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International Conference on software Maintenance (ICSM)

作者： Zhenhao Wu Jiashuo Zhang Jianbo Gao Yue Li Qingshan Li Zhi Guan Zhong Chen Key Laboratory of High Confidence Software Technologies Peking University MoE Beijing China EECS Peking University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China

ISBN: (数字)9781728156194

ISBN: (纸本)9781728156200

In recent years, many decentralized applications based on blockchain (DApp) have been developed. Some development tools provide testing functions, but only for developers to write unit tests for smart contracts rather than test DApp as a whole. Moreover, due to the difficulty for testers to understand the implementation details of smart contracts, insufficient functional testing causes some DApps not to meet functional design expectations. The inherent complexity of DApp, inconvenient pre-state setting, and not-so-readable logs make DApp testing challenging. In this paper, we propose Kaya, a testing framework for DApps to bridge these gaps. Firstly, Kaya formulate automatically executed test cases that cover both front-end behaviors and back-end logics with simple setting. Secondly, Kaya provides a flexible and convenient way for test engineers to set the blockchain pre-states. Thirdly, Kaya transforms incomprehensible addresses into readable variables for easier comprehension. Besides, to fit the various application environments, we provide both GUI and CLI for test engineers to use Kaya. Our case study and preliminary human study demonstrates the potential of Kaya in helping test engineers to test DApps more easily. A demo video is at https://***/7DyI_EpVZFw.

关键词： software maintenance Smart contracts Blockchain Transforms Writing Tools Testing

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Anaerobic Granular Sludge Performance in an Expanded Granular Sludge Bed Reactor Treating Calcium-Rich Wastewater by Adjusting Caco3 Crystallization: Effect of Upflow Velocity and Ca2+ Concentration

SSRN

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SSRN 2023年

作者： Liu, Xiaoji Pan, Dongning Yuan, Quan Feng, Xiyuan Li, Meixuan Song, Xuening Li, Meiling Ge, Yajuan Xing, Yukun Yu, Yuanzhou Jin, Zhengyu Key Laboratory of Ecology and Environment in Minority Areas National Ethnic Affairs Commission College of Life & Environmental Sciences Minzu University of China Beijing100081 China School of Ecology and Environment Beijing Technology and Business University Beijing100048 China CECEP（Feixi）WTE CO. Ltd Hefei231241 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China Harbin Institute of Technology Software Engineering Co. Ltd Harbin150028 China Tianjin Research Institute for Water Transport Engineering M.O.T Tianjin300000 China Huanan Construction Limited Company China Construction Sixth Engineering Bureau Shenzhen518108 China

The role of upflow velocity and Ca2+ concentration in controlling the type and rate of CaCO3 crystallization and their impacts on an expanded granular sludge bed (EGSB) reactor were studied. An improved upflow velocity could promote metastable CaCO3 crystals and achieve the optimized portion of vaterite with a value of 84% at 10 m/h with a small amount of aragonite, thus limiting the scaling in the reactor. The calcium concentration was found similar impacts on CaCO3 crystalline phases. Through stepwise setup of increasing upflow velocity and organic loading rate (OLR), granules cultivated in R3 (Ca2+ 800 mg/L) revealed maximum amount of biomass with biggest particle size distribution and fastest average settling rate, with relative stable COD removal efficiency and the fast optimized reactor capacity at OLR of 16 kgCOD/m3d. A low upflow velocity and a higher Ca2+ concentration could be applied at the initial cultivation stage of the EGSB reactor to promote nucleus formation and granules growth. The Ca2+ concentration had a significant impact on the bacterial community and favoured the growth of Tolumonas and Anaeromousa Anaeroarcus. Archaea, rather than bacteria, was strengthened to contribute more to methane production at a relatively high Ca2+ concentration. © 2023, The Authors. All rights reserved.

