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arXiv 2022年

作者： Liu, Zhe Huang, Yuekai Chen, Chunyang Hu, Jun Wang, Junjie Wang, Qing Institute of Software Chinese Academy of Sciences Beijing China Monash University Melbourne Australia University of Chinese Academy of Sciences Beijing China Laboratory for Internet Software Technologies Beijing China State Key Laboratory of Computer Sciences Beijing China Science & Technology on Integrated Information System Laboratory Beijing China

Mobile apps are indispensable for people’s daily life. Complementing with automated testing, manual testing is the last line of defence for app quality. However, the repeated actions and easily missing of functionalities make manual testing time-consuming and inefficient. Inspired by the game candy crush with flashy candies as hint moves for players, we propose an approach named NaviDroid for navigating testers via highlighted next operations for more effective and efficient testing. Within NaviDroid, we construct an enriched state transition graph with the triggering actions as the edges for two involved states. Based on it, we utilize the dynamic programming algorithm to plan the exploration path, and augment the GUI with visualized hints for testers to quickly explore untested activities and avoid duplicate explorations. The automated experiments demonstrate the high coverage and efficient path planning of NaviDroid and a user study further confirms its usefulness. It can help us develop more robust software that works in more mission-critical settings, not only by performing more thorough testing with the same effort that has been put in before, but also by integrating these techniques into different parts of development *** Codes software engineering (***), Human-Computer Interaction (***) © 2022, CC BY.

关键词： Quality assurance

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Analysis of identifiers in IoT platforms

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Digital Communications and Networks 2020年第3期6卷 333-340页

作者： Haris Aftab Komal Gilani JiEun Lee Lewis Nkenyereye SeungMyeong Jeong JaeSeung Song Software Engineering and Security(SES)Lab Department of Computer and Information SecuritySejong UniversitySeoul05006Republic of Korea IoT Convergence Platform Lab Korea Electronics Technologies InstituteSungnam-Si13509Republic of Korea

The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices *** need to identify those devices is the foremost important to perform any kind of *** organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification *** existing industrial identification mechanisms can also be used in the *** is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard *** unavailability of a unified IS method makes the inter-working among IoT platforms *** paper analyses and compares ISs used by several selected IoT *** work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.

关键词： Internet of things Identifiers Identification schemes IoT platforms IoT standards

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FINDGATE: Fine-grained Defect Prediction Based on a Heterogeneous Discrete Code Graph-guided Attention Transformer

FINDGATE: Fine-grained Defect Prediction Based on a Heteroge...

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

作者： Jiaxi Xu Ping Chen Banghu Yin Zhichang Huang Qiaochun Qiu China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou Guangdong China The Ministry of Industry and Information Technology Key Laboratory of Performance and Reliability Testing and Evaluation for Basic Software and Hardware Guangzhou Guangdong China College of System Engineering National University of Defense Technology Changsha Hunan China

Recognizing defects in source code through deep learning methods has become an important research subject for improving software quality. Although Transformer-based models such as CodeBERT have demonstrated impressive performance improvement in defect prediction tasks, models relying on single-structured input data, such as sequences, have limited ability to capture the code's structural features. Treating code simply as text overlooks essential information such as control dependencies, data dependencies, and syntactic structures inherent in the code. This paper proposes the Heterogeneous Discrete Code Graph (HDCG), which assigns structural information to code tokens from multiple perspectives. We also introduce an improved transformer model FINEGATE that leverages HDCG to guide self-attention. The experiments demonstrate that FINEGATE can effectively predict source code defects and perform fine-grained defect localization.

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Context-aware Bug Reproduction for Mobile Apps

Context-aware Bug Reproduction for Mobile Apps

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International Conference on software engineering (ICSE)

作者： Yuchao Huang Junjie Wang Zhe Liu Song Wang Chunyang Chen Mingyang Li Qing Wang Science and Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Intelligent Game Beijing China University of Chinese Academy of Sciences Beijing China Electrical Engineering and Computer Science York University Canada Monash University Melbourne Australia

Bug reports are vital for software maintenance that allow the developers being informed of the problems encountered in the software. Before bug fixing, developers need to reproduce the bugs which is an extremely time-consuming and tedious task, and it is highly expected to automate this process. However, it is challenging to do so considering the imprecise or incomplete natural language described in reproducing steps, and the missing or ambiguous single source of information in GUI components. In this paper, we propose a context-aware bug reproduction approach ScopeDroid which automatically reproduces crashes from textual bug reports for mobile apps. It first constructs a state transition graph (STG) and extracts the contextual information of components. We then design a multi-modal neural matching network to derive the fuzzy matching matrix between all candidate GUI events and reproducing steps. With the STG and matching information, it plans the exploration path for reproducing the bug, and enriches the initial STG iteratively. We evaluate the approach on 102 bug reports from 69 popular Android apps, and it successfully reproduces 63.7% of the crashes, outper-forming the state-of-the-art baselines by 32.6% and 38.3%. We also evaluate the usefulness and robustness of ScopeDroid with promising results. Furthermore, to train the neural matching network, we develop a heuristic-based automated training data generation method, which can potentially motivate and facilitate other activities as user interface operations.

