Proceedings of the 9th Asia-Pacific Symposium on Internetware最新文献

CRSearcher: Searching Code Database for Repairing Bugs CRSearcher:搜索代码数据库修复bug

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131720

Yingyi Wang, Yuting Chen, Beijun Shen, Hao Zhong

{"title":"CRSearcher: Searching Code Database for Repairing Bugs","authors":"Yingyi Wang, Yuting Chen, Beijun Shen, Hao Zhong","doi":"10.1145/3131704.3131720","DOIUrl":"https://doi.org/10.1145/3131704.3131720","url":null,"abstract":"With the exponentially rising of software development in the past decades, millions of software products have been created. Existing empirical studies show that many code snippets are similar. Although there exist many difficulties in maintaining these similar code snippets, we believe that it is feasible to leverage the similarity to enhance program repairs, as bugs may have already been repaired in many other similar code snippets. In this paper, we propose CRSearcher, an approach, that searches open-sourced codebases and uses similar code to repair bugs. It is designed with insights from three observations: small patch, code redundancy, and the availability of open-sourced software repositories. With these insights, CRSearcher provides the engineers with an interactive strategy for program repair which automatically locates bug location, searches for similar code, and recommends code snippets as an aid, but allows developers to make a final decision. We have implemented CRSearcher on the basis of the state-of-the-art techniques such as Findbugs and a token-based similar code snippets search engine. In our evaluation, we have built a code database that consists of several open-source projects. Our evaluation results show that CRSearcher does help generating high quality program patches, and reduce more than 50% time on repairing six buggy programs.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122266163","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: 5

Combining Collaborative Filtering and Topic Modeling for More Accurate Android Mobile App Library Recommendation 结合协同过滤和主题建模的Android移动应用库推荐

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131721

Huan Yu, Xin Xia, Xiaoqiong Zhao, Weiwei Qiu

{"title":"Combining Collaborative Filtering and Topic Modeling for More Accurate Android Mobile App Library Recommendation","authors":"Huan Yu, Xin Xia, Xiaoqiong Zhao, Weiwei Qiu","doi":"10.1145/3131704.3131721","DOIUrl":"https://doi.org/10.1145/3131704.3131721","url":null,"abstract":"The applying of third party libraries is an integral part of many mobile applications. With the rapid development of mobile technologies, there are many free third party libraries for developers to download and use. However, there are a large number of third party libraries which always iterate rapidly, it is hard for developers to find available libraries within them. Several previous studies have proposed approaches to recommend third party libraries, which works in the scenario where a developer knows some required libraries, and needs to find other relevant libraries with limited knowledge. In the paper, to further improve the performance of app library recommendation, we propose an approach which combines collaborative filtering and topic modeling techniques. In the collaborative filtering component, given a new app, our approach recommends libraries by using its similar apps. In the topic modelling component, our approach first extracts the topics from the textual description of mobile apps, and given a new app, our approach recommends libraries based on the libraries used by the apps which has similar topic distributions. We perform experiments on a set of 1,013 apps, and the results show that our approach improves the state-of-the-art by a substantial margin.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114347247","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: 15

AgileRabbit: A Feedback-Driven Offloading Middleware for Smartwatch Apps agilerrabbit:一个反馈驱动的智能手表应用卸载中间件

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131709

Meihua Yu, Yun Ma, Xuanzhe Liu, Gang Huang, Xiangqun Chen

{"title":"AgileRabbit: A Feedback-Driven Offloading Middleware for Smartwatch Apps","authors":"Meihua Yu, Yun Ma, Xuanzhe Liu, Gang Huang, Xiangqun Chen","doi":"10.1145/3131704.3131709","DOIUrl":"https://doi.org/10.1145/3131704.3131709","url":null,"abstract":"With the rapid development of wearable devices such as smartwatches, we are brought to a new era of wearable computing. Due to limited computational capability, storage, and battery capacity, wearable devices can hardly execute computation-intensive tasks. The mainstream approach to overcoming these limitations is computation offloading, i.e., offloading the tasks to mobile devices or the remote cloud servers. However, computation offloading cannot improve performance or save power consumption under all conditions. For example, offloading may not be worth in the case of very poor network conditions. To address the issue, in this paper, we propose AgileRabbit, a feedback-driven middleware of computation offloading for smartwatch apps. We design an offloading decision algorithm using the feedback data with a given objective i.e., minimizing the task completion time, or minimizing the total power consumption of smartwatches and mobile devices. With the assistance of AgileRabbit, computation-intensive tasks in smartwatch apps can be well scheduled and assigned to the proper computation node. We implement a speech recognition application on Android Wear platform and deploy it on AgileRabbit to validate the effectiveness of our approach. Evaluation results show that AgileRabbit can significantly improve the performance and save power consumption while incurring small overheads.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122124159","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: 4

