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Study of a code comment decision method based on structural features

Study of a code comment decision method based on structural ...

引用

2019 International Conference on Intelligent computing, Automation and Systems, ICICAS 2019

作者： Wang, Renmin Wang, Tao Wang, Huaimin Key Lab. of Parallel and Distributed Computing National University of Defense Technology Changsha China

ISBN: (纸本)9781728161068

Code comment is one of the most effective ways to help programmers to understand the source code. High-quality comment decisions can not only cover the core code snippets in the software system but also avoid generating redundant code comments. However, in actual development, there is no uniform comment specification, and most of the comment decisions depend on personal experience and domain knowledge. This paper has learned a common comment decision specification from a large number of code comment examples to assist programmers in making appropriate comment decisions during code development. This paper proposes a method to extract the code structure from the context code of the current code line, and use the machine learning algorithm to determine the possibility that the current code needs to add comments. The proposed method was evaluated on 8 well-known open-source Python projects in GitHub and the experimental results show the feasibility and effectiveness of the method in some code types. © 2019 IEEE.

关键词： Machine learning

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A supervised approach for tag hierarchy construction in open source communities 15

A supervised approach for tag hierarchy construction in open...

引用

7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Gu, Chongming Yin, Gang Wang, Tao Yang, Cheng Wang, Huaimin Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China

ISBN: (纸本)9781450336413

The massive amounts of open source software provide sufficient reusable resources for software development. Most of the OSS communities adopt a kind of categorization or tagging mechanism to organize the software. However, the categorization often too coarse, while the tags are flat and fail to capture the inter-relation among them. In this paper, we propose a novel approach to reveal the latent relations between tags and build a tag hierarchy to help locate resources. We firstly build a co-occurrence network, based on which we compare the connotations of tags and construct a preliminary hierarchy. Then we leverage the domain knowledge of category in SourceForge to optimize and improve the relations between tags. At the end, we demonstrate the effectiveness of the constructed tag hierarchy with quantitative evaluation, which suggest the validation of our approach. © 2015 ACM.

关键词： Open source software

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Personalized mobile application discovery 1

Personalized mobile application discovery

引用

1st International Workshop on Crowd-Based Software Development Methods and Technologies, CrowdSoft 2014

作者： Yang, Cheng Wang, Tao Yin, Gang Wang, Huaimin Wu, Ming Xiao, Ming Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China

ISBN: (纸本)9781450332248

With the dramatic growing of mobile application markets, users can find apps with any function they desire in these markets. However, the huge amounts of apps make it quite a challenge for users to discover good applications efficiently. Previous studies recommend applications based on the download history, user ratings or app usage records. Most of these studies fail to capture users' personal interests in mobile applications precisely. In this paper, we leverage apps as features for describing user's personal interests and propose a novel approach to do personalized recommendation. We introduce a Small-Crowd model to distinguish apps at reflecting users' personal interests, and design a weighting method to rank the installed apps for users by combining the global download information with fine-grained app usage records. The extensive experiments validate the effectiveness of our approach which outperforms state-of-the-art method. Copyright 2014 ACM.

关键词： Mobile computing

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Exploring the use of @-mention to assist software development in GitHub 15

Exploring the use of @-mention to assist software developmen...

引用

7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Wang, Huaimin Yin, Gang Wang, Tao Yu, Yue Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

Recently, many researches propose that social media tools can promote the collab.ration among developers, which are beneficial to the software development. Nevertheless, there is little empirical evidence to confirm that using @-mention has indeed a beneficial impact on the issues in GitHub. In this paper, we analyze the data from GitHub and give some insights on how @-mention is used in the issues (general- issues and pull-requests). Our statistical results indicate that, @-mention attracts more participants and tends to be used in the difficult issues. @-mention favors the solving process of issues by enlarging the visibility of issues and facilitating the developers' collab.ration. In addition to this global study, our study also build a @-network based on the @-mention database we extract. Through the @-network, we can mine the relationships and characteristics of developers in GitHub's issues. © 2015 ACM.

关键词： Social networking (online)

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Evaluating bug severity using crowd-based knowledge: An exploratory study 15

Evaluating bug severity using crowd-based knowledge: An expl...

引用

7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Yin, Gang Wang, Tao Yu, Yue Wang, Huaimin Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

In bug tracking system, the high volume of incoming bug reports poses a serious challenge to project managers. Triaging these bug reports manually consumes time and resources which leads to delaying the resolution of important bugs. StackOverow is the most popular crowdsourcing Q&A community with plenty of bug-related posts. In this paper, we explore the correlation between bug severity and the crowd attributes of linked posts. Two typical types of projects' bug repositories are studied here, e.g. Mozilla (user-centric project) and Eclipse (developer-centric project). Our results show that the bug severity is consistent with the crowd- based knowledge both in Mozilla and Eclipse, i.e. the linked posts of severe bugs have higher score etc. in StackOverow than non-severe bugs. This interesting phenomenon inspires us that we can optimize the existing evaluation methods of bug severity by incorporating the crowd-based knowledge from a third-party in future. © 2015 ACM.

