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Formalization of Android Activity-Fragment Multitasking Mechanism and Static Analysis of Mobile Apps

Formal Aspects of Computing 2025年第2期37卷 1-86页

作者： He, Jinlong Wu, Zhilin Chen, Taolue Key Laboratory of System Software Chinese Academy of Sciences Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China School of Computing and Mathematical Sciences Birkbeck University of London Northern Ireland London United Kingdom

The multitasking mechanism between activities and fragments plays a fundamental role in the Android operating system, which involves a wide range of features, including launch modes, intent flags, task affinities, and structured activities containing fragments. All of them are being widely used in Android apps, both open source and commercial ones. In this article, we present a formal semantics of the Android multitasking mechanism between activities and fragments, which accommodates all the important features and gives insofar the most comprehensive and accurate formalization. In particular, our semantics is formulated based on multi-stack systems, and fully captures the behavior of task stacks and activity stacks regarding fragments. Based on the semantics, we provide new static analysis algorithms, which are both multi-stack aware and fragment sensitive, thus achieve more precise static analysis for Android apps. We validate our approach by extensive experiments on both open source and commercial Android apps. The results highlight the benefits of the considering the semantics of the multitasking mechanism between activities and fragments in static analysis, and confirm the efficacy of our approach. © 2025 Copyright held by the owner/author(s).

关键词： Android multitasking mechanism activities and fragments formal semantics stack unboundedness static analysis

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Characterizing the app recommendation relationships in the iOS app store: a complex network's perspective

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science China(Information sciences) 2025年第4期68卷 284-299页

作者： Gang HUANG Fuqi LIN Yun MA Haoyu WANG Qingxiang WANG Gareth TYSON Xuanzhe LIU Key Lab of High Confidence Software Technologies (Peking University) Ministry of Education School of Computer Science Peking University Institute for Artificial Intelligence Peking University School of Cyber Science and Engineering Huazhong University of Science and Technology Alibaba Group Hong Kong University of Science and Technology (Guangzhou)

Mobile apps have become widely adopted in our daily lives. To facilitate app discovery, most app markets provide recommendations for users, which may significantly impact how apps are accessed. However, little has been known about the underlying relationships and how they reflect(or affect) user behaviors. To fill this gap, we characterize the app recommendation relationships in the i OS app store from the perspective of the complex network. We collect a dataset containing over 1.3 million apps and 50 million app recommendations. This dataset enables us to construct a complex network that captures app recommendation relationships. Through this, we explore the recommendation relationships between mobile apps and how these relationships reflect or affect user behavior patterns. The insights gained from our research can be valuable for understanding typical user behaviors and identifying potential policy-violating apps.

关键词： mobile app recommendation complex network user behavior policy-violating app

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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Detecting Element Accessing Bugs in C++ Sequence Containers 24

Detecting Element Accessing Bugs in C++ Sequence Containers

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39th ACM/IEEE International Conference on Automated software Engineering, ASE 2024

作者： Li, Zhilin Ma, Xutong Hu, Mengze Yan, Jun State Key Lab. of Computer Science Ins. of Software CAS University of Chinese Academy of Sciences Beijing China State Key Lab. of Computer Science Ins. of Software CAS Beijing China State Key Lab. of Computer Science Ins. of Software CAS Tech. Center of Software Eng. Ins. of Software CAS University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Sequence Containers (SC) in the C++ Standard Template Library (STL), such as the vector, are widely used in large-scale projects for their maintainability and flexibility. However, accessing the elements in an SC is bug-prone, as such operations will not check their boundaries during compilation or execution, which can lead to memory errors, such as buffer overflow problems. And these bugs are difficult to detect with available static analyzers, since the size of SCs and the target of iterators cannot be precisely tracked without accurate analysis of the behavior of SCs and *** address this problem, we propose a combined model of SC sizes and iterator targets by tracking them simultaneously through a set of meta-operations extracted from corresponding method calls, and report improper operation usages according to three bug patterns. We implement the approach as a static analyzer, Scasa, on the top of the Clang Static Analyzer (CSA) framework, and evaluate its effectiveness and efficiency against CSA and other state-of-the-art static analyzers on a benchmark composed of 2,230 manually created code snippets and eight popular open-source C++ projects with a lot of SC usages. The experimental results reveal that Scasa effectively identifies nearly all inherent bugs within the manual code snippets and generates 125 reports for these projects (with a time loss of 5 - 85%) where 72 of them are marked as correct with a manual revision. And to further confirm these correct reports, we also select some important ones for developers. These results show that accessing elements of SCs is bug-prone, and cooperatively tracking SC sizes and iterator targets can accurately detect these bugs with acceptable overhead. Copyright held by the owner/author(s).