Automatically Generating Task-Oriented API Learning Guide 自动生成面向任务的API学习指南

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131714

Zixiao Zhu, Chenyan Hua, Yanzhen Zou, Bing Xie, Junfeng Zhao

引用次数: 3

Scalable Relevant Project Recommendation on GitHub GitHub上可扩展的相关项目建议

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131706

Wenyuan Xu, Xiaobing Sun, Xin Xia, Xiang Chen

{"title":"Scalable Relevant Project Recommendation on GitHub","authors":"Wenyuan Xu, Xiaobing Sun, Xin Xia, Xiang Chen","doi":"10.1145/3131704.3131706","DOIUrl":"https://doi.org/10.1145/3131704.3131706","url":null,"abstract":"GitHub, one of the largest social coding platforms, fosters a flexible and collaborative development process. In practice, developers in the open source software platform need to find projects relevant to their development work to reuse their function, explore ideas of possible features, or analyze the requirements for their projects. Recommending relevant projects to a developer is a difficult problem considering that there are millions of projects hosted on GitHub, and different developers may have different requirements on relevant projects. In this paper, we propose a scalable and personalized approach to recommend projects by leveraging both developers' behaviors and project features. Based on the features of projects created by developers and their behaviors to other projects, our approach automatically recommends top N most relevant software projects to developers. Moreover, to improve the scalability of our approach, we implement our approach in a parallel processing frame (i.e., Apache Spark) to analyze large-scale data on GitHub for efficient recommendation. We perform an empirical study on the data crawled from GitHub, and the results show that our approach can efficiently recommend relevant software projects with a relatively high precision fit for developers' interests.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125415348","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: 10

Learning from Internet: Handling Uncertainty in Robotic Environment Modeling 从互联网学习:处理机器人环境建模中的不确定性

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131712

Yiying Li, Huaimin Wang, Bo Ding, Huimin Che

{"title":"Learning from Internet: Handling Uncertainty in Robotic Environment Modeling","authors":"Yiying Li, Huaimin Wang, Bo Ding, Huimin Che","doi":"10.1145/3131704.3131712","DOIUrl":"https://doi.org/10.1145/3131704.3131712","url":null,"abstract":"Uncertainty is a great challenge for environment perception of autonomous robots. For instance, while building semantic maps (i.e., maps with semantic labels such as object names), the robot may encounter unexpected objects of which it has no knowledge. It will lead to inevitable failures in traditional environment modeling software. The abundant knowledge being accumulated on the Internet has the potential to assist robots to handle such kind of uncertainly. However, existing researches have not touched this issue yet. This paper proposes a cloud-based semantic mapping engine named SemaCloud, which can not only augment robot's environment modeling capability by the rich cloud resources but also cope with uncertainty by utilizing the Internet knowledge on necessary. It adopts a state-of-art Deep Neural Network (DNN) for real-time and accurate recognition of pre-trained objects. If an object is beyond the knowledge of this DNN, a special mechanism named QoS-aware cloud phase transition is triggered to seek help from existing recognition services on the Internet. By a set of carefully-designed algorithms, it can maximize benefits and minimize the negative impacts on the Quality of Service (QoS) properties of robotic applications, which is essential to many robot scenarios. The experiments on both open datasets and real robots show that our work can handle uncertainly successfully in robotic semantic mapping without sacrificing critical real-time constraints.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121807535","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: 3

Evaluating Software Evolution Based on Pattern Mining 基于模式挖掘的软件演化评价

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131723

Xiaohui Zhou, Xinyue Zhang, Wenpin Jiao

{"title":"Evaluating Software Evolution Based on Pattern Mining","authors":"Xiaohui Zhou, Xinyue Zhang, Wenpin Jiao","doi":"10.1145/3131704.3131723","DOIUrl":"https://doi.org/10.1145/3131704.3131723","url":null,"abstract":"Software systems need constantly maintaining or adapting to continuously meet the changing business requirements. The process of maintenance or adaptation is software evolution. In general, people hope to evaluate software evolution for guiding software maintenances. By evaluating how well software maintenances follow the positive evolutionary trends, developers can assert whether it is necessary to redevelop or even refactor newly released or maintained versions of software to enforce the software evolution back on track. In this paper, we propose an approach to evaluating software evolution based on API usage patterns, which are the accumulations and summarizations of people's software design and development experience. In the approach, better software evolution is considered as the process of reusing more usage patterns, and software evolution is evaluated based on how well software reuses usage patterns in the process of evolution. Our work consists of three parts. First, we use a graph-based algorithm to mine usage patterns from different open-source software. Second, we use the patterns to evaluate the evolutions of software systems and accordingly analyze the important changes during software evolution. Third, we compare different approaches and analyze which approach can reflect the process of software evolution accurately. Our experiments on several open source programs show that our approach is more effective than other approaches on identifying the great change events during software evolution.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127115403","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

