2016 Third International Conference on Trustworthy Systems and their Applications (TSA)最新文献_第3页

A Copy-Move Forgery Detection Scheme with Improved Clone Region Estimation 一种改进克隆区域估计的复制-移动伪造检测方案

2016 Third International Conference on Trustworthy Systems and their Applications (TSA) Pub Date : 2016-09-01 DOI: 10.1109/TSA.2016.12

Fei Zhao, Wenchang Shi, Bo Qin, Bin Liang

引用次数: 5

A Search Based Context-Aware Approach for Understanding and Localizing the Fault via Weighted Call Graph 基于加权呼叫图的搜索上下文感知故障理解与定位方法

2016 Third International Conference on Trustworthy Systems and their Applications (TSA) Pub Date : 2016-09-01 DOI: 10.1109/TSA.2016.20

Jingxuan Tu, Xiaoyuan Xie, Yuming Zhou, Baowen Xu, Lin Chen

{"title":"A Search Based Context-Aware Approach for Understanding and Localizing the Fault via Weighted Call Graph","authors":"Jingxuan Tu, Xiaoyuan Xie, Yuming Zhou, Baowen Xu, Lin Chen","doi":"10.1109/TSA.2016.20","DOIUrl":"https://doi.org/10.1109/TSA.2016.20","url":null,"abstract":"Strictly speaking, fault localization includes assessing the code risk of being faulty and identifying the real fault. In practice, only highlighting some possible faulty statements is not helpful enough to reason the roots of the observed failures in a system. Programmers need to manually inspect the highlighted risky statements one by one, reading and understanding their contexts, in order to identify the real faulty ones. However, most related works have been focusing on risk assessment by simply ignoring the fault identification, which makes such techniques much less practical in real world. Therefore, in this paper, we propose a context-aware approach to assist fault comprehension and identification. Built on risk assessment results, our approach searches for the faults on Weighted Call Graph. In our approach the risky statements are re-ordered by function call chains, which can provide much richer information to understand the context and hence reduce the efforts in manual code inspection. Case studies with three open-source systems show that the proposed approach could help to improve the effectiveness of the whole fault localization process.","PeriodicalId":114541,"journal":{"name":"2016 Third International Conference on Trustworthy Systems and their Applications (TSA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116318493","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: 2

X-Prcaf : Xposed Based Protecting Cache File from Leaks in Android Social Applications X-Prcaf:基于暴露保护缓存文件从泄漏在Android社交应用程序

2016 Third International Conference on Trustworthy Systems and their Applications (TSA) Pub Date : 2016-09-01 DOI: 10.1109/TSA.2016.13

Qi Tang, Wen Zhang, Xiaoyong Li, Bin Wang

引用次数: 2

What Are the Dominant Projects in the GitHub Python Ecosystem? 什么是GitHub Python生态系统中的主导项目?

2016 Third International Conference on Trustworthy Systems and their Applications (TSA) Pub Date : 2016-09-01 DOI: 10.1109/TSA.2016.23

Wanwangying Ma, Lin Chen, Yuming Zhou, Baowen Xu

{"title":"What Are the Dominant Projects in the GitHub Python Ecosystem?","authors":"Wanwangying Ma, Lin Chen, Yuming Zhou, Baowen Xu","doi":"10.1109/TSA.2016.23","DOIUrl":"https://doi.org/10.1109/TSA.2016.23","url":null,"abstract":"GitHub, a popular social-software-development platform, has fostered a variety of software ecosystems where projects depend on one another and co-evolve together. The projects located in the central hub of the ecosystem are supposed to be important and could affect a number of other projects. However, few researches have investigated the dominant projects in a software ecosystem. In this study, we aim to identify the most influential projects in the GitHub Python ecosystem. We first construct the GitHub Python ecosystem with 19797 projects by identifying their inter-dependencies. Then, we calculate the four kinds of centrality metrics to measure the centrality and influence of each project in the ecosystem. Finally, we evaluate the project's popularity using GitHub social methods and compare the consistency of the two measurements. Our results indicate that 1) the most influential projects are mostly custom libraries; 2) only a small number of projects have large values of the centrality metrics; 3) the dominant projects are not always popular among the GitHub users. Our results help the researchers and practitioners gain a better understanding of the GitHub Python ecosystem.","PeriodicalId":114541,"journal":{"name":"2016 Third International Conference on Trustworthy Systems and their Applications (TSA)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122877398","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: 11