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

作者： Peng Wu Liangze Yin Xiang Du 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

With the development of open source software and open source community, there are more available codes on the Internet. And the open vulnerability information can be found on the Internet. In fact, using known vulnerabilities to calculate the similarity with the source code has been demonstrated a useful method to detect vulnerabilities. But the vulnerabilities often have many irrelevant codes, which may cause false positives and reduce the accuracy of vulnerability detection. Besides, the program code may have been patched. This also leads to false positives. We use code property graphs to extract source code and calculate the similarity between the vulnerable code and the source code to judge whether the software has vulnerabilities. By using the patched code, we can reduce the false positive. We use our approach on LibTIFF and Linux kernel. The experimental results show that the approach can effectively find vulnerabilities and reduce the false positive.

关键词： Linux software quality Feature extraction Internet software reliability Security Open source software

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Experimental verification of group non-membership in optical circuits

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Photonics Research 2021年第9期9卷 1745-1751页

作者： KAI SUN ZI-JIAN ZHANG FEI MENG BIN CHENG ZHU CAO JIN-SHI XU MAN-HONG YUNG CHUAN-FENG LI GUANG-CAN GUO CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Department of Physics Southern University of Science and TechnologyShenzhen 518055China Department of Computer Science The University of Hong KongPokfulamHong Kong SARChina Centre for Quantum Software and Information Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyNSW 2007Australia Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai 200237China Shenzhen Institute for Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China

The class quantum Merlin–Arthur(QMA),as the quantum analog of nondeterministic polynomial time,contains the decision problems whose YES instance can be verified efficiently with a quantum *** problem of deciding the group non-membership(GNM)of a group element is conjectured to be a member of *** works on the verification of GNM,which still lacks experimental demonstration,required a quantum circuit with O(n~5)group oracle ***,we provide an efficient way to verify GNM problems,in which each quantum circuit only contains O(1)group of oracle calls,and the number of qubits in each circuit is reduced by *** on this protocol,we then experimentally demonstrate the new verification process with a four-element group in an all-optical *** new protocol is validated experimentally by observing a significant completeness-soundness gap between the probabilities of accepting elements in and outside the *** work efficiently simplifies the verification of GNM and is helpful in constructing more quantum protocols based on the near-term quantum devices.

关键词： quantum element polynomial

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Verifying opacity of a modified PSTM 13

Verifying opacity of a modified PSTM

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13th International Symposium on Theoretical Aspects of software engineering, TASE 2019

作者： Fang, Yucheng Zhu, Huibiao Yin, Jiaqi Shanghai Key Laboratory of Trustworthy Computing School of Computer Science and Software Engineering East China Normal University China

ISBN: (纸本)9781728133423

software transactional memory (STM) provides programmers with a high-level programming abstraction for synchronization of parallel processes, allowing blocks of codes that execute in an interleaved manner to be treated as an atomic block. Python software Transactional Memory (PSTM) is an STM implementation in Python language. Its presentation fills a gap that Python lacks an applicable and reliable software transactional memory. PSTM satisfies the basic transaction properties, however it does not satisfy opacity, which defines conditions for serialising concurrent transaction. To alleviate this issue, we modify the PSTM implementation and present a new PSTM called PSTM-M. Based on PSTM-M, we verify opacity of this implementation. We present the formalization of opacity which is based on the history model of transaction. Further, we explain why PSTM does not satisfy opacity and present a modified PSTM called PSTM-M. Finally, we give a machine-checked proof for the opacity of PSTM-M based on the theorem prover Coq. © 2019 IEEE.

关键词： Python

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Gathering github oss requirements from q&a community: An empirical study

arXiv

引用

arXiv 2020年

作者： Huang, Hao Lu, Yao Mao, Xinjun Key Laboratory of Software Engineering for Complex Systems College of Computer National University of Defense Technology Changsha410073 China

ross-community collaboration can exploit the expertise and knowledges of crowds in different communities. Recently increasing users in open source software (OSS) community like GitHub attempt to gather software requirements from question and answer (Q&A) communities such as Stack Overflow (SO). In order to investigate this emerging cross-community collaboration phenomenon, the paper presents an exploratory study on cross-community requirements gathering of OSS projects in GitHub. We manually sample 3266 practice cases and quantitatively analyze the popularity of the phenomenon, the characteristics of the gathered requirements, and collaboration behaviors of cross-community. Some important findings are obtained: more than half of the requirements gathered from SO are enhancements and the majority of the gathered requirements are non-functional requirements. In addition, OSS developers can directly obtain related solutions and contributions of the gathered requirements from SO in the gathering process. Copyright © 2020, The Authors. All rights reserved.

