Xuanzhe Liu

Xuanzhe Liu
Peking University | PKU · School of Electronic and Computer Engineering

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153
Publications
46,195
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Introduction
Skills and Expertise

Publications

Publications (153)
Preprint
Serverless computing is an emerging cloud computing paradigm that has been applied to various domains, including machine learning, scientific computing, video processing, etc. To develop serverless computing-based software applications (a.k.a., serverless applications), developers follow the new cloud-based software architecture, where they develop...
Preprint
Serverless computing is an emerging cloud computing paradigm that frees developers from server management. However, existing studies report that software applications developed in serverless fashion (named serverless applications) severely suffer from cold start latency. We propose an application-level performance optimization approach called Lambd...
Preprint
Serverless computing is an emerging cloud computing paradigm. Moreover, it has become an attractive development option for cloud-based applications for software developers. The most significant advantage of serverless computing is to free software developers from the burden of complex underlying management tasks and allow them to focus on only the...
Article
A reliable and up-to-date malware dataset is critical to evaluate the effectiveness of malware detection approaches. Although there are several widely-used malware benchmarks in our community (e.g., MalGenome, Drebin, Piggybacking and AMD, etc.), these benchmarks face several limitations including out-of-date, size, coverage, and reliability issues...
Preprint
Full-text available
This paper proposes Mandheling, the first system that enables highly resource-efficient on-device training by orchestrating the mixed-precision training with on-chip Digital Signal Processing (DSP) offloading. Mandheling fully explores the advantages of DSP in integer-based numerical calculation by four novel techniques: (1) a CPU-DSP co-scheduling...
Article
Mobile malware detection has attracted massive research effort in our community. A reliable and up-to-date malware dataset is critical to evaluate the effectiveness of malware detection approaches. Essentially, the malware ground truth should be manually verified by security experts, and their malicious behaviors should be carefully labelled. Altho...
Preprint
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Deploying deep learning (DL) on mobile devices has been a notable trend in recent years. To support fast inference of on-device DL, DL libraries play a critical role as algorithms and hardware do. Unfortunately, no prior work ever dives deep into the ecosystem of modern DL libs and provides quantitative results on their performance. In this paper,...
Preprint
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 distrib...
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Public edge platforms have drawn increasing attention from both academia and industry. In this study, we perform a first-of-its-kind measurement study on a leading public edge platform that has been densely deployed in China. Based on this measurement, we quantitatively answer two critical yet unexplored questions. First, from end users' perspectiv...
Article
Modern mobile OSes support to display Web pages in the native apps, which we call embedded Web pages. In this paper, we conduct, to the best of our knowledge, the first measurement study on browsing embedded Web pages on Android. Our study on 22,521 popular Android apps shows that 57.9% and 73.8% of apps embed Web pages on two popular app markets:...
Article
The past decades witnessed the fast and wide deployment of Internet. The Internet has bred the ubiquitous computing environment that is spanning the cloud, edge, mobile devices, and IoT. Software running over such a ubiquitous computing environment environment is eating the world. A recently emerging trend of Internet-based software systems is “ re...
Article
A new vision of harnessing the ocean of video data captured by cameras in an efficient, secure, and manageable way. Following the hardware trends in reality, we advocate to treat cameras as the first-class computing and storage platform, and expose their services to third parties. To this end, the cameras should move from hard-coded to software-def...
Preprint
Emotions at work have long been identified as critical signals of work motivations, status, and attitudes, and as predictors of various work-related outcomes. For example, harmonious passion increases commitment at work but stress reduces sustainability and leads to burnouts. When more and more employees work remotely, these emotional and mental he...
Article
Sentiment and emotion detection from textual communication records of developers have various application scenarios in software engineering (SE). However, commonly used off-the-shelf sentiment/emotion detection tools cannot obtain reliable results in SE tasks and misunderstanding of technical knowledge is demonstrated to be the main reason. Then re...
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Deep Learning (DL) is finding its way into a growing number of mobile software applications. These software applications, named as DL based mobile applications (abbreviated as mobile DL apps) integrate DL models trained using large-scale data with DL programs. A DL program encodes the structure of a desirable DL model and the process by which the m...
Preprint
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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 character...
Preprint
WebAssemly is an emerging runtime for Web applications and has been supported in almost all browsers. Recently, WebAssembly is further regarded to be a the next-generation environment for blockchain applications, and has been adopted by Ethereum, namely eWASM, to replace the state-of-the-art EVM. However, whether and how well current eWASM outperfo...