Fast and Precise recovery in Stream processing based on Distributed Cache 基于分布式缓存的流处理快速精确恢复

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131724

Yingying Zheng, Wei Wang, Lijie Xu, Zhen Tang, Zhongshan Ren, Jun Wei, Dan Ye

{"title":"Fast and Precise recovery in Stream processing based on Distributed Cache","authors":"Yingying Zheng, Wei Wang, Lijie Xu, Zhen Tang, Zhongshan Ren, Jun Wei, Dan Ye","doi":"10.1145/3131704.3131724","DOIUrl":"https://doi.org/10.1145/3131704.3131724","url":null,"abstract":"Stream processing system (SPS) faces the problem of node failure when running over a long period of time. In addition, \"exactly once\" precise semantic guarantee is more and more important for SPS in some scenarios. In general, the approaches to achieve precise semantic is by using global snapshot, which should store state and records to external reliable storage or rely on transactions. However, these approaches suffer from high recovery latency, because of large I/O disk overhead. In order to reduce excessive latency in failure recovery, we save the intermediate results which are produced during the stream processing, and propose an algorithm DCAS which asynchronously snapshots state to implements precise recovery. In addition, we use in-memory distributed cache to provide the storage of intermediate results and snapshots to reduce recovery latency. We evaluate our failure recovery approach in recovery latency and runtime overhead. The experimental results show that our approach is 2 to 6 times faster than other conventional failure recovery approaches, and induces a 6% runtime overhead.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123785962","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

Framework for Adaptive Computation Offloading in IoT Applications 物联网应用中自适应计算卸载框架

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131717

Shihong Chen, B. Liu, Xing Chen, Ying Zhang, Gang Huang

{"title":"Framework for Adaptive Computation Offloading in IoT Applications","authors":"Shihong Chen, B. Liu, Xing Chen, Ying Zhang, Gang Huang","doi":"10.1145/3131704.3131717","DOIUrl":"https://doi.org/10.1145/3131704.3131717","url":null,"abstract":"The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. IoT applications try to provide more and more functionality and then they inevitably become so complex as to make the limits of devices worse, which may lead to poor performance of applications. Computation offloading is a promising way to improve the performance of an IoT application by executing some parts of the application on remote devices or servers. However, supporting such capability is not easy for application developers due to (1) adaptability: IoT applications often face changes of runtime environments so that the adaptation on offloading is needed. (2) effectiveness: when the device context changes, it needs to dynamically decide the deployment plan of computation tasks, and the reduced execution time must be greater than the network delay and extra overheads caused by offloading. This paper proposes a framework which supports IoT applications with adaptive computation offloading capability. First, a design pattern is proposed to enable an application to be computation offloaded on-demand. Second, an estimation model is presented to automatically decide the deployment plan for offloading. Third, a framework is implemented to support the design pattern and the estimation model. A thorough evaluation on the real-world application is proposed, and the results show that our approach can help reduce execution time by over 45% in most scenarios.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122367036","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: 7

API Usage Change Rules Mining based on Fine-grained Call Dependency Analysis 基于细粒度调用依赖分析的API使用变化规则挖掘

Proceedings of the 9th Asia-Pacific Symposium on Internetware Pub Date : 2017-09-23 DOI: 10.1145/3131704.3131707

Ping Yu, Fei Yang, Chun Cao, Hao Hu, Xiaoxing Ma

{"title":"API Usage Change Rules Mining based on Fine-grained Call Dependency Analysis","authors":"Ping Yu, Fei Yang, Chun Cao, Hao Hu, Xiaoxing Ma","doi":"10.1145/3131704.3131707","DOIUrl":"https://doi.org/10.1145/3131704.3131707","url":null,"abstract":"Software frameworks are widely used in application development. But APIs of a framework may change when it evolves to accommodate new feature requests or to fix bugs. Those changes may break existing client programs of the framework, so client programs need to be migrated to the updated release when the framework evolves. Some technologies (e.g. call dependency analysis) have been proposed to find replacement APIs between the old and new framework releases. However, existing approaches based on call dependency analysis take whole method body as an analysis unit. The context in which a method is called is ignored. In this paper, we present a fine-grained approach named AUC-Miner to infer API usage change rules between two releases of the framework. To take method invocation context into consideration, we propose an approach to get more precise call relationship changes by code splitting. We also analyze indirect method invocations to re-fine call dependency analysis. After elaborating API usage change transactions, we adopt frequent item-set mining to generate API replacement rules. Text similarity and some heuristics to identify evolution of root methods are also applied in the mining progress. The evaluation of AUC-Miner on three popular frameworks shows that its precision is higher than basic call dependency analysis and another API replacement recommendation tool named AURA.","PeriodicalId":349438,"journal":{"name":"Proceedings of the 9th Asia-Pacific Symposium on Internetware","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134352294","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: 3