Computer Science ›› 2021, Vol. 48 ›› Issue (5): 45-50.doi: 10.11896/jsjkx.201000107
• Computer Software • Previous Articles Next Articles
FAN Jia-kuan1, WANG Hao-yue1, ZHAO Sheng-yu2, ZHOU Tian-yi1, WANG Wei1
CLC Number:
[1]XUAN Q,GHAREHYAZIE M,DEVANBU P T,et al.Measu-ring the effect of social communications on individual working rhythms:A case study of open source software[C]// 2012 International Conference on Social Informatics.2012:78-85. [2]SOWE S K,STAMELOS I,ANGELIS L.Understanding know-ledge sharing activities in free/open source software projects:An empirical study[J].Journal of Systems and Software,2008,3(81):431-446. [3]BACHMAN N,BERNSTEIN A.When process data quality affects the number of bugs:Correlations in software engineering datasets[C]//2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).2010:62-71. [4]GOURLEY B A,DEVANBU P.Detecting patch submission and acceptance in oss projects[C]//Fourth International Workshop on Mining Software Repositories (MSR'07).ICSE,2007:26. [5]HO J,ERMON S.Generative adversarial imitation learning[C]//Advances in Neural Information Processing Systems.2016:4565-4573. [6]BOEH M,LI G H.Value-based software engineering:a casestudy[J].Computer,2003,36(3):33-41. [7]MARLOW J,DABBISH L,HERBSLEB J.Impression formation in online peer production:Activity traces and personal profiles in github[C]//Proceedings of the 2013 Conference on Computer Supported Cooperative Work(CSCW '13).New York,NY,USA,2013:117-128. [8]TSAY J,DABBISH L,HERBSLEB J.Influence of social andtechnical factors for evaluating contribution in github[C]//Proceedings of the 36th International Conference on Software Engineering(ICSE 2014).New York,NY,USA,2014:356-366. [9]X-lab.Github's digital annual report for 2019[OL].https://github.com/X-lab2017/github-analysis-report-2019,2020. [10]YE D,LIU Z,SUN M,et al.Mastering Complex Control inMOBA Games with Deep Reinforcement Learning[C]//AAAI.2020:6672-6679. [11]JIANG N,JIN S,DUAN Z,et al.RL-Duet:Online Music Accompaniment Generation Using Deep Reinforcement Learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2020:710-718. [12]JING M,MA X,HUANG W,et al.Reinforcement Learningfrom Imperfect Demonstrations under Soft Expert Guidance[C]//AAAI.2020:5109-5116. [13]LILLICRAP T P,HUNT J J,PRITZEL A,et al.Continuouscontrol with deep reinforcement learning[J].arXiv:1509.02971,2015. [14]JENSE N,SCACCHI W.Role migration and advancement pro-cesses in ossd projects:A comparative case study[C]//29th International Conference on Software Engineering (ICSE'07).2007:364-374. [15]SCHULMAN J,WOLSKI F,DHARIWAL P,et al.Proximalpolicy optimization algorithms[J].arXiv:1707.06347,2017. [16]THUNG T F,BISSYANDE ,LO D,et al.Network structure of social coding in github[C]//17th European Conference on Software Maintenance and Reengineering