Article
Edge Computing has emerged as a new computing paradigm dedicated for mobile applications for performance enhancement and energy efficiency purposes. Specifically, it benefits today's interactive applications on power-constrained devices by offloading compute-intensive tasks to the edge nodes which is in close proximity. Meanwhile, Field Programmabl...
Preprint
Federated learning (FL) was designed to enable mobile phones to collaboratively learn a global model without uploading their private data to a cloud server. However, exiting FL protocols has a critical communication bottleneck in a federated network coupled with privacy concerns, usually powered by a wide-area network (WAN). Such a WAN-driven FL de...
Article
Many studies have explored various algorithms to predict where a user is likely to visit based on their contexts and trajectories. While successful cases are often reported, few discussions have been done on what happens if the prediction targets vary: whether coarser locations are easier to be predicted, and whether predicting the immediate next l...
Preprint
As COVID-19 has been spreading across the world since early 2020, a growing number of malicious campaigns are exploiting the COVID-19 pandemic. Cryptocurrency has attracted great attentions from attackers in this pandemic, namely, COVID-19 themed cryptocurrency scams are increasingly popular during the pandemic. However, these newly emerging scams...
Article
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 decentralized applications. A...
Conference Paper
Sentiment classification typically relies on a large amount of labeled data. In practice, the availability of labels is highly imbalanced among different languages. To tackle this problem, cross-lingual sentiment classification approaches aim to transfer knowledge learned from one language that has abundant labeled examples (i.e., the source langua...
Article
Smartphone applications (a.k.a., apps) have become indispensable in our everyday life and work. In practice, accomplishing a task on smartphones may require the user to navigate among various apps. Unlike Web pages that are inherently interconnected through hyperlinks, apps are usually isolated building blocks, and the lack of direct links between...
Preprint
Federated learning (FL) is an emerging distributed machine learning paradigm that stands out with its inherent privacy-preserving advantages. Heterogeneity is one of the core challenges in FL, which resides in the diverse user behaviors and hardware capacity across devices who participate in the training. Heterogeneity inherently exerts a huge infl...
Preprint
Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. These software applications, named as DL based software (in short as DL software), integrate DL models trained using a large data corpus with DL programs written based on DL frameworks such as TensorFlow and Keras. A DL program encodes the networ...
Preprint
To preserve user privacy while enabling mobile intelligence, techniques have been proposed to train deep neural networks on decentralized data. However, training over decentralized data makes the design of neural architecture quite difficult as it already was. Such difficulty is further amplified when designing and deploying different neural archit...
Article
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 al...
Preprint
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 al...
Preprint
Surveillance IoT cameras are becoming autonomous: they operate on batteries without connecting to power wires, and run analytics without help from external compute resources. Such autonomous paradigm significantly frees video analytics from privacy concern and deployment constraint. However, they are constrained by limited energy and on-device comp...
Conference Paper
Sentiment analysis has various application scenarios in software engineering (SE), such as detecting developers' emotions in commit messages and identifying their opinions on Q&A forums. However, commonly used out-of-the-box sentiment analysis tools cannot obtain reliable results on SE tasks and the misunderstanding of technical jargon is demonstra...
Preprint
Full-text available
Sentiment analysis has various application scenarios in software engineering (SE), such as detecting developers' emotions in commit messages and identifying their opinions on Q&A forums. However, commonly used out-of-the-box sentiment analysis tools cannot obtain reliable results on SE tasks and the misunderstanding of technical jargon is demonstra...
Conference Paper
Full-text available
Sentiment classification typically relies on a large amount of labeled data. In practice, the availability of labels is highly imbalanced among different languages, e.g., more English texts are labeled than texts in any other languages, which creates a considerable inequality in the quality of related information services received by users speaking...
Conference Paper
To bridge the knowledge gap between research and practice, we present the first empirical study on 16,500 the most popular Android apps, demystifying how smartphone apps exploit deep learning in the wild. To this end, we build a new static tool that dissects apps and analyzes their deep learning functions. Our study answers threefold questions: wha...
Preprint
As low-cost surveillance cameras grow rapidly, we advocate for these cameras to be zero streaming: ingesting videos directly to their local storage and only communicating with the cloud in response to queries. To support queries over videos stored on zero-streaming cameras, we describe a system that spans the cloud and cameras. The system builds on...
Conference Paper
Automated-test-generation tools generate test cases to enable dynamic analysis of Android apps, such as functional testing. These tools build a GUI model to describe the app states during the app execution, and generate a script that performs actions on UI widgets to form a test case. However, when the test cases are re-executed, the apps under ana...