关键词： StackOverflow crowd-based knowledge Bugzilla Bug severity

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Linking stack overflow to issue tracker for issue resolution 2014

Linking stack overflow to issue tracker for issue resolution

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6th Asia-Pacific Symposium on Internetware, Internetware 2014

作者： Wang, Tao Yin, Gang Wang, Huaimin Yang, Cheng Zou, Peng Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China Academy of Equipment Command and Technology Beijing100000 China

ISBN: (纸本)9781450334013

Issue resolution is a central task for software development. The efficiency of issue fixing largely relies on the issue report quality. Stack Overflow, which hosts rich and real-Time posts about programming-specific problems, is a valuable external source of knowledge for issue resolution. In this paper, we present CrossLink, an analysis framework that automatically introduce related posts in Stack Overflow to issues in Android Issue Tracker. This helps developers to leverage the abundant and professional knowledge from massive programmers in Stack Overflow for issue resolution. CrossLink explores the semantic similarities as well as the temporal associations between the two types of repositories to recommend Stack Overflow posts to Android issues. The internal links in Stack Overflow are also employed to improve the linking accuracy. The experiments prove the effectiveness of CrossLink with precision of 62.51% for top-10 recommendations, which is significantly higher than the state-of-Art method. © 2014 ACM.

关键词： Android (operating system)

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A Multi-Dimensional Assessment Model and Its Application in E-learning Courses of Computer Science 20

A Multi-Dimensional Assessment Model and Its Application in ...

引用

21st Annual Conference of the Special Interest Group in Information Technology Education, SIGITE 2020

作者： Luo, Jiwen Lu, Feng Wang, Tao Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781450370455

Computer science is a practical discipline. It is always a great challenge to evaluate students' computer practice using computer-aided means for large scale students. We always need to address problems such as suspected plagiarism and deviation of the overall difficulty factor. In this paper, a multi-dimensional assessment model is designed for CS courses based on the detailed practice processing data in an E-learning system. The model comprehensively evaluates the students' learning process and results in three aspects of correctness, originality, and quality detection. Besides, the teacher can easily participate in the assessment according to their needs. The correctness is an essential requirement, and the originality is based on the clustering results of students' behaviors after clone detection to curb homework plagiarism. SonarQube is used to detect code quality and put forward higher requirements for codes. Manual participation intelligence has improved the flexibility and applicability of the model to a certain extent. We applied this model on the EduCoder online education platform and carried out a comprehensive analysis of 485 students in the parallel Programming Principles and Practice Class of Huazhong University of Science and Technology. Experiment results confirm the distinction, rationality, and fairness of the model in assessing student performance. It not only gives students a credible, comprehensive score in large-scale online practical programming courses but also gives teachers and students corresponding suggestions based on the evaluation results. Furthermore, the model can be extended to other online education platforms. © 2020 ACM.

关键词： Students

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Study of a Code Comment Decision Method Based on Structural Features

Study of a Code Comment Decision Method Based on Structural ...

引用

International Conference on Intelligent computing, Automation and Systems (ICICAS)

作者： Renmin Wang Tao Wang Huaimin Wang Key Lab. of Parallel and Distributed Computing National University of Defense Technology Changsha China

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161075

关键词： decision making feature extraction knowledge acquisition learning (artificial intelligence) public domain software software engineering system documentation program and system documentation open source software Information Extraction Comment Software engineering Codes Feature extraction Computer personnel Structural properties Software systems Machine learning algorithms decision making

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Predicting Programming Behavior in OSS Communities: A Case Study of NLP-based Approach

Predicting Programming Behavior in OSS Communities: A Case S...

引用

Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Manyan Huo Yue Yu Zhixing Li Junsheng Chang Key Lab. of Parallel and Distributed Computing Lab. College of Computer National University of Defence Technology ChangSha China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

Prediction of developers' programming behaviors is an effective way to improve their development efficiency and optimize the organization of project modules and files. However, little research exists investigating on this direction. In order to address this knowledge gap, we proposed a NLP-based approach to predict the programming behaviors in OSS (Open Source Software) communities. The proposed approach i) embeds the historical programming behavior data of a project into a multi-dimensional vector space to capture the potential laws in the data, ii) forms an eigenvector matrix reflecting the semantic relationship of the development behavior data, and iii) predicts the next programming behavior of a specific developer based on the eigenvector matrix. Our experiments on five OSS projects show that the prediction accuracy rate of the proposed prediction approach can reach up to about 50%, indicating that it can summarize the development behavior data law and effectively predict the programming behavior of developers. Our work can provide valuable assistance for developers' programming and projects' maintenance in practice.

关键词： Training Semantics Programming Predictive models Prediction algorithms Data models Context modeling

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Towards MLOps: A Case Study of ML Pipeline Platform

Towards MLOps: A Case Study of ML Pipeline Platform

引用

Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Yue Zhou Yue Yu Bo Ding Key Lab. of Parallel and Distributed Computing Lab. College of Computer National University of Defence Technology ChangSha China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

The development and deployment of machine learning (ML) applications differ significantly from traditional applications in many ways, which have led to an increasing need for efficient and reliable production of ML applications and supported infrastructures. Though platforms such as TensorFlow Extended (TFX), ModelOps, and Kubeflow have provided end-to-end lifecycle management for ML applications by orchestrating its phases into multistep ML pipelines, their performance is still uncertain. To address this, we built a functional ML platform with DevOps capability from existing continuous integration (CI) or continuous delivery (CD) tools and Kubeflow, constructed and ran ML pipelines to train models with different layers and hyperparameters while time and computing resources consumed were recorded. On this basis, we analyzed the time and resource consumption of each step in the ML pipeline, explored the consumption concerning the ML platform and computational models, and proposed potential performance bottlenecks such as GPU utilization. Our work provides a valuable reference for ML pipeline platform construction in practice.

关键词： Training Computational modeling Pipelines Graphics processing units Tools Data models Task analysis

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