Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops最新文献_第10页

More than Code: Contributions in Scrum Software Engineering Teams 不仅仅是代码:Scrum软件工程团队中的贡献

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392241

Frederike Ramin, Christoph Matthies, Ralf Teusner

引用次数: 12

Mining Hypernyms Semantic Relations from Stack Overflow 从堆栈溢出挖掘中词语义关系

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392160

L. Tóth, Balázs Nagy, T. Gyimóthy, László Vidács

{"title":"Mining Hypernyms Semantic Relations from Stack Overflow","authors":"L. Tóth, Balázs Nagy, T. Gyimóthy, László Vidács","doi":"10.1145/3387940.3392160","DOIUrl":"https://doi.org/10.1145/3387940.3392160","url":null,"abstract":"Communication between a software development team and business partners is often a challenging task due to the different context of terms used in the information exchange. The various contexts in which the concepts are defined or used create slightly different semantic fields that can evolve into information and communication silos. Due to the silo effect, the necessary information is often inadequately forwarded to developers resulting in poorly specified software requirements or misinterpreted user feedback. Communication difficulties can be reduced by introducing a mapping between the semantic fields of the parties involved in the communication based on the commonly used terminologies. Our research aims to obtain a suitable semantic database in the form of a semantic network built from the Stack Overflow corpus, which can be considered to encompass the common tacit knowledge of the software development community. Terminologies used in the business world can be assigned to our semantic network, so software developers do not miss features that are not specific to their world but relevant to their clients. We present an initial experiment of mining semantic network from Stack Overflow and provide insights of the newly captured relations compared to WordNet.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122521792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DockerKG

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392161

Jiahong Zhou, Wei Chen, Chang Liu, Jiaxin Zhu, Guoquan Wu, Jun Wei

引用次数: 0

Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging 软件工程师调试过程中的虚拟代理对话行为分类

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3391487

Andrew Wood, Zachary Eberhart, Collin McMillan

{"title":"Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging","authors":"Andrew Wood, Zachary Eberhart, Collin McMillan","doi":"10.1145/3387940.3391487","DOIUrl":"https://doi.org/10.1145/3387940.3391487","url":null,"abstract":"A \"dialogue act\" is a written or spoken action during a conversation. Dialogue acts are usually only a few words long, and are often categorized by researchers into a relatively small set of dialogue act types, such as eliciting information, expressing an opinion, or making a greeting. Research interest into automatic classification of dialogue acts has grown recently due to the proliferation of Virtual Agents (VA) e.g. Siri, Cortana, Alexa. But unfortunately, the gains made into VA development in one domain are generally not applicable to other domains, since the composition of dialogue acts differs in different conversations. In this paper, we target the problem of dialogue act classification for a VA for software engineers repairing bugs. A problem in the SE domain is that very little sample data exists - the only public dataset is a recently-released Wizard of Oz study with 30 conversations. Therefore, we present a transfer-learning technique to learn on a much larger dataset for general business conversations, and apply the knowledge to the SE dataset. In an experiment, we observe between 8% and 20% improvement over two key baselines.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117080965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Do You Just Discuss or Do You Solve?: Meeting Analysis in a Software Project at Early Stages 你只是讨论还是解决?:软件项目早期阶段的会议分析

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3391468

J. Klünder, Nils Prenner, Ann-Kathrin Windmann, Marek Stess, Michael Nolting, Fabian Kortum, Lisa Handke, K. Schneider, S. Kauffeld

{"title":"Do You Just Discuss or Do You Solve?: Meeting Analysis in a Software Project at Early Stages","authors":"J. Klünder, Nils Prenner, Ann-Kathrin Windmann, Marek Stess, Michael Nolting, Fabian Kortum, Lisa Handke, K. Schneider, S. Kauffeld","doi":"10.1145/3387940.3391468","DOIUrl":"https://doi.org/10.1145/3387940.3391468","url":null,"abstract":"Software development is a very cooperative and communicative task. In most software projects, meetings are a very important medium to share information. However, these meetings are often not as effective as expected. One big issue hindering productive and satisfying meetings is inappropriate behavior such as complaining. In particular, talking about problems without at least trying to solve them decreases motivation and mood of the team. Interaction analyses in meetings allow the assessment of appropriate and inappropriate behavior influencing the quality of a meeting. Derived from an established interaction analysis coding scheme in psychology, we present act4teams-short which allows real-time coding of meetings in software projects. We apply act4teams-short in an industrial case study at Volkswagen Commercial Vehicles, a large German company in the automotive domain. We analyze ten team-internal meetings at early project stages. Our results reveal difficulties due to missing project structure and the overall project goal. Furthermore, the team has an intrinsic interest in identifying problems and solving them, without any extrinsic input being required.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124602116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

OffSide 越位

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.5040/9781350040809.00000002

Jón Arnar Briem, Jordi Smit, Hendrig Sellik, Pavel Rapoport, Georgios Gousios, M. Aniche

引用次数: 16

Improving Code Recommendations by Combining Neural and Classical Machine Learning Approaches 结合神经和经典机器学习方法改进代码推荐

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3391489

M. Schumacher, K. T. Le, A. Andrzejak

{"title":"Improving Code Recommendations by Combining Neural and Classical Machine Learning Approaches","authors":"M. Schumacher, K. T. Le, A. Andrzejak","doi":"10.1145/3387940.3391489","DOIUrl":"https://doi.org/10.1145/3387940.3391489","url":null,"abstract":"Code recommendation systems for software engineering are designed to accelerate the development of large software projects. A classical example is code completion or next token prediction offered by modern integrated development environments. A particular challenging case for such systems are dynamic languages like Python due to limited type information at editing time. Recently, researchers proposed machine learning approaches to address this challenge. In particular, the Probabilistic Higher Order Grammar technique (Bielik et al., ICML 2016) uses a grammar-based approach with a classical machine learning schema to exploit local context. A method by Li et al., (IJCAI 2018) uses deep learning methods, in detail a Recurrent Neural Network coupled with a Pointer Network. We compare these two approaches quantitatively on a large corpus of Python files from GitHub. We also propose a combination of both approaches, where a neural network decides which schema to use for each prediction. The proposed method achieves a slightly better accuracy than either of the systems alone. This demonstrates the potential of ensemble-like methods for code completion and recommendation tasks in dynamically typed languages.","PeriodicalId":309659,"journal":{"name":"Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131324260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Digital Twin for Cybersecurity Incident Prediction: A Multivocal Literature Review 网络安全事件预测的数字孪生:多声音文献综述

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392199

Abhishek Pokhrel, Vikash Katta, Ricardo Colomo Palacios

引用次数: 16

Human Factors in the Study of Automatic Software Repair: Future Directions for Research with Industry 软件自动修复研究中的人为因素:工业研究的未来方向

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392176

E. Winter, David Bowes, S. Counsell, T. Hall, Saemundur O. Haraldsson, Vesna Nowack, J. Woodward

引用次数: 1

Increasing the Trust In Refactoring Through Visualization 通过可视化提高重构的信任度

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Pub Date : 2020-06-27 DOI: 10.1145/3387940.3392190

Alex Bogart, E. Alomar, Mohamed Wiem Mkaouer, Ali Ouni

引用次数: 7