Article
Due to their on-body and ubiquitous nature, wearables can generate a wide range of unique sensor data creating countless opportunities for deep learning tasks. We propose DeepWear, a deep learning (DL) framework for wearable devices to improve the performance and reduce the energy footprint. DeepWear strategically offloads DL tasks from a wearable...
Article
Mobile users spend an extensive amount of time on typing. A more efficient text input instrument brings a significant enhancement of user experience. Deep learning techniques have been recently applied to suggesting the next words of input, but to achieve more accurate predictions, these models should be customized for individual users. Personaliza...
Preprint
Full-text available
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...
Preprint
Deep learning (DL) is a game-changing technique in mobile scenarios, as already proven by the academic community. However, no prior literature has studied the adoption of DL in the mobile wild. To fill such gap, in this work, we carry out the first empirical study to demystify how DL is utilized in mobile apps. Based on static analysis technique, w...
Article
Android ecosystem is heavily fragmented. The numerous combinations of different device models and operating system versions make it impossible for Android app developers to exhaustively test their apps, and thus various compatibility issues arise. Unfortunately, little is known on the characteristics of such fragmentation-induced compatibility issu...
Conference Paper
We present DeepCache, a principled cache design for deep learning inference in continuous mobile vision. DeepCache benefits model execution efficiency by exploiting temporal locality in input video streams. It addresses a key challenge raised by mobile vision: the cache must operate under video scene variation, while trading off among cacheability,...
Chapter
When smartphones, applications (a.k.a, apps), and app stores have been widely adopted by the billions, an interesting debate emerges: whether and to what extent do device models influence the behaviors of their users? The answer to this question is critical to almost every stakeholder in the smartphone app ecosystem, including app store operators,...
Preprint
Full-text available
Most existing sentiment analysis approaches heavily rely on a large amount of labeled data that usually involve time-consuming and error-prone manual annotations. The distribution of this labeled data is significantly imbalanced among languages, e.g., more English texts are labeled than texts in other languages, which presents a major challenge to...
Conference Paper
Blockchain systems, with the characteristics of decentralization, irreversibility and traceability, have attracted a lot of attentions recently. However, the current performance of blockchain is poor, which becomes a major constraint of its applications. Additionally, different blockchain systems lack standard performance monitoring approach which...
Conference Paper
Many apps benefit from knowing their power consumption and adapting their behaviors on the fly. To offer apps power knowledge at run time, an OS often meters system power and divides it among apps. Since the impacts of concurrent apps on system power are entangled, this approach not only makes it difficult to reason about power but also results in...
Conference Paper
Full-text available
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 enabl...
Conference Paper
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Based on a large data set of emoji using behavior collected from smartphone users over the world, this paper investigates gender-specific usage of emojis. We present various interesting findings that evidence a considerable difference in emoji usage by female and male users. Such a difference is significant not just in a statistical sense; it is su...
Article
Web browsing is always a key requirement of Internet users. Current mobile Web apps can contain computation-intensive JavaScript logics and thus affect browsing performance. Learning from our over-decade research and development experiences of the Internetware paradigm, we present the novel and generic i-Jacob approach to improving the performance...
Article
Full-text available
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 es...
Conference Paper
Full-text available
Stock trend prediction plays a critical role in seeking maximized profit from stock investment. However, precise trend prediction is very difficult since the highly volatile and non-stationary nature of stock market. Exploding information on Internet together with advancing development of natural language processing and text mining techniques have...
Article
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With the popularity of smartphones, users are heavily dependent on mobile applications for daily work and entertainments. However, mobile apps are becoming more and more complicated with more features and increasing size, part of which may be redundant to users. Due to the limitation of current installation mechanism, users have to download full-si...
Article
Full-text available
Convolutional Neural Network (CNN) is the state-of-the-art algorithm of many mobile vision fields. It is also applied in many vision tasks such as face detection and augmented reality on mobile devices. Though benefited from the high accuracy achieved via deep CNN models, nowadays commercial mobile devices are often short in processing capacity and...
Article
Imperfect Web resource loading prevents mobile Web browsing from providing satisfactory user experience. In this article, we design and implement the SWAROVsky system to address three main issues of inefficiency in current Web resource loading: (1) on-demand and thus slow loading of sub-resources of webpages; (2) duplicated loading of resources wit...
Article
The prevalent smartphones have become the major entrance to accessing services on the Internet. On smartphones, users can have two options as the clients, i.e., native apps and Web apps. There have been several debates about native apps and Web apps. However, major service providers such as Google, Amazon, and Facebook provide both native apps and...
Conference Paper
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., offl...