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DroidLink: Automated Generation of Deep Links for Android Apps [article]

Yun Ma, Xuanzhe Liu, Ruogu Du, Ziniu Hu, Yi Liu, Meihua Yu, Gang Huang
2016 arXiv   pre-print
The mobile application (app) has become the main entrance to access the Internet on handheld devices. Unlike the Web where each webpage has a global URL to reach directly, a specific "content page" of an app can be opened only by exploring the app with several operations from the landing page. The interoperability between apps is quite fixed and thus limits the value-added "linked data" between apps. Recently, deep link has been proposed to enable targeting and opening a specific page of an app
more » ... ific page of an app externally with an accessible uniform resource identifier (URI). However, implementing deep link for mobile apps requires a lot of manual efforts by app developers, which can be very error-prone and time-consuming. In this paper, we propose DroidLink to automatically generating deep links for existing Android apps. We design a deep link model suitable for automatic generation. Then we explore the transition of pages and build a navigation graph based on static and dynamic analysis of Android apps. Next, we realize an updating mechanism that keeps on revisiting the target app and discover new pages, and thus generates deep links for every single page of the app. Finally, we repackage the app with deep link supports, but requires no additional deployment requirements. We generate deep links for some popular apps and demonstrate the feasibility of DroidLink.
arXiv:1605.06928v1 fatcat:ohz75ayn2zbzhgntjtc532npiy

Characterizing EOSIO Blockchain [article]

Yuheng Huang, Haoyu Wang, Lei Wu, Gareth Tyson, Xiapu Luo, Run Zhang, Xuanzhe Liu, Gang Huang, Xuxian Jiang
2020 arXiv   pre-print
EOSIO has become one of the most popular blockchain platforms since its mainnet launch in June 2018. In contrast to the traditional PoW-based systems (e.g., Bitcoin and Ethereum), which are limited by low throughput, EOSIO is the first high throughput Delegated Proof of Stake system that has been widely adopted by many applications. Although EOSIO has millions of accounts and billions of transactions, little is known about its ecosystem, especially related to security and fraud. In this paper,
more » ... ud. In this paper, we perform a large-scale measurement study of the EOSIO blockchain and its associated DApps. We gather a large-scale dataset of EOSIO and characterize activities including money transfers, account creation and contract invocation. Using our insights, we then develop techniques to automatically detect bots and fraudulent activity. We discover thousands of bot accounts (over 30% of the accounts in the platform) and a number of real-world attacks (301 attack accounts). By the time of our study, 80 attack accounts we identified have been confirmed by DApp teams, causing 828,824 EOS tokens losses (roughly 2.6 million US$) in total.
arXiv:2002.05369v1 fatcat:gnklajb24begxmzz26z5ewaouy


Yun Ma, Ziniu Hu, Yunxin Liu, Tao Xie, Xuanzhe Liu
2018 Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18  
Compared to the Web where each web page has a global URL for external access, a specific "page" inside a mobile app cannot be easily accessed unless the user performs several steps from the landing page of this app. Recently, the concept of "deep link" is expected to be a promising solution and has been advocated by major service providers to enable targeting and opening a specific page of an app externally with an accessible uniform resource identifier. In this paper, we present a large-scale
more » ... sent a large-scale empirical study to investigate how deep links are really adopted, over 25,000 Android apps. To our surprise, we find that deep links have quite low coverage, e.g., more than 70% and 90% of the apps do not have deep links on app stores Wandoujia and Google Play, respectively. One underlying reason is the mandatory and non-trivial manual efforts of app developers to provide APIs for deep links. We then propose the Aladdin approach along with its supporting tool to help developers practically automate the release of deep-link APIs to access locations inside their apps. Aladdin includes a novel cooperative framework by synthesizing the static analysis and the dynamic analysis while minimally engaging developers' inputs and configurations, without requiring any coding efforts or additional deployment efforts. We evaluate Aladdin with 579 popular apps and demonstrate its effectiveness and performance. CCS CONCEPTS • Human-centered computing → Ubiquitous and mobile computing systems and tools; KEYWORDS Deep link; Android apps; program analysis ACM Reference Format:
doi:10.1145/3178876.3186059 dblp:conf/www/MaHL0L18 fatcat:y54cn3hm7za5dlworbqsmqguri