关键词： C++ (programming language)

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FIFAWC:a dataset with detailed annotation and rich semantics for group activity recognition

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Frontiers of computer science 2024年第6期18卷 271-272页

作者： Duoxuan PEI Di HUANG Yunhong WANG State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Intelligent Recognition and Image Processing Lab. School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

1 *** Activity Recognition(GAR),which aims to identify activities performed collectively in videos,has gained significant attention *** conventional action recognition centered on single individuals,GAR explores the c... 详细信息

关键词： has collective gained

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Generalized splitting-ring number theoretic transform

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Frontiers of computer science 2024年第4期18卷 205-207页

作者： Zhichuang LIANG Yunlei ZHAO Zhenfeng ZHANG School of Computer Science Fudan UniversityShanghai 200433China State Key Laboratory of Cryptology Beijing 100036China Institute of Software Chinese Academy of SciencesBeijing 100190China

1 Introduction Lattice-based cryptography is one of the most promising routine of post-quantum cryptography(PQC).The fundamental and time-consuming operation in lattice-based schemes is the polynomial multiplication i... 详细信息

关键词： ring splitting polynomial

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AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks

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Journal of computer science & Technology 2024年第2期39卷 401-420页

作者：龚成卢冶代素蓉邓倩杜承昆李涛 College of Software Nankai UniversityTianjin 300350China College of Computer Science Nankai UniversityTianjin 300350China State Key Laboratory of Processors Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China

Exploring the expected quantizing scheme with suitable mixed-precision policy is the key to compress deep neural networks(DNNs)in high efficiency and *** exploration implies heavy workloads for domain experts,and an automatic compression method is ***,the huge search space of the automatic method introduces plenty of computing budgets that make the automatic process challenging to be applied in real *** this paper,we propose an end-to-end framework named AutoQNN,for automatically quantizing different layers utilizing different schemes and bitwidths without any human *** can seek desirable quantizing schemes and mixed-precision policies for mainstream DNN models efficiently by involving three techniques:quantizing scheme search(QSS),quantizing precision learning(QPL),and quantized architecture generation(QAG).QSS introduces five quantizing schemes and defines three new schemes as a candidate set for scheme search,and then uses the Differentiable Neural Architecture Search(DNAS)algorithm to seek the layer-or model-desired scheme from the *** is the first method to learn mixed-precision policies by reparameterizing the bitwidths of quantizing schemes,to the best of our *** optimizes both classification loss and precision loss of DNNs efficiently and obtains the relatively optimal mixed-precision model within limited model size and memory *** is designed to convert arbitrary architectures into corresponding quantized ones without manual intervention,to facilitate end-to-end neural network *** have implemented AutoQNN and integrated it into *** experiments demonstrate that AutoQNN can consistently outperform state-of-the-art *** 2-bit weight and activation of AlexNet and ResNet18,AutoQNN can achieve the accuracy results of 59.75%and 68.86%,respectively,and obtain accuracy improvements by up to 1.65%and 1.74%,respectively,compared with state-of-the-art ***,c

关键词： automatic quantization mixed precision quantizing scheme search quantizing precision learning quan-tized architecture generation

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A Blockchain Wallet Scheme with Multi-Factor Authentication Based on Distributed System 4

A Blockchain Wallet Scheme with Multi-Factor Authentication ...