关键词： Requirements engineering

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Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over Sequences

arXiv

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arXiv 2021年

作者： Qian, Chao Liu, Dan-Xuan Feng, Chao Tang, Ke State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China School of Computer Science and Technology University of Science and Technology of China Hefei230027 China Shenzhen Key Laboratory of Computational Intelligence Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Evolutionary algorithms (EAs) are general-purpose optimization algorithms, inspired by natural evolution. Recent theoretical studies have shown that EAs can achieve good approximation guarantees for solving the problem classes of submodular optimization, which have a wide range of applications, such as maximum coverage, sparse regression, influence maximization, document summarization and sensor placement, just to name a few. Though they have provided some theoretical explanation for the general-purpose nature of EAs, the considered submodular objective functions are defined only over sets or multisets. To complement this line of research, this paper studies the problem class of maximizing monotone submodular functions over sequences, where the objective function depends on the order of items. We prove that for each kind of previously studied monotone submodular objective functions over sequences, i.e., prefix monotone submodular functions, weakly monotone and strongly submodular functions, and DAG monotone submodular functions, a simple multi-objective EA, i.e., GSEMO, can always reach or improve the best known approximation guarantee after running polynomial time in expectation. Note that these best-known approximation guarantees can be obtained only by different greedy-style algorithms before. Empirical studies on various applications, e.g., accomplishing tasks, maximizing information gain, search- and-tracking and recommender systems, show the excellent performance of the GSEMO. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational complexity

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A Novel Image Classification Model Jointing Attention and ResNet for Scratch

A Novel Image Classification Model Jointing Attention and Re...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Shuaifei Zhao Lichen Qiu Peng Qi Yan Sun Beijing Key Laboratory of Intelligent Telecomm. Software and Multimedia Beijing University of Posts and Telecomm Beijing China Dongyuqiao Primary School Shandong China

ISBN: (数字)9781728131290

ISBN: (纸本)9781728131306

In recent years, Scratch has been widely used in helping teenagers learn to program. Before programming with Scratch, users usually need to select a background image with a proper style to set the environment of role activities and emotional tone of works. In order to make the image styles rich and diverse, users can use the fast neural style transfer method to generate the image. However, when users use this method, they are usually puzzled with the optional styles, which makes it a common phenomenon that the contents of transformed images do not match the chosen styles. To resolve this problem, we design a novel image classification model to help recognize the scene of the image, which can guide users to select optional styles for the image. First, we improve the residual network with two attention modules and reconstruct the residual module structure, which improves the accuracy of model classification. Then, we propose a self-adjusting learning rate module, which can accelerate the convergence of the model and reduce fluctuations of the loss function. The experiment results show that our model outperforms other classic image classification methods in classifying the background image of Scratch. The classification accuracy on the testset reaches 98%.

关键词： Training Feature extraction Computational modeling Programming profession Machine learning Neural networks

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An Analysis of Factors Influencing the Demand for Smart Energy in Yunnan Province Based on Pearson Correlation Coefficient

An Analysis of Factors Influencing the Demand for Smart Ener...

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Sustainable Power and Energy Conference (iSPEC)

作者： Min Cao Xiaoyi Long Tianwen Feng Siyang Liu Na Zhao Hai Lu Electric Power Research Institute of Yunnan Power Grid Key Laboratory of CSG for Electric Po wer Measurement Kunming China School of Computer Science Wuhan University Wuhan China Key Laboratory in Software Engineering of Yunnan Province School of Software Yunnan University Kunming China Electric Power Research Institute of Yunnan Power Grid Key Laboratory in Software Engineering of Yunnan Province School of Software Yunnan Kunming China Electric Power Research Institute of Yunnan Power Grid Kunming China

ISBN: (数字)9781728191645

ISBN: (纸本)9781728191652

The current energy market is undergoing a digital transformation. The deep integration of energy and technology is one of the core concepts of smart energy, and also the internationally recognized development focus. This paper analyzes the data of energy production and consumption in Yunnan Province. By calculating Pearson correlation coefficients between power consumption data and different indicators, it is found that the positive correlation between power consumption and the added value of the second industry is the largest. At the same time, through the analysis of the problems and challenges of energy industry in Yunnan Province, this paper demonstrates the significance of developing smart energy in Yunnan Province.