关键词： Anaerobic digestion

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Dimensional response analysis of self-centering piers subjected to near-fault pulse-like ground motions

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Structures 2025年 79卷

作者： Guiqiang Guo Dongxia Sun Zongliang Wu Zhihao Wang Dixiong Yang School of Civil Engineering and Transportation North China University of Water Resources and Electric Power Zhengzhou 450045 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Department of Engineering Mechanics Dalian University of Technology Dalian 116024 China

The self-centering piers are generally equipped with energy dissipation devices and recentering devices so that the peak and residual drifts can be effectively controlled. However, there is no efforts conducted to systematically analyze the effects of energy dissipation and recentering devices on the peak and residual drifts of self-centering piers subjected to near-fault pulse-like ground motions. To this end, this paper aims to address this issue by using the method of dimensional analysis with intrinsic length scale. First, the appropriate rules of shape parameters for the flag-shaped hysteretic model are examined to represent the plump hysteretic loop of well-designed self-centering piers. Then, idealized MP pulses are utilized as input to analyze the effects of energy dissipation and recentering devices on the peak and residual drifts of self-centering piers. Finally, some near-fault pulse-like ground motion records are used for the further validation. It is shown that the shape parameters of flag-shaped hysteretic model representing a plump hysteresis loop can be set as follows: A =  n  = 1.0 and β = (- γ ) > 0. Compared with the stiffness of post-tensioned tendons, increasing the prestressing force of post-tensioned tendons can significantly reduce the peak and residual drifts. In addition, the equipment of energy dissipation devices is also beneficial to reduce the peak drift. However, note that a large prestressing force may jeopardize the rocking mechanism of self-centering piers, it is advised that large prestressing force should be avoided to protect this rocking mechanism.

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Automatic Detection and Repair Recommendation for Missing Checks

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Journal of Computer Science & Technology 2019年第5期34卷 972-992页

作者： Ling-Yun Situ Lin-Zhang Wang Yang Liu Bing Mao Xuan-Dong Li State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China Department of Computer Science and Technology Nanjing UniversityNanjing 210023China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore

Missing checks for untrusted inputs used in security-sensitive operations is one of the major causes of various vulnerabilities. Efficiently detecting and repairing missing checks are essential for prognosticating potential vulnerabilities and improving code reliability. We propose a systematic static analysis approach to detect missing checks for manipulable data used in security-sensitive operations of C/C++ programs and recommend repair references. First, customized securitysensitive operations are located by lightweight static analysis. Then, the assailability of sensitive data used in securitysensitive operations is determined via taint analysis. And, the existence and the risk degree of missing checks are assessed. Finally, the repair references for high-risk missing checks are recommended. We implemented the approach into an automated and cross-platform tool named Vanguard based on Clang/LLVM 3.6.0. Large-scale experimental evaluation on open-source projects has shown its effectiveness and efficiency. Furthermore, Vanguard has helped us uncover five known vulnerabilities and 12 new bugs.

关键词： static analysis missing check vulnerability detection repair recommendation

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Detail retention and enhancement for camouflaged object detection

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Neurocomputing 2025年 648卷

作者： Shangjing Chen Feng Xu Tao Zeng Xin Li Jiale Chen Xin Lyu College of Computer Science and Software Engineering Hohai University Nanjing 211100 China School of Computer Engineering Jiangsu Ocean University Lianyungang 222005 China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing 211100 China

The objective of camouflaged object detection is to segment objects that share similar visual attributes with their backgrounds. Existing methods leverage the consistency and variability of the object to pinpoint its location; however, when presented with samples exhibiting intricate edges, the model tends to overlook critical details. Toward this issue, we analyzed the reasons from the perspective of processing basic features and found that roughly compressing the feature channel could lead to the loss of fine features at the initial stage of the pipeline. Therefore, we introduce a multi-scale feature preprocessing approach named Soft Channel Compression prior to feature fusion, which retains key cues by enhancing the visibility of fine-grained features. We then utilize self-attention to fuse the results of multi-scale feature sampling, synthesizing contextual information between extended details and the main object. Furthermore, we propose the Hierarchical Receptive Field Complementarity module, using a divide-and-conquer strategy to enhance discriminative features with different scales in object details. This facilitates the integration of information across various ranges by employing a hierarchical manner to expand the receptive field, thereby achieving complementary information between local areas. Extensive experimental results on benchmark datasets demonstrate that the proposed method outperforms other state-of-the-art methods.

