RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 30

How does working from home affect developer productivity? — A case study of Baidu during the COVID-19 pandemic
Bao, Lingfeng; Li, Tao; Xia, Xin; Zhu, Kaiyu; Li, Hui; Yang, Xiaohu
Sci China Inf Sci, 2022, 65(4): 142102
Keywords: working from home; developer productivity
Cite as: Bao L F, Li T, Xia X, et al. How does working from home affect developer productivity? — A case study of Baidu during the COVID-19 pandemic. Sci China Inf Sci, 2022, 65(4): 142102, doi: 10.1007/s11432-020-3278-4

LETTER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 5

Teegraph: trusted execution environment and directed acyclic graph-based consensus algorithm for IoT blockchains
Fu, Xiang; Wang, Huaimin; Shi, Peichang; Ma, Xingkong; Zhang, Xunhui
Sci China Inf Sci, 2022, 65(3): 139104
Keywords: blockchain; dag; byzantine fault-tolerant; consensus algorithm; tee
Cite as: Fu X, Wang H M, Shi P C, et al. Teegraph: trusted execution environment and directed acyclic graph-based consensus algorithm for IoT blockchains. Sci China Inf Sci, 2022, 65(3): 139104, doi: 10.1007/s11432-019-1516-3

PERSPECTIVE Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 4

Toward actionable testing of deep learning models
Xiong, Yingfei; Tian, Yongqiang; Liu, Yepang; Cheung, Shing-Chi
Sci China Inf Sci, 2023, 66(7): 176101
Keywords: Deep Learnin; Testing; Bug Fixing; Machine Translation; Image Classification; Numeric Bugs
Cite as: Xiong Y F, Tin Y Q, Liu Y P, et al. Toward actionable testing of deep learning models. Sci China Inf Sci, 2023, 66(7): 176101, doi: 10.1007/s11432-022-3580-5

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 4

Cluster-preserving sampling algorithm for large-scale graphs
Zhang, Jianpeng; Chen, Hongchang; Yu, Dingjiu; Pei, Yulong; Deng, Yingjun
Sci China Inf Sci, 2023, 66(1): 112103
Keywords: graph sampling; clustering structure; top-leader nodes; expansion strategies; large-scale graphs
Cite as: Zhang J P, Chen H C, Yu D J, et al. Cluster-preserving sampling algorithm for large-scale graphs. Sci China Inf Sci, 2023, 66(1): 112103, doi: 10.1007/s11432-021-3370-4

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 4

A theoretic framework of bidirectional transformation between systems and models
He, Xiao; Hu, Zhenjiang; Meng, Na
Sci China Inf Sci, 2022, 65(10): 202103
Keywords: bidirectional transformation; system-model synchronization; change propagation; model-driven engineering; system edit
Cite as: He X, Hu Z J, Meng N. A theoretic framework of bidirectional transformation between systems and models. Sci China Inf Sci, 2022, 65(10): 202103, doi: 10.1007/s11432-020-3276-5

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 3

ArgusDroid: detecting Android malware variants by mining permission-API knowledge graph
Bai, Yude; Chen, Sen; Xing, Zhenchang; Li, Xiaohong
Sci China Inf Sci, 2023, 66(9): 192101
Keywords: malicious behavior; Android document; knowledge graph; malware family variant; machine learning
Cite as: Bai Y D, Chen S, Xing Z C, et al. ArgusDroid: detecting Android malware variants by mining permission-API knowledge graph. Sci China Inf Sci, 2023, 66(9): 192101, doi: 10.1007/s11432-021-3414-7

From CAS & CAE Members
REVIEW Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 2

Categorizing methods for integrating machine learning with executable specifications
Harel, David; Yerushalmi, Raz; Marron, Assaf; Elyasaf, Achiya
Sci China Inf Sci, 2024, 67(1): 111101
Keywords: machine learning; artificial intelligence; grey box learning; domain knowledge; rules; behavioral programming; deep reinforcement learning; survey
Cite as: Harel D, Yerushalmi R, Marron A, et al. Categorizing methods for integrating machine learning with executable specifications. Sci China Inf Sci, 2024, 67(1): 111101, doi: 10.1007/s11432-022-3826-6

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 2

BATON: symphony of random testing and concolic testing through machine learning and taint analysis
Chen, Bihuan; Liu, Yang; Peng, Xin; Wu, Yijian; Qin, Shengchao
Sci China Inf Sci, 2023, 66(3): 132101
Keywords: system testing; random testing; concolic testing
Cite as: Chen B H, Liu Y, Peng X, et al. BATON: symphony of random testing and concolic testing through machine learning and taint analysis. Sci China Inf Sci, 2023, 66(3): 132101, doi: 10.1007/s11432-020-3403-2

RESEARCH PAPER Supplementary Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 2