关键词： Industries Correlation coefficient Power demand Correlation Digital transformation Conferences Production

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Value-driven Cache Replacement Strategy in Mobile Edge Computing

Value-driven Cache Replacement Strategy in Mobile Edge Compu...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Hua Wei Hong Luo Yan Sun Mohammad S. Obaidat Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Beijing University of Science and Technology Beijing China

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

The mobile edge computing greatly reduces the transmission delay by offloading computing job to the base station, which is closer to the user. It solves the problem of high delay in cloud computing. Since the edge server has limited resources, improving the efficiency of computation offloading becomes a problem that needs to be addressed. Considering the data is reusable, it is a feasible solution to use the cache to improve the efficiency of computation offloading. In order to make the cache better serve the computation offloading process, we must design a reasonable cache replacement strategy. The traditional cache replacement strategy only considers the cache hit ratio, but ignores the cache value. It is not applicable to the edge computing process. In this paper, a new cache replacement strategy is proposed for the cache replacement problem in mobile edge computing, which is more suitable for computation offloading process. First, we define the cache value based on the priority of computing job. Then, we define the problem of maximizing the cache value in mobile edge computing as a multiobjective optimization problem. Finally, in order to find a suitable Pareto solution, we propose a cache replacement strategy based on the ideal point method. The experimental results show that the proposed algorithm results are significantly better than the existing competitive cache replacement methods.

关键词： Conferences Delays Computational efficiency Servers Global communication Optimization Edge computing

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ReGO: Reference-Guided Outpainting for Scenery Image

arXiv

引用

arXiv 2021年

作者： Wang, Yaxiong Wei, Yunchao Qian, Xueming Zhu, Li Yang, Yi The School of Software Engineering Xi’an Jiaotong University Xi'An710049 China Institute of Information Science Beijing Jiaotong University Beijing100000 China The Key Laboratory for Intelligent Networks and Network Security Ministry of Education Xi’an Jiaotong University Xi'An710049 China The SMILES Laboratory Xi’an Jiaotong University Xi'An710049 China Zhibian Technology Co. Ltd. Taizhou317000 China The School of Software Xi’an Jiaotong University Xi'An710049 China School of Computer Science and Technology Zhejiang University Hangzhou310000 China

We aim to tackle the challenging yet practical scenery image outpainting task in this work. Recently, generative adversarial learning has significantly advanced the image outpainting by producing semantic consistent content for the given image. However, the existing methods always suffer from the blurry texture and the artifacts of the generative part, making the overall outpainting results lack authenticity. To overcome the weakness, this work investigates a principle way to synthesize texture-rich results by borrowing pixels from its neighbors (i.e. , reference images), named Reference-Guided Outpainting (ReGO). Particularly, the ReGO designs an Adaptive Content Selection (ACS) module to transfer the pixel of reference images for texture compensating of the target one. To prevent the style of the generated part from being affected by the reference images, a style ranking loss is further proposed to augment the ReGO to synthesize style-consistent results. Extensive experiments on two sceneary benchmarks, NS6K [3], NS8K [9] and SUN Attribute [25], well demonstrate the effectiveness of our ReGO. Our code is available at https://***/wangyxxjtu/ReGOPytorch. © 2021, CC BY.

关键词： Textures

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Stock investment selection via time series subpatterns and multi-relationship fusion

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Pattern Recognition 2026年 169卷

作者： Yandi Shi Jing Chi Suochao Yi Caiming Zhang School of Computing and Artificial Intelligence Shandong University of Finance and Economics Jinan 250014 Shandong China Shandong Key Laboratory of Lightweight Intelligent Computing and Visualization for Digital Economy Jinan 250014 Shandong China School of Software Shandong University Jinan 250101 Shandong China

Due to the non-stationary dynamics and complex interrelationships in the stock market, stock investment selection remains a critical and challenging task in the fintech field. We propose a novel stock investment selection framework based on time series subpatterns and multi-relationship fusion. First, we propose a novel stock time-series subpattern representation that effectively captures local temporal patterns, enabling precise characterization of stock-specific features. We further learn the temporal dependencies among subpatterns to reveal implicit pattern changes in each stock’s historical data. Second, unlike traditional methods that learn stock correlation coefficients and fuse them to obtain stock features, we leverage the Transformer Encoder’s capability to capture inherent relationships between data, enabling the extraction of implicit short-term relationship between subpatterns of different stocks and thus directly obtaining features influenced by short-term inter-stock relationship. Third, we fuse the short-term and long-term stock relationships to obtain a fused relationship that influences stock trend changes. This multi-relationship fusion reflects the complex synchronous variation patterns between stocks and facilitates information exchange between long-term and short-term relationships, thereby uncovering the latent connections between these two types of relationships. Finally, we combine the temporal dependencies of stock subpatterns with the fused relationship to predict stock trends. Experimental results on three datasets demonstrate that the proposed method outperforms the state-of-the-art methods.

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