A First Look at Blockchain-based Decentralized Applications [article]

Kaidong Wu, Yun Ma, Gang Huang, Xuanzhe Liu
2019 arXiv   pre-print
With the increasing popularity of blockchain technologies in recent years, blockchain-based decentralized applications (DApps for short in this paper) have been rapidly developed and widely adopted in many areas, being a hot topic in both academia and industry. Despite of the importance of DApps, we still have quite little understanding of DApps along with its ecosystem. To bridge the knowledge gap, this paper presents the first comprehensive empirical study of blockchain-based DApps to date,
more » ... ed DApps to date, based on an extensive dataset of 995 Ethereum DApps and 29,846,075 transaction logs over them. We make a descriptive analysis of the popularity of DApps, summarize the patterns of how DApps use smart contracts to access the underlying blockchain, and explore the worth-addressing issues of deploying and operating DApps. Based on the findings, we propose some implications for DApp users to select proper DApps, for DApp developers to improve the efficiency of DApps, and for blockchain vendors to enhance the support of DApps.
arXiv:1909.00939v1 fatcat:st3qtdqi6fczrln6a2e6vk232i

Demystifying Developers' Issues in Distributed Training of Deep Learning Software [article]

Diandian Gu, Zhenpeng Chen, Yuanqiang Liu, Zili Zhang, Yun Ma, Xin Jin, Xuanzhe Liu
2021 arXiv   pre-print
Deep learning (DL) has been pervasive in a wide spectrum of nowadays software systems and applications. The rich features of these DL based software applications (i.e., DL software) usually rely on powerful DL models. To train powerful DL models with large datasets efficiently, it has been a common practice for developers to parallelize and distribute the computation and memory over multiple devices in the training process, which is known as distributed training. However, existing efforts in
more » ... sting efforts in the software engineering (SE) research community mainly focus on issues in the general process of training DL models. In contrast, to the best of our knowledge, issues that developers encounter in distributed training have never been well studied. Given the surging importance of distributed training in the current practice of developing DL software, this paper fills in the knowledge gap and presents the first comprehensive study on developers' issues in distributed training. To this end, we extract and analyze 1,054 real-world developers' issues in distributed training from Stack Overflow and GitHub, two commonly used data sources for studying software issues. We construct a fine-grained taxonomy consisting of 30 categories regarding the fault symptoms and summarize common fix patterns for different symptoms. Based on the results, we suggest actionable implications and research avenues that can potentially facilitate the future development of distributed training.
arXiv:2112.06222v1 fatcat:kmmqsghqgbdu3btozzysmgy664

Understanding Characteristics of Commodity Serverless Computing Platforms [article]

Jinfeng Wen, Yi Liu, Zhenpeng Chen, Yun Ma, Haoyu Wang, Xuanzhe Liu
2021 arXiv   pre-print
Serverless computing becomes the new trending paradigm in cloud computing, allowing developers to focus on the core application logic and rapidly prototype applications. Due to the great prospects of serverless computing, in recent years, most major cloud vendors have rolled out their commodity serverless computing platforms. However, the characteristics of these platforms have not been systematically studied. To fill this knowledge gap, this paper presents a comprehensive study on
more » ... udy on characterizing mainstream commodity serverless computing platforms (i.e., AWS Lambda, Azure Functions, Google Cloud Functions, and Alibaba Cloud Function Compute). First, we qualitatively analyze these platforms from development, deployment, and runtime aspects to form the taxonomy of characteristics. Additionally, we quantitatively evaluate the actual performance of different serverless computing platforms through our designed benchmark platform. Our benchmark platform has two types of benchmarks, i.e., microbenchmarks and macrobenchmarks. Based on the results of qualitative and quantitative analyses, we derive a series of findings and provide insightful implications for both developers and cloud vendors.
arXiv:2012.00992v2 fatcat:l2d6hgaa4vcxnjmfeznvnxygem