关键词： Camouflaged object detection Edge detail Hierarchical manner Multi-scale feature Regional information complementarity

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Frontiers of Computer Science 2019年第2期13卷 231-246页

作者： Min GAO Bin LING Linda YANG Junhao WEN Qingyu XIONG Shun LI Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education Chongqing 400044 China School of Software Engineering Chongqing University Chongqing 400044 China School of Engineering University of Portsmouth Portsmouth PO1 3 AH UK

Collaborative filtering (CF) is a technique commonly used for personalized recommendation and Web service quality-of-service (QoS) prediction. However, CF is vulnerable to shilling attackers who inject fake user profiles into the system. In this paper, we first present the shilling attack problem on CF-based QoS recommender systems for Web services. Then, a robust CF recommendation approach is proposed from a user similarity perspective to enhance the resistance of the recommender systems to the shilling attack. In the approach, the generally used similarity measures are analyzed, and the DegSim (the degree of similarities with top k neighbors) with those measures is selected for grouping and weighting the users. Then, the weights are used to calculate the service similarities/differences and predictions. We analyzed and evaluated our algorithms using WS-DREAM and Movielens datasets. The experimental results demonstrate that shilling attacks influence the prediction of QoS values, and our proposed features and algorithms achieve a higher degree of robustness against shilling attacks than the typical CF algorithms.

关键词： collaborative filtering service recommendation system robustness shilling attack

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Evidence-aware hierarchical interactive attention networks for explainable claim verification 29

Evidence-aware hierarchical interactive attention networks f...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Wu, Lianwei Rao, Yuan Yang, Xiong Wang, Wanzhen Nazir, Ambreen Lab of Social Intelligence and Complexity Data Processing School of Software Engineering Xi'an Jiaotong University China Shannxi Joint Key Laboratory for Artifact Intelligence Sub-Lab of Xi'an Jiaotong University China Research Institute of Xi'an Jiaotong University Shenzhen China

ISBN: (纸本)9780999241165

Exploring evidence from relevant articles to confirm the veracity of claims is a trend towards explainable claim verification. However, most strategies capture the top-k check-worthy articles or salient words as evidence, but this evidence is difficult to focus on the questionable parts of unverified claims. Besides, they utilize relevant articles indiscriminately, ignoring the source credibility of these articles, which may cause quiet a few unreliable articles to interfere with the assessment results. In this paper, we propose Evidence-aware Hierarchical Interactive Attention Networks (EHIAN) by considering the capture of evidence fragments and the fusion of source credibility to explore more credible evidence semantics discussing the questionable parts of claims for explainable claim verification. EHIAN first designs internal interaction layer (IIL) to strengthen deep interaction and matching between claims and relevant articles for obtaining key evidence fragments, and then proposes global inference layer (GIL) that fuses source features of articles and interacts globally with the average semantics of all articles and finally earns the more credible evidence semantics discussing the questionable parts of claims. Experiments on two datasets demonstrate that EHIAN not only achieves the state-of-the-art performance but also secures effective evidence to explain the results. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Semantics

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Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis

arXiv

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arXiv 2022年

作者： Zhong, Qihuang Ding, Liang Liu, Juhua Du, Bo Jin, Hua Tao, Dacheng The National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence School of Computer Science Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan China The Research Center for Graphic Communication Printing and Packaging Institute of Artificial Intelligence Wuhan University Wuhan China The JD Explore Academy *** Beijing China The Affiliated Hospital of Kunming University of Science and Technology Kunming China

