2023

作者： Al-Taie, Abbas J. Albusoda, Bushra S. Department of Civil Engineering l-Nahrain University Baghdad10070 Iraq Department of Civil Engineering University of Baghdad Baghdad10070 Iraq

ISBN: (纸本)9789492859310

the maximum internal shear resistance of engineering geomaterials is defined as shear strength. the numerical modeling of numerous engineering problems (e.g. bearing capacity, slope stability, and lateral pressure) is mainly depending on the obtained value of soil shear strength. In geotechnical engineering, the internal friction angle and cohesion are termed the strength parameters of the geomaterials. Different laboratory tests like unconfined, direct shear, and triaxial tests are used to obtain these parameters. Among these tests, the triaxial test is the more precise but, at the same time, it is more costly and timeconsuming. the development in the software technology may assist in the easy defining of strength parameters. In this paper, the laboratory-prepared gypsiferous clay soil samples were tested in triaxial compression (unconsolidated undrained) test under different confining pressure (100, 200, and 400) kPa. then, the obtained experimental results were numerically modeled using a specialized finite element geotechnical program. Finally, the comparison between the experimental and numerical modeling results revealed very good agreement. the deviatoric stresses at failure determined from numerical analysis are compared to values of experimental tests with a 90% to 91% agreement. Also, the mode of failure obtained, based on the modeling of gypsiferous clay sample, using Mohr-Coulomb model is in comparison to the actual experimental mode. this behavior, however, is directly affected by the boundary conditions for the numerical model. © 2024, EUROSIS-ETI. All rights reserved.

关键词： Shear strength

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Towards generating contextualised fault scenarios for reliability risk analysis of cyber-physical systems 35

Towards generating contextualised fault scenarios for reliab...

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35th international conference on software engineering and knowledge engineering, SEKE 2023

作者： Wei, Lufeng Li, Zhi Qin, Yuansong School of Computer Science and Engineering Guangxi Normal University Guilin China

this paper proposes an approach that combines Fault Tree Analysis with Problem Frames to present the latent reliability risks of Cyber-Physical Systems. By extracting causality within each, this approach associates the atomic events of the Fault Tree with the shared phenomena of the Problem Diagram, in order to generate scenarios with contexts that may lead to the occurrence of faults. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Fault tree analysis

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Deep Direct Visual Servoing of Tendon-Driven Continuum Robots 18

Deep Direct Visual Servoing of Tendon-Driven Continuum Robot...

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IEEE 18th international conference on Automation Science and engineering (IEEE CASE)

作者： Abdulhafiz, Ibrahim Nazari, Ali A. Abbasi-Hashemi, Taha Jalali, Amir Zareinia, Kourosh Saeedi, Sajad Janabi-Sharifi, Farrokh Toronto Metropolitan Univ Dept Elect Comp & Biomed Engn Toronto ON M5B 2K3 Canada Toronto Metropolitan Univ Dept Mech & Ind Engn Toronto ON M5B 2K3 Canada

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Vision-based control provides a significant potential for the end-point positioning of continuum robots under physical sensing limitations. Traditional visual servoing requires feature extraction and tracking followed by full or partial pose estimation, limiting the controller's efficiency. We hypothesize that employing deep learning models and implementing direct visual servoing can effectively resolve the issue by eliminating such intermediate steps, enabling control of a continuum robot without requiring an exact system model. this paper presents the control of a single-section tendon-driven continuum robot using a modified VGG-16 deep learning network and an eye-in-hand direct visual servoing approach. the proposed algorithm is first developed in Blender software using only one input image of the target and then implemented on a real robot. the convergence and accuracy of the results in normal, shadowed, and occluded scenes demonstrate the effectiveness and robustness of the proposed controller.

关键词： Deep learning Limiting software algorithms Pose estimation Robot sensing systems Feature extraction Visual servoing

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Artificial Intelligence Based SysML Block Diagram Extension and Evolution for Product Lines 20

Artificial Intelligence Based SysML Block Diagram Extension ...

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20th ACS/IEEE international conference on Computer Systems and Applications (AICCSA)

作者： Ferchichi, Olfa Beltaifa, Ndraoudha Labed Jilani, Lamia Univ Manouba Natl Sch Comp Sci RIADI Lab Campus Manouba Manouba Tunisia Univ Sesame Ghazela Tunisia Univ Carthage Carthage Tunisia Univ Tunis Tunis Tunisia

ISBN: (纸本)9798350319439

SysML is a standard language that permits to model systems of any type such as plane, ships and software intensive systems. software Product Line large scale reuse approach has demonstrated its success. the industry provides benefits in term of cost savings and acceleration of time to maket. the available literature indicates that there have been efforts to enhance the capability of SysML in handling product families. However, these attempts are not yet fully systematic, and there remains a significant amount of work to be undertaken in this area. In this present paper, we deal with the SysML Block Diagram in order to investigate to what extent it permits variability representation and how it can evolve during the system evolution or when agility is needed. We want to capitalize on the knowledge necessary for block diagram extention and evolution and take advantage of knowledge from Product Line domain engineering and application engineering. So, we decide to use an ontology which is an articifial intelligence artifact. An ontology is a powerful mean to represent knowledge and reason about it. Here, we use the ontology to help decision making for Block diagram evolution as well.

关键词： SysML block diagram Product Line engineering Variability Evolution Artificial Intelligence Artifact Ontology

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MLOps-Enabled Security Strategies for Next-Generation Operational Technologies 24

MLOps-Enabled Security Strategies for Next-Generation Operat...

