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Out of sight, out of mind: a distance-aware forgetting strategy for adaptive random testing

Science China(Information Sciences) 2017年第9期60卷 78-98页

作者： Chengying MAO Tsong Yueh CHEN Fei-Ching KUO school of software and Communication Engineering Jiangxi University of Finance and Economics Department of computer Science and software Engineering Swinburne University of Technology

Adaptive random testing(ART) achieves better failure-detection effectiveness than random testing by increasing the diversity of test cases. However, the intention of ensuring even spread of test cases inevitably causes an overhead problem. Although two basic forgetting strategies(i.e. random forgetting and consecutive retention) were proposed to reduce the computation cost of ART, they only considered the temporal distribution of test cases. In the paper, we presented a distance-aware forgetting strategy for the fixed size candidate set version of ART(DF-FSCS), in which the spatial distribution of test cases is taken into consideration. For a given candidate, the test cases out of its "sight" are ignored to reduce the distance computation cost. At the same time, the dynamic adjustment for partitioning and the second-round forgetting are adopted to ensure the linear complexity of DF-FSCS algorithm. Both simulation analysis and empirical study are employed to investigate the efficiency and effectiveness of DF-FSCS. The experimental results show that DF-FSCS significantly outperforms the classical ART algorithm FSCS-ART in efficiency, and has comparable failure-detection effectiveness. Compared with two basic forgetting methods, DF-FSCS is better in both efficiency and effectiveness. In contrast with a typical linear-time ART algorithm RBCVT-Fast, our algorithm requires less computational overhead and exhibits the similar failure-detection capability. In addition, DF-FSCS has more reliable performance than RBCVT-Fast in detecting failures for the programs with high-dimensional input domain.

关键词： adaptive random testing software testing test cases computational overhead diversity

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An efficient deterministic secure quantum communication scheme based on cluster states and identity authentication

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Chinese Physics B 2009年第10期18卷 4105-4109页

作者：刘文杰陈汉武马廷淮李志强刘志昊胡文博 school of computer Science and Engineering Southeast University school of computer and software Nanjing University of Information Science and Technology College of Information Engineering Yangzhou University

A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit two bits of classical information per cluster state, and its efficiency of the quantum communication is 1/3, which is approximately 1.67 times that of the previous protocol presented by Wang et al [Chin. Phys. Lett. 23 （2006） 2658]. Security analysis shows the present scheme is secure against intercept-resend attack and the impersonator＇s attack. Furthermore, it is more economic with present-day techniques and easily processed by a one-way quantum computer.

关键词： deterministic secure quantum communication cluster state identity authentication

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PSP-Finder:A Defect Detection Method Based on Mining Correlations from Function Call Paths

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Chinese Journal of Electronics 2018年第4期27卷 776-782页

作者： CUI Zhanqi CHEN Xiang MU Yongmin PAN Minxue WANG Rongcun computer school Beijing Information Science and Technology University Sate Key Laboratory for Novel software Technology Nanjing University school of computer Science and Technology Nantong University school of computer Science and Technology China University of Mining and Technology

Large scale programs usually imply many programming rules, which are missing from the specification documents. However, if programmers violate these rules in the process of programming, it is possible to introduce software defects. Previous works on mining function call correlation patterns only use structural information of the program, while control flow, data flow or other semantic information of the program are not exploited in those approaches. As a result, the defect detecting ability is restricted and high false rate is caused. This paper proposes a defect detection method based on mining function call association rules from program paths, which can be provided by simple static analysis. Then, the programs are automatically checked against the function call association rules for detecting suspicious defects. Based on this approach,experiments are carried out on a group of open source projects. The experiment results show that this approach can improve the capability of detecting defects and find more bugs related to program execution path. In addition,the false positive function call patterns and the overhead for manually validating suspicious defects are reduced.