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4th International Conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Gao, Qianwen Tu, Yichi Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Tca Lab of State Key Laboratory of Computer Science Beijing China

ISBN: (纸本)9798331528324

Blockchain wallet is a technology focusing on generating, storing and utilizing private keys to manage digital assets securely. As a service, blockchain wallets require user authentication. Traditional blockchain wallets employ mnemonic phrases to assist users in storing and managing private keys. However, the complex operation procedures and the totally different identity authentication mechanism of traditional wallets undoubtedly hinder their development. What's worse, it's inconvenient for secure storage, and doesn't support account recovery, which affects the security and usability of traditional wallets. To address this issue, this paper provides a solution for identity authentication and private key management of blockchain digital wallets in distributed scenarios. It proposes an architecture for building a distributed multi-factor authentication digital wallet for blockchain. We design and implement this blockchain digital wallet based on a distributed multi-factor authentication system. By employing a secret sharing scheme, the encrypted private key shares are stored on distributed servers. When a user wants to use his private key, the wallet conducts a private key recovery operation, which significantly reducing the risk of storing the private key locally. This mitigates security issues such as single-point failure and weak password attacks. What's more, Users are only required to operate the hardware token once during the authentication and private key recovery operation, ensuring the balance between the security and usability of blockchain digital wallets. © 2024 IEEE.

关键词： Blockchain

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PAD: A Robustness Enhancement Ensemble Method via Promoting Attention Diversity 30

PAD: A Robustness Enhancement Ensemble Method via Promoting ...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Yang, Yuting Huang, Pei Ma, Feifei Cao, Juan Li, Jintao China University of Chinese Academy of Sciences China Department of Computer Science Stanford University United States State Key Laboratory of Computer Science Institute of Software CAS China Laboratory of Parallel Software and Computational Science Institute of Software CAS China

ISBN: (纸本)9782493814104

Deep neural networks can be vulnerable to adversarial attacks, even for the mainstream Transformer-based models. Although several robustness enhancement approaches have been proposed, they usually focus on some certain type of perturbation. As the types of attack can be various and unpredictable in practical scenarios, a general and strong defense method is urgently in require. We notice that most well-trained models can be weakly robust in the perturbation space, i.e., only a small ratio of adversarial examples exist. Inspired by the weak robust property, this paper presents a novel ensemble method for enhancing robustness. We propose a lightweight framework PAD to save computational resources in realizing an ensemble. Instead of training multiple models, a plugin module is designed to perturb the parameters of a base model which can achieve the effect of multiple models. Then, to diversify adversarial example distributions among different models, we promote each model to have different attention patterns via optimizing a diversity measure we defined. Experiments on various widely-used datasets and target models show that PAD can consistently improve the defense ability against many types of adversarial attacks while maintaining accuracy on clean data. Besides, PAD also presents good interpretability via visualizing diverse attention patterns. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Deep neural networks

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A survey for light field super-resolution

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High-Confidence Computing 2024年第1期4卷 118-129页

作者： Mingyuan Zhao Hao Sheng Da Yang Sizhe Wang Ruixuan Cong Zhenglong Cui Rongshan Chen Tun Wang Shuai Wang Yang Huang Jiahao Shen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang UniversityHangzhou 311115China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Compared to 2D imaging data,the 4D light field(LF)data retains richer scene’s structure information,which can significantly improve the computer’s perception capability,including depth estimation,semantic segmentation,and LF ***,there is a contradiction between spatial and angular resolution during the LF image acquisition *** overcome the above problem,researchers have gradually focused on the light field super-resolution(LFSR).In the traditional solutions,researchers achieved the LFSR based on various optimization frameworks,such as Bayesian and Gaussian *** learning-based methods are more popular than conventional methods because they have better performance and more robust generalization *** this paper,the present approach can mainly divided into conventional methods and deep learning-based *** discuss these two branches in light field spatial super-resolution(LFSSR),light field angular super-resolution(LFASR),and light field spatial and angular super-resolution(LFSASR),***,this paper also introduces the primary public datasets and analyzes the performance of the prevalent approaches on these ***,we discuss the potential innovations of the LFSR to propose the progress of our research field.

关键词： Light field super-resolution Convolutional neural network Transformer Sub-aperture image Epipolar-plane image

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