Hierarchical Federated Learning through LAN-WAN Orchestration [article]

Jinliang Yuan, Mengwei Xu, Xiao Ma, Ao Zhou, Xuanzhe Liu, Shangguang Wang
2020 arXiv   pre-print
Conference'17, July 2017, Washington, DC, USA Jinliang Yuan, Mengwei Xu, Xiao Ma, Ao Zhou, Xuanzhe Liu, and Shangguang Wang  ... 
arXiv:2010.11612v1 fatcat:oumtgzsck5gqngzxtnxt4l42ai

Predicting Smartphone Battery Life based on Comprehensive and Real-time Usage Data [article]

Huoran Li, Xuanzhe Liu, Qiaozhu Mei
2018 arXiv   pre-print
Smartphones and smartphone apps have undergone an explosive growth in the past decade. However, smartphone battery technology hasn't been able to keep pace with the rapid growth of the capacity and the functionality of smartphones and apps. As a result, battery has always been a bottleneck of a user's daily experience of smartphones. An accurate estimation of the remaining battery life could tremendously help the user to schedule their activities and use their smartphones more efficiently.
more » ... e efficiently. Existing studies on battery life prediction have been primitive due to the lack of real-world smartphone usage data at scale. This paper presents a novel method that uses the state-of-the-art machine learning models for battery life prediction, based on comprehensive and real-time usage traces collected from smartphones. The proposed method is the first that identifies and addresses the severe data missing problem in this context, using a principled statistical metric called the concordance index. The method is evaluated using a dataset collected from 51 users for 21 months, which covers comprehensive and fine-grained smartphone usage traces including system status, sensor indicators, system events, and app status. We find that the remaining battery life of a smartphone can be accurately predicted based on how the user uses the device at the real-time, in the current session, and in history. The machine learning models successfully identify predictive features for battery life and their applicable scenarios.
arXiv:1801.04069v1 fatcat:nam55jx3hbf45mjhgklkxjijva

A First Look at Emoji Usage on GitHub: An Empirical Study [article]

Xuan Lu, Yanbin Cao, Zhenpeng Chen, Xuanzhe Liu
2018 arXiv   pre-print
Emoji is becoming a ubiquitous language and gaining worldwide popularity in recent years including the field of software engineering (SE). As nonverbal cues, emojis are widely used in user understanding tasks such as sentiment analysis, but few work has been done to study emojis in SE scenarios. This paper presents a large scale empirical study on how GitHub users use emojis in development-related communications. We find that emojis are used by a considerable proportion of GitHub users. In
more » ... tHub users. In comparison to Internet users, developers show interesting usage characteristics and have their own interpretation of the meanings of emojis. In addition, the usage of emojis reflects a positive and supportive culture of this community. Through a manual annotation task, we find that sentimental usage is a main intention of using emojis in issues, pull requests, and comments, while emojis are mainly used to emphasize important contents in README. These findings not only deepen our understanding about the culture of SE communities, but also provide implications on how to facilitate SE tasks with emojis such as sentiment analysis.
arXiv:1812.04863v1 fatcat:ybtghv3xlnagvm6qmyo54h3dpi


Tao Xie, Yuanfang Cai, Xuanzhe Liu, Xiaoyin Wang, Mithun P. Acharya, Marcelo d'Amorim, Xiaoxing Ma
2017 Journal of Computer Science and Technology  
We appreciate great help from the guest editors for the theme of data-driven software engineering: Yuanfang Cai (Drexel University, Philadelphia), Xuanzhe Liu (Peking University, Beijing), and Xiaoyin  ...  Liu is an associate professor in Peking University, Beijing.  ... 
doi:10.1007/s11390-017-1782-3 fatcat:qumbvtkptvaabefrpy2gconoue