Context-aware API recommendation using tensor factorization
Zhou, Yu; Chen, Chen; Wang, Yongchao; Han, Tingting; Chen, Taolue
Sci China Inf Sci, 2023, 66(2): 122101
Keywords: API recommendation; tensor factorization; context awareness; word embedding; software development intelligent
Cite as: Zhou Y, Chen C, Wang Y C, et al. Context-aware API recommendation using tensor factorization. Sci China Inf Sci, 2023, 66(2): 122101, doi: 10.1007/s11432-021-3529-9

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 2

LPW: an efficient data-aware cache replacement strategy for Apache Spark
Li, Hui; Ji, Shuping; Zhong, Hua; Wang, Wei; Xu, Lijie; Tang, Zhen; Wei, Jun; Huang, Tao
Sci China Inf Sci, 2023, 66(1): 112104
Keywords: Spark; memory; cache replacement; least partition weight; data-aware
Cite as: Li H, Ji S P, Zhong H, et al. LPW: an efficient data-aware cache replacement strategy for Apache Spark. Sci China Inf Sci, 2023, 66(1): 112104, doi: 10.1007/s11432-021-3406-5

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 2

Towards characterizing bug fixes through dependency-level changes in Apache Java open source projects
Cui, Di; Fan, Lingling; Chen, Sen; Cai, Yuanfang; Zheng, Qinghua; Liu, Yang; Liu, Ting
Sci China Inf Sci, 2022, 65(7): 172101
Keywords: empirical software engineering; software maintenance; software evolution; software architecture; software design
Cite as: Cui D, Fan L L, Chen S, et al. Towards characterizing bug fixes through dependency-level changes in Apache Java open source projects. Sci China Inf Sci, 2022, 65(7): 172101, doi: 10.1007/s11432-020-3317-2

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 1

Deep learning-based open API recommendation for Mashup development
Wang, Ye; Chen, Junwu; Huang, Qiao; Xia, Xin; Jiang, Bo
Sci China Inf Sci, 2023, 66(7): 172102
Keywords: Mashup development; open API recommendation; deep learning; neural network; service discovery
Cite as: Wang Y, Chen J W, Huang Q, et al. Deep learning-based open API recommendation for Mashup development. Sci China Inf Sci, 2023, 66(7): 172102, doi: 10.1007/s11432-021-3531-0

LETTER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 1

A software-defined MAPE-K architecture for unmanned systems
Jiang, Mingyue; Zheng, Libin; Ding, Zuohua; Jin, Zhi
Sci China Inf Sci, 2023, 66(5): 159101
Keywords: software-defined architecture; unmanned systems; MAPE-K; metamodel; resource management
Cite as: Jiang M Y, Zheng L B, Ding Z H, et al. A software-defined MAPE-K architecture for unmanned systems. Sci China Inf Sci, 2023, 66(5): 159101, doi: 10.1007/s11432-020-3213-2

LETTER Supplementary Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 1

Automated regression unit test generation for program merges
Ji, Tao; Chen, Liqian; Mao, Xiaoguang; Yi, Xin; Jiang, Jiahong
Sci China Inf Sci, 2022, 65(9): 199103
Keywords: regression testing; unit test generation; test oracles; program merges; merge conflicts
Cite as: Ji T, Chen L Q, Mao X G, et al. Automated regression unit test generation for program merges. Sci China Inf Sci, 2022, 65(9): 199103, doi: 10.1007/s11432-019-3020-4

LETTER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 1

HAF: a hybrid annotation framework based on expert knowledge and learning technique
Li, Zhixing; Yu, Yue; Wang, Tao; Yin, Gang; Mao, Xinjun; Wang, Huaimin
Sci China Inf Sci, 2022, 65(1): 119105
Keywords: hybrid annotation framework; data annotation; expert knowledge; learning technique; labeled dataset
Cite as: Li Z X, Yu Y, Wang T, et al. HAF: a hybrid annotation framework based on expert knowledge and learning technique. Sci China Inf Sci, 2022, 65(1): 119105, doi: 10.1007/s11432-019-9891-5

NEWS & VIEWS Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 1

XiUOS: an open-source ubiquitous operating system for industrial Internet of Things
Cao, Donggang; Xue, Dongliang; Ma, Zhiyi; Mei, Hong
Sci China Inf Sci, 2022, 65(1): 117101
Keywords: ubiquitous operating system; industrial internet of things; intelligent manufacturing; cps; hcps
Cite as: Cao D G, Xue D L, Ma Z Y, et al. XiUOS: an open-source ubiquitous operating system for industrial Internet of Things. Sci China Inf Sci, 2022, 65(1): 117101, doi: 10.1007/s11432-021-3294-y