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A Kind of new parallax algorithm based on symmetric continuous optimization 5

A Kind of new parallax algorithm based on symmetric continuo...

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2020 5th International Seminar on Computer Technology, Mechanical and Electrical engineering, ISCME 2020

作者： Jiang, Kaiwen Zhang, Degan Xu, Haixia Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin300410 China

With the fast development of 3D imaginations becomes more and more fascination, multi-view stereo based 3D reconstruction is a significant technique for those application. To facilitate the subsequent processing of 3D reconstruction and reduce the possibility of other algorithms falling into local optimal solutions, attempting to get better and faster performance, a new parallax calculation based on symmetric continuous optimization is proposed in this paper. The algorithm is proposed here will be tested respectively in the same data, in order to certificate the algorithm applied is better than traditional minimize El algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

arXiv

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arXiv 2024年

作者： Zhang, Yaning Wang, Tianyi Yu, Zitong Gao, Zan Shen, Linlin Chen, Shengyong Jinan250353 China Nanyang Technological University 50 Nanyang Ave Block N 4 639798 Singapore School of Computing and Information Technology Great Bay University Dongguan523000 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China Jinan250014 China The Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches mainly capture face forgery patterns using image modality, other modalities like fine-grained noises and texts are not fully explored, which limits the generalization capability of the model. In addition, most FFD methods tend to identify facial images generated by GAN, but struggle to detect unseen diffusion-synthesized ones. To address the limitations, we aim to leverage the cutting-edge foundation model, contrastive language-image pre-training (CLIP), to achieve generalizable diffusion face forgery detection (DFFD). In this paper, we propose a novel multi-modal fine-grained CLIP (MFCLIP) model, which mines comprehensive and fine-grained forgery traces across image-noise modalities via language-guided face forgery representation learning, to facilitate the advancement of DFFD. Specifically, we devise a fine-grained language encoder (FLE) that extracts fine global language features from hierarchical text prompts. We design a multi-modal vision encoder (MVE) to capture global image forgery embeddings as well as fine-grained noise forgery patterns extracted from the richest patch, and integrate them to mine general visual forgery traces. Moreover, we build an innovative plug-and-play sample pair attention (SPA) method to emphasize relevant negative pairs and suppress irrelevant ones, allowing cross-modality sample pairs to conduct more flexible alignment. Extensive experiments and visualizations show that our model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Alignment

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A compact patch coupler using cross-slots for 5G applications

A compact patch coupler using cross-slots for 5G application...

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Sciences and Techniques of Automatic Control and Computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Khadija Abouhssous Layla Wakrim Asmaa Zugari Alia Zakriti Department of Civil and Industrial Sciences and Technologies Laboratory of Science and Advanced Technology National School of Applied Sciences Abdelmalek Essadi University Tetouan Morocco Laboratory of Innovation in Management and Engineering for Business (LIMIE) Higher Institute of Engineering and Business (ISGA) Marrakech Morocco Information and Telecommunication System Laboratory FS Abdelmalek Essadi University Tetouan Morocco

A compact hybrid patch coupler operating at 3.5 GHz for fifth generation applications is presented. By introducing cross-slots with T-shaped heads on the edges, the proposed hybrid patch coupler’s overall size is reduced significantly. The proposed coupler offers a size reduction of 79% compared to the overall size occupied by a conventional reference design. Simulation results show a successful fit of the miniature coupler such that the reflection coefficient and the isolation values are −44.27 dB and −24.35 dB at 3.5 GHz. The insertion coefficient and coupling coefficient values are −3.18 dB and −3.88 dB for the same resonance frequency, with 30% fractional bandwidth (FBW) and 89° phase difference, showing that the cross-slot patch coupler is capable of diagonally coupling the input signal to its outputs at 3.5 GHz.

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Model-enhanced Vector Index

arXiv

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arXiv 2023年

作者： Zhang, Hailin Wang, Yujing Chen, Qi Chang, Ruiheng Zhang, Ting Miao, Ziming Hou, Yingyan Ding, Yang Miao, Xupeng Wang, Haonan Pang, Bochen Zhan, Yuefeng Sun, Hao Deng, Weiwei Zhang, Qi Yang, Fan Xie, Xing Yang, Mao Cui, Bin School of Computer Science Key Lab of High Confidence Software Technologies Peking University China Microsoft United States Aerospace Information Research Institute Key Laboratory of Target Cognition and Application Technology Chinese Academy of Sciences China Institute of Information Engineering Chinese Academy of Sciences China Carnegie Mellon University United States National University of Singapore Singapore National Engineering Laboratory for Big Data Analysis and Applications Peking University China

Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in document retrieval due to low latency and decent recall performance. Recent research indicates that deep retrieval solutions offer better model quality, but are hindered by unacceptable serving latency and the inability to support document updates. In this paper, we aim to enhance the vector index with endto- end deep generative models, leveraging the differentiable advantages of deep retrieval models while maintaining desirable serving efficiency. We propose Modelenhanced Vector Index (MEVI), a differentiable model-enhanced index empowered by a twin-tower representation model. MEVI leverages a Residual Quantization (RQ) codebook to bridge the sequence-to-sequence deep retrieval and embeddingbased models. To substantially reduce the inference time, instead of decoding the unique document ids in long sequential steps, we first generate some semantic virtual cluster ids of candidate documents in a small number of steps, and then leverage the well-adapted embedding vectors to further perform a fine-grained search for the relevant documents in the candidate virtual clusters. We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Are Halal Food Supply Chains Sustainable: A Review And Bibliometric Analysis

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Journal of Foodservice Business Research 2021年第5期24卷 554-595页

作者： Rejeb, Abderahman Rejeb, Karim Zailani, Suhaiza Department of Logistics and Forwarding Doctoral School of Regional Sciences and Business Administration Széchenyi István University Györ Hungary Department of Software Engineering Higher Institute of Computer Science El Manar Ariana Tunisia Department of Operations Management and Information System Faculty of Business and Accountancy University Malaya Kuala Lumpur Malaysia

Halal food supply chains (HFSCs) are increasingly characterized by fragmentation, complexity, and uncertainty. Halal food consumers are becoming more demanding for food quality and compliance with Islamic dietary law. As sustainability is a multidimensional concept that entails several aspects and interpretations, the objectives of HFSCs significantly overlap with the sustainable dimensions of the food ecosystem. The purpose of this study is to examine the inherent sustainable aspects and characteristics of HFSCs. Therefore, a systematic literature review and a bibliometric analysis were conducted to redress the lack of academic attention being given to the relationships of HFSCs with sustainability. Selected 74 papers were coded and analyzed according to the dimensions of sustainability, namely, the economic, social, and environmental dimensions. The review primarily attempts to provide answers to the following research question: What are the sustainable aspects of HFSCs? We provide a comprehensive analysis of the three critical components of sustainability, offering a broad and comprehensive picture of many critical issues in HFSCs. Finally, the contribution of the study, the scope of future research, and the limitations are highlighted in detail. © 2021 Taylor & Francis.

关键词： economic Halal Food Supply Chains social sustainability

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Modeling techno-economic multi-objectives of smart homes considering energy optimization and demand management

Science and Technology for Energy Transition (STET)

引用

Science and Technology for Energy Transition (STET) 2024年 79卷

作者： Khan, Mohammad Ahmar Kareem, A.K. Askar, Shavan Abduvalieva, Dilsora Roopashree, R. Prasad, K.D.V. Sharma, Aanchal Sharma, Abhishek Ghazaly, Nouby M. Mohmmedi, M. Department of Mis Dhofar University Salalah Oman Biomedical Engineering Department College of Engineering and Technologies Al-Mustaqbal University Babil Hillah51001 Iraq Erbil Polytechnic University Erbil Technical Engineering College Information System Engineering Department Erbil Iraq Department of Mathematics and Information Technologies Tashkent State Pedagogical University Bunyodkor Avenue 27 Tashkent100070 Uzbekistan Karnataka Bangalore India Kothur Mandal Mamidipally Mahabubnagar Telangana Hyderabad India Chandigarh Pharmacy College Chandigarh Group of Colleges Jhanjeri Punjab Mohali140307 India Department of Medicine National Institute of Medical Sciences Nims University Rajasthan Jaipur India Technical College Imam Ja'afar Al-Sadiq University Baghdad Iraq Mechanical Engineering Faculty of Engineering South Valley University Egypt Department of Electrical Engineering Islamic Azad University Branch of Central Tehran Tehran Iran

The research suggests an approach that prioritizes customer needs and aims to reduce energy expenses while safeguarding customer privacy. Furthermore, it is recommended that smart homes incorporate a home energy management system to optimize appliance energy consumption. Conversely, the introduction of demand-side management addresses the energy management challenges faced by smart households. The main goal of this approach is to decrease energy usage and electricity costs for customers. Moreover, it enhances user satisfaction while waiting at common intervals. The primary emphasis of this study is on a smart residence furnished with energy management technology and smart home gadgets capable of supplying electricity to the grid. These objectives are considered distinct aspects in the multi-objective optimization issue stemming from this approach. The study utilizes the grasshopper optimization algorithm (GOA) to optimize battery and home appliance scheduling in smart homes with flexible devices. The goal is to reduce the overall cost of microgrid systems through demand-side management implementation. This comparison highlights the superiority of the proposed method in optimizing energy consumption and reducing carbon emissions in a variety of scenarios. By achieving lower energy costs and carbon emissions while maintaining a comfortable indoor environment, the proposed method proves to be a highly effective and sustainable solution for energy management in buildings. These simulation results provide strong evidence of the methodâ ? ? s potential to significantly impact energy efficiency and environmental sustainability in real-world applications. Furthermore, the consistent minimization of the discomfort index showcases the methodâ ? ? s ability to prioritize occupant comfort while still achieving significant energy savings and emissions reductions. Overall, the comparison with other algorithms solidifies the effectiveness and practicality of the proposed method in

关键词： Smart homes

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