Measurement and Analysis of Mobile Web Cache Performance

Yun Ma, Xuanzhe Liu, Shuhui Zhang, Ruirui Xiang, Yunxin Liu, Tao Xie
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15  
The Web browser is a killer app on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, caching has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the performance of mobile Web caching. For example, most of these studies mainly focus on client-side implementations but not server-side
more » ... not server-side configurations, suffer from biased user behaviors, and fail to study "miscached" resources. To address these issues, in this paper, we present a proactive approach for a comprehensive measurement study on mobile Web cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effective the caching works in practice. We report detailed analysis results of different websites and various types of Web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems -Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content, Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile Web developers can do to mitigate those problems.
doi:10.1145/2736277.2741114 dblp:conf/www/MaLZXLX15 fatcat:6txguz6hrnax7eqtgzsh7zz6tu

Service Encapsulation for Middleware Management Interfaces

Xing Chen, Xuanzhe Liu, Xiaodong Zhang, Zhao Liu, Gang Huang
2010 2010 Fifth IEEE International Symposium on Service Oriented System Engineering  
Middleware has become the popular runtime infrastructure of modern IT systems. Due to the complex application contexts and various user requirements, more and more applications are now making use of different middleware platforms. It might require the cooperation of several types of middleware, and result in challenging issues for collaborative management of heterogeneous middleware. To solve this problem, it may be a feasible solution to make management interfaces delivered in the form of
more » ... in the form of services and used in serviceoriented styles. In this paper, we propose an approach to encapsulating middleware management interfaces into Web services. First of all, we introduce middleware management problems induced by the development of requirements. Then, we present the technical challenges and illustrate the details about how to enable different management interfaces to be in service-oriented styles. Followed by identified technical challenges, we evaluate the approach and primarily discuss how to manage middleware systems collaboratively based on management services.
doi:10.1109/sose.2010.35 dblp:conf/sose/ChenLZLH10 fatcat:6xwfi2ntivhifoxvi4tvnvca5y

Internet of Bodies/Internet of Sports

M. Brian Blake, Nagarajan Kandasamy, Schahram Dustdar, Xuanzhe Liu
2020 IEEE Internet Computing  
Xuanzhe Liu is currently an Associate Professor and an Assistant Dean with the Institute for Artificial Intelligence, Peking University, Beijing, China.  ... 
doi:10.1109/mic.2020.3026924 fatcat:crnygwwyordkzd7lqcf6x2vcrm


Liu Xuanzhe, Qi Zhao, Gang Huang, Zhi Jin, Hong Mei
2010 Proceedings of the IEEE/ACM international conference on Automated software engineering - ASE '10  
The Web is currently moving towards a platform with rich services. A notable trend is that end-users create mashups by composing services with short, iterative development life cycles as well as updating with evolving needs. However, the large number of services and the high complexity of composition constraints make manual composition extremely difficult. Addressing this issue, we have developed an approach to assisting the end-users to build mashups in a simple and fast fashion. A tag-based
more » ... hion. A tag-based model provides end-users a quick and intuitive insight of services. End-users simply describe their desired goals with tags. Interacting with a service repository, our approach employs a planning approach to suggest services that end-users might want to involve in the final outputs, including some additional interesting or relevant ones to induce more potential composition opportunities. End-users are allowed to iteratively modify, adjust or refine their goals. We have implemented our approach with a tool called iMashup.
doi:10.1145/1858996.1859052 dblp:conf/kbse/LiuZHJM10 fatcat:peg7dsqptfh5bhgdjpyjmzckqa

Understanding and Detecting Fragmentation-Induced Compatibility Issues for Android Apps

Lili Wei, Yepang Liu, S.C. Cheung, Huaxun Huang, Xuan Lu, Xuanzhe Liu
2018 IEEE Transactions on Software Engineering  
Liu et al. observed that a notable proportion of Android performance bugs occur only on specific devices and platforms [90] .  ... 
doi:10.1109/tse.2018.2876439 fatcat:ca6ncthalfhahalqteweevku5y
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