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. To better comprehend long complicated sentences and obtain accurate aspect-specific information, linguistic and commonsense knowledge are generally required in this task. However, most current methods employ complicated and inefficient approaches to incorporate external knowledge, e.g., directly searching the graph nodes. Additionally, the complementarity between external knowledge and linguistic information has not been thoroughly studied. To this end, we propose a knowledge graph augmented network (KGAN), which aims to effectively incorporate external knowledge with explicitly syntactic and contextual information. In particular, KGAN captures the sentiment feature representations from multiple different perspectives, i.e., context-, syntax- and knowledge-based. First, KGAN learns the contextual and syntactic representations in parallel to fully extract the semantic features. Then, KGAN integrates the knowledge graphs into the embedding space, based on which the aspect-specific knowledge representations are further obtained via an attention mechanism. Last, we propose a hierarchical fusion module to complement these multi-view representations in a local-to-global manner. Extensive experiments on five popular ABSA benchmarks demonstrate the effectiveness and robustness of our KGAN. Notably, with the help of the pretrained model of RoBERTa, KGAN achieves a new record of state-of-the-art performance among all datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： Sentiment analysis

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On Pareto-frontier Approximate Computing for Many-core Systems

On Pareto-frontier Approximate Computing for Many-core Syste...

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intelligent Technology and Embedded Systems (ICITES), International Conference on

作者： Xinyue Hou Xiaohang Wang Maurizio Palesi Amit Kumar Singh Yingtao Jiang Mei Yang Letian Huang Junying Chen Key Laboratory of Big Data and Intelligent Robot (South China University of Technology) Ministry of Education School of Software Engineering South China University of Technology University of Catania Catania Italy School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom University of Nevada Las Vegas USA School of Electronic Science and Engineering University of Electronic Science and Technology of China China

Approximate computing is an emerging paradigm that aggressively improves performance or reduces energy consumption by sacrificing computation quality for error forgiving applications. Various approximate techniques, including loop truncation, approximate communication, etc. have been proposed. Previous works focus on optimization using only one approximation knob. However, we have observed that simultaneously optimizing with multiple approximation knobs leads to a large search space and is more likely to find better solutions. Therefore, in this paper, we first develop application models for performance, error, and power, followed by formulation of an optimization problem to maximize system performance under error and power constraints, using three approximation knobs, which are loop truncation, data dropping, and computational precision scaling. In order to solve the problem efficiently, a lightweight algorithm based on interior point algorithm is proposed. Experimental results show that, compared to state-of-the-art approximate approaches, the proposed scheme can reduce the execution time by as much as 33.1%. The overhead of the proposed method is low, making it a suitable approximate scheme for future many-core systems.

关键词： Energy consumption Power demand Embedded systems Computational modeling System performance Approximate computing Approximation algorithms

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Vulnerability Analysis through Interface-based Checker Design

Vulnerability Analysis through Interface-based Checker Desig...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Xiang Du Liangze Yin Peng Wu Liyuan Jia Wei Dong Key Laboratory Of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha China

ISBN: (数字)9781728189154

ISBN: (纸本)9781728189161

Checkers design is a main step for static analysis of different vulnerabilities. This paper focuses on static analysis on code property graph, which combines abstract syntax tree, control flow graph, and program dependence graph. Developing checkers on code property graph directly is usually complex and difficult. In this paper, we have analyzed a large number of checkers of different vulnerabilities, and extracted those most commonly used operations as a set of interfaces. We have implemented these interfaces and developed a set of vulnerability checkers based on them. The practical efficacy of these checkers are evaluated on the Linux kernel source code. Experimental results show that our proposed interfaces are strong enough to express most vulnerabilities and our implementation is effective for vulnerabilities detection.

关键词： Linux software algorithms Static analysis software quality Syntactics software reliability Kernel

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