关键词： Function call graphs Function call paths Mining association rules Defect detection

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Reinforcement learning based energy efficient robot relay for unmanned aerial vehicles against smart jamming

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Science China(Information Sciences) 2022年第1期65卷 234-246页

作者： Xiaozhen LU Jingfang JIE Zihan LIN Liang XIAO Jin LI Yanyong ZHANG Department of Information and Communication Engineering Xiamen University school of computer Science and Educational software Guangzhou University school of computer Science and Technology University of Science and Technology of China

Unmanned aerial vehicles(UAVs) with limited energy resources, severe path loss, and shadowing to the ground base stations are vulnerable to smart jammers that aim to degrade the UAV communication performance and exhaust the UAV energy. The UAV anti-jamming communication performance, such as the outage probability, degrades if the robot relay is not aware of the jamming policies and the UAV network topology. In this paper, we propose a robot relay scheme for UAVs against smart jamming, which combines reinforcement learning with a function approximation approach named tile coding, to jointly optimize the robot moving distance and relay power with the unknown jamming channel states and locations. The robot mobility and relay policy are chosen based on the received jamming power, the robot received signal quality,location and energy consumption, and the bit error rate of the UAV messages. We also present a deep reinforcement learning version for the robot with sufficient computing resources. It uses three deep neural networks to choose the robot mobility and relay policy with reduced sample complexity, so as to avoid exploring dangerous policies that lead to the high outage probability of the UAV messages. The network architecture of the three networks is designed with fully connected layers instead of convolutional layers to reduce the computational complexity, which is analyzed by theoretical analyses. We provide the performance bound of the proposed schemes in terms of the bit error rate, robot energy consumption and utility based on a game-theoretic study. Simulation results show that the performance of our proposed relay schemes,including the bit error rate, the outage probability, and the robot energy consumption outperforms the existing schemes.

关键词： unmanned aerial vehicles relay jamming game theory reinforcement learning

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Deep learning for code generation: a survey

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Science China(Information Sciences) 2024年第9期67卷 5-40页

作者： Huangzhao ZHANG Kechi ZHANG Zhuo LI Jia LI Jia LI Yongmin LI Yunfei ZHAO Yuqi ZHU Fang LIU Ge LI Zhi JIN Key Lab of High Confidence software Technologies (Peking University) Ministry of Education school of computer Science Peking University school of computer Science and Engineering Beihang University

In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutions to deep learning-based code generation. In this survey, we generally formalize the pipeline and procedure of code generation and categorize existing solutions according to taxonomy from perspectives of architecture, model-agnostic enhancing strategy, metrics, and tasks. In addition, we outline the challenges faced by current dominant large models and list several plausible directions for future research. We hope that this survey may provide handy guidance to understanding, utilizing, and developing deep learning-based code-generation techniques for researchers and practitioners.

关键词： code generation automated software engineering deep learning large model artificial intelligence

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Dual-domain and Multiscale Fusion Deep Neural Network for PPG Biometric Recognition

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Machine Intelligence Research 2023年第5期20卷 707-715页

作者： Chun-Ying Liu Gong-Ping Yang Yu-Wen Huang Fu-Xian Huang school of computer Heze UniversityHeze 274015China school of software Shandong UniversityJinan 250101China

Photoplethysmography(PPG)biometrics have received considerable *** deep learning has achieved good performance for PPG biometrics,several challenges remain open:1)How to effectively extract the feature fusion representation from time and frequency PPG signals.2)How to effectively capture a series of PPG signal transition information.3)How to extract timevarying information from one-dimensional time-frequency sequential *** address these challenges,we propose a dual-domain and multiscale fusion deep neural network(DMFDNN)for PPG biometric *** DMFDNN is mainly composed of a two-branch deep learning framework for PPG biometrics,which can learn the time-varying and multiscale discriminative features from the time and frequency ***,we design a multiscale extraction module to capture transition information,which consists of multiple convolution layers with different receptive fields for capturing multiscale transition *** addition,the dual-domain attention module is proposed to strengthen the domain of greater contributions from time-domain and frequency-domain data for PPG *** on the four datasets demonstrate that DMFDNN outperforms the state-of-the-art methods for PPG biometrics.

关键词： Photoplethysmography(PPG)signal biometric recognition multiple scale deep neural network dual-domain attention.

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Detection of semantically similar code

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Frontiers of computer Science 2014年第6期8卷 996-1011页

作者： Tiantian WANG Kechao WANG Xiaohong SU Peijun MA school of computer Science and Technology Harbin Institute of Technology Harbin 150001 China school of software Harbin University Harbin 150086 China

The traditional similar code detection approaches are limited in detecting semantically similar codes, impeding their applications in practice. In this paper, we have improved the traditional metrics-based approach as well as the graph- based approach and presented a metrics-based and graph- based combined approach. First, source codes are represented as augmented system dependence graphs. Then, metrics- based candidate similar code extraction is performed to filter out most of the dissimilar code pairs so as to lower the computational complexity. After that, code normalization is performed on the candidate similar codes to remove code variations so as to detect similar code at the semantic level. Finally, program matching is performed on the normalized control dependence trees to output semantically similar codes. Experiment results show that our approach can detect similar codes with code variations, and it can be applied to large software.

关键词： similar code detection system dependence graph code normalization semantically equivalent

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Splitting touching cells based on concave-point and improved watershed algorithms

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Frontiers of computer Science 2014年第1期8卷 156-162页

作者： Hong SONG Qingjie ZHAO Yinghong LIU school of software Beijing Institute of Technology Beijing 100081 China school of computer Science Beijing Institute of Technology Beijing 100081 China

Splitting touching cells is important for medi- cal image processing and analysis system. In this paper, a novel strategy is proposed to separate ellipse-like or circle- like touching cells in which different algorithms are used ac- cording to the concave-point cases of touching domains. In the strategy, a concave-point extraction and contour segmen- tation methods for cells in series and in parallel are used for the images with distinct concave points, and an improved watershed algorithm with multi-scale gradient and distance transformation is adopted for the images with un-distinct or complex concave points. In order to visualize each whole cell, ellipse fitting is used to process the segments. Experimental results show that, for the cell images with distinct concave points, both of the two algorithms can achieve good separat- ing results, but the concave-point based algorithm is more ef- ficient. However, for the cell images with unobvious or com- plex concave points, the improved watershed based algorithm can give satisfying segmenting results.

关键词： touching cells splitting concave points water-shed ellipse fitting

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Accelerating MUS enumeration by inconsistency graph partitioning

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Science China(Information Sciences) 2019年第11期62卷 70-80页

作者： Jie LUO Shaofan LIU State Key Laboratory of software Development Environment School of Computer Science and EngineeringBeihang University

The problem of finding minimal unsatisfiable subsets(MUSes) has been studied frequently because of its theoretical importance and wide range of applications in domains such as electronic design automation, software, and integrated circuit verification. In this paper, a method for accelerating the enumeration of MUSes based on inconsistency graph partitioning is proposed. First, an inconsistency graph of a set of clauses is constructed by extracting the inconsistency relations between literals of different clauses. In this paper, we show that by partitioning the inconsistency graph into small connected components through a vertex cut, the enumeration of MUSes in different components becomes independent and it is possible to compute them separately. Moreover, the MUSes of the original clause set can be constructed by merging the unit clauses in the MUSes of these connected components back into the clauses in the vertex cut. Experiments show that by integrating the acceleration method into the MARCO MUSes enumerator, there is a 2–3 times improvement in the average runtime of solved instances for randomly generated benchmarks. By integrating the acceleration method into itself as an MUS enumerator, there is another 3–4 times improvement when compared with the accelerated MARCO.

关键词： minimal unsatisfiable subsets inconsistency graph graph partition SAT UNSAT

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Towards Connecting Discrete Mathematics and software Engineering

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Tsinghua Science and Technology 2020年第3期25卷 325-335页

作者： Tun Li Wanwei Liu Juan Chen Xiaoguang Mao Xinjun Mao the school of computer National University of Defense Technology and are also with Laboratory of Software Engineering for Complex Systems

To enhance training in software development,we argue that students of software engineering should be exposed to software development activities early in the *** entails meeting the challenge of engaging students in software development before they take the software engineering *** this paper,we propose a method to connect courses in the software engineering curriculum by setting comprehensive development projects to students in prerequisite courses for software *** the Discrete Mathematics(DM)course as an example,we describe the implementation of the proposed method and teaching practices using several practical and comprehensive projects derived from topics in discrete *** descriptions of the sample projects,their application,and training results are *** and lessons learned from applying these practices show that it is a promising way to connect courses in the software engineering curriculum.

关键词： Discrete Mathematics(DM) software engineering proof checker database management system symbolic execution engine

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