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28th international conference on Evaluation and Assessment in software engineering (EASE)

作者： Ahmad, Tazeem Adnan, Mohd Rafi, Saima Akbar, Muhammad Azeem Anwar, Ayesha Univ Southern Queensland Darling Hts Qld Australia Inha Univ Incheon South Korea Edinburgh Napier Univ Edinburgh Midlothian Scotland LUT Univ Dept Software Engn Lappeenranta Finland Univ Faisalabad Dept Comp Sci Faisalabad Pakistan

ISBN: (纸本)9798400717017

In recent years, the significant increase in enterprise data availability and the progress in Artificial Intelligence (AI) have enabled organizations to address real-world issues through Machine Learning (ML). In this regard, machine learning operations (MLOps) have been proven to be a beneficial strategy for evolving ML models from theoretical ideas to practical solutions of business sector issues. With the knowledge of MLOps being vast and scattered, this research work focuses on the application of MLOps methodologies in sophisticated operational technologies, prioritizing the enhancement of security measures. this research work also discusses the specific challenges in securing ML implementations in such settings and underscores the importance of robust MLOps strategies in ensuring effective security protocols. Moreover, it explains current practices and identified improvement areas, highlighting the importance of MLOps in overcoming obstacles and maximizing the value of ML in operational technology contexts.

关键词： Machine Learning DevOps Security Operational Technology MLOps Best Practices Continuous Deployment

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WADEC: Decompiling WebAssembly Using Large Language Model 24

WADEC: Decompiling WebAssembly Using Large Language Model

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

作者： She, Xinyu Zhao, Yanjie Wang, Haoyu Huazhong Univ Sci & Technol Hubei Engn Res Ctr Big Data Secur Sch Cyber Sci & Engn Hubei Key Lab Distributed Syst Secur Wuhan Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

WebAssembly (abbreviated Wasm) has emerged as a cornerstone of web development, offering a compact binary format that allows high-performance applications to run at near-native speeds in web browsers. Despite its advantages, Wasm's binary nature presents significant challenges for developers and researchers, particularly regarding readability when debugging or analyzing web applications. therefore, effective decompilation becomes crucial. Unfortunately, traditional decompilers often struggle with producing readable outputs. While some large language model (LLM)-based decompilers have shown good compatibility with general binary files, they still face specific challenges when dealing with Wasm. In this paper, we introduce a novel approach, WADEC, which is the first use of a fine-tuned LLM to interpret and decompile Wasm binary code into a higher-level, more comprehensible source code representation. the LLM was meticulously fine-tuned using a specialized dataset of wat-c code snippets, employing self-supervised learning techniques. this enables WADEC to effectively decompile not only complete wat functions but also finer-grained wat code snippets. Our experiments demonstrate that WADEC markedly outperforms current state-of-the-art tools, offering substantial improvements across several metrics. It achieves a code inflation rate of only 3.34%, a dramatic 97% reduction compared to the state-of-the-art's 116.94%. Unlike the output of baselines that cannot be directly compiled or executed, WADEC maintains a recompilability rate of 52.11%, a re-execution rate of 43.55%, and an output consistency of 27.15%. Additionally, it significantly exceeds state-of-the-art performance in AST edit distance similarity by 185%, cyclomatic complexity by 8%, and cosine similarity by 41%, achieving an average code similarity above 50%. In summary, WADEC enhances understanding of the code's structure and execution flow, facilitating automated code analysis, optimization, and security auditi

关键词： Training Measurement Codes Large language models Source coding Self-supervised learning Security Optimization Faces software engineering

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the Impact Of Bug Localization Based on Crash Report Mining: A Developers' Perspective 44

The Impact Of Bug Localization Based on Crash Report Mining:...

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

作者： Medeiros, Marcos Kulesza, Uira Coelho, Roberta Bonifacio, Rodrigo Treude, Christoph Adachi, Eiji Univ Fed Rio Grande do Norte Natal Brazil Univ Brasilia Brasilia Brazil Univ Melbourne Melbourne Australia

ISBN: (纸本)9798400702174

Developers often use crash reports to understand the root cause of bugs. However, locating the buggy source code snippet from such information is a challenging task, mainly when the log database contains many crash reports. To mitigate this issue, recent research has proposed and evaluated approaches for grouping crash report data and using stack trace information to locate bugs. the effectiveness of such approaches has been evaluated by mainly comparing the candidate buggy code snippets with the actual changed code in bug-fix commits-which happens in the context of retrospective repository mining studies. therefore, the existing literature still lacks discussing the use of such approaches in the daily life of a software company, which could explain the developers' perceptions on the use of these approaches. In this paper, we report our experience of using an approach for grouping crash reports and finding buggy code on a weekly basis for 18 months, within three development teams in a software company. We grouped over 750,000 crash reports, opened over 130 issues, and collected feedback from 18 developers and team leaders. Among other results, we observe that the amount of system logs related to a crash report group is not the only criteria developers use to choose a candidate bug to be analyzed. Instead, other factors were considered, such as the need to deliver customer-prioritized features and the difficulty of solving complex crash reports (e.g., architectural debts), to cite some. the approach investigated in this study correctly suggested the buggy file most of the time-the approach's precision was around 80%. In this study, the developers also shared their perspectives on the usefulness of the suspicious files and methods extracted from crash reports to fix related bugs.

关键词： software crash Bug correlation Bug localization Crash reports Stack traces Bug prioritization

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