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

An efficient schedulability analysis based on worst-case interference time for real-time systems
Liu, Hongbiao; Yang, Mengfei; Qiao, Lei; Chen, Xi; Gong, Jian
Sci China Inf Sci, 2024, 67(9): 192103
Keywords: five-tuple real-time task model; real-time system; spacecraft; Internet of Things; exact schedulability analysis; worst-case interference time
Cite as: Liu H B, Yang M F, Qiao L, et al. An efficient schedulability analysis based on worst-case interference time for real-time systems. Sci China Inf Sci, 2024, 67(9): 192103, doi: 10.1007/s11432-022-3891-4

REVIEW Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

Deep learning for code generation: a survey
Zhang, Huangzhao; Zhang, Kechi; Li, Zhuo; Li, Jia; Li, Yongmin; Zhao, Yunfei; Zhu, Yuqi; Liu, Fang; Li, Ge; Jin, Zhi
Sci China Inf Sci, 2024, 67(9): 191101
Keywords: code generation; automated software engineering; deep learning; large model; artificial intelligence
Cite as: Zhang H Z, Zhang K C, Li Z, et al. Deep learning for code generation: a survey. Sci China Inf Sci, 2024, 67(9): 191101, doi: 10.1007/s11432-023-3956-3

MOOP Video Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

Do community responses influence OSS contributor retention? A survival analysis
Wang, Zhe; Li, Zhixing; Yu, Yue
Sci China Inf Sci, 2024, 67(8): 184101
Keywords: open source software; open source community; community response; contributor retention; survival analysis
Cite as: Wang Z, Li Z X, Yu Y. Do community responses influence OSS contributor retention? A survival analysis. Sci China Inf Sci, 2024, 67(8): 184101, doi: 10.1007/s11432-024-4090-0

LETTER Supplementary Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

Improving actionable warning identification via the refined warning-inducing context representation
Ge, Xiuting; Fang, Chunrong; Li, Xuanye; Zhang, Quanjun; Liu, Jia; Zhao, Zhihong; Chen, Zhenyu
Sci China Inf Sci, 2024, 67(5): 159101
Keywords: Actionable warning identification; Warning representation; Program slicing; Static analysis; Machine learning
Cite as: Ge X T, Fang C R, Li X Y, et al. Improving actionable warning identification via the refined warning-inducing context representation. Sci China Inf Sci, 2024, 67(5): 159101, doi: 10.1007/s11432-023-3975-6

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

What can we learn from quality assurance badges in open-source software?
Li, Feng; Lou, Yiling; Tan, Xin; Chen, Zhenpeng; Dong, Jinhao; Li, Yang; Wang, Xuanzhi; Hao, Dan; Zhang, Lu
Sci China Inf Sci, 2024, 67(4): 142103
Keywords: quality assurance; badge; open-source software; code quality; empirical study
Cite as: Li F, Lou Y L, Tan X, et al. What can we learn from quality assurance badges in open-source software?. Sci China Inf Sci, 2024, 67(4): 142103, doi: 10.1007/s11432-022-3611-3

REVIEW Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

When debugging encounters artificial intelligence: state of the art and open challenges
Song, Yi; Xie, Xiaoyuan; Xu, Baowen
Sci China Inf Sci, 2024, 67(4): 141101
Keywords: software debugging; fault localization; program repair; artificial intelligence; machine learning
Cite as: Song Y, Xie X Y, Xu B W. When debugging encounters artificial intelligence: state of the art and open challenges. Sci China Inf Sci, 2024, 67(4): 141101, doi: 10.1007/s11432-022-3803-9

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

ASTSDL: predicting the functionality of incomplete programming code via an AST-sequence-based deep learning model
Yu, Yaoshen; Huang, Zhiqiu; Shen, Guohua; Li, Weiwei; Shao, Yichao
Sci China Inf Sci, 2024, 67(1): 112105
Keywords: functionality prediction; incomplete programming code; syntactical information; code representation model; deep learning algorithm
Cite as: Yu Y S, Huang Z Q, Shen G H, et al. ASTSDL: predicting the functionality of incomplete programming code via an AST-sequence-based deep learning model. Sci China Inf Sci, 2024, 67(1): 112105, doi: 10.1007/s11432-021-3665-1

RESEARCH PAPER Webpage Webpage-cn SpringerLink Google Scholar Cited in SCI: 0

LegoDroid: flexible Android app decomposition and instant installation
Liu, Yi; Ma, Yun; Xiao, Xusheng; Xie, Tao; Liu, Xuanzhe
Sci China Inf Sci, 2023, 66(4): 142103
Keywords: performance; software bloat; instant installation; mobile applications; program analysis
Cite as: Liu Y, Ma Y, Xiao X S, et al. LegoDroid: flexible Android app decomposition and instant installation. Sci China Inf Sci, 2023, 66(4): 142103, doi: 10.1007/s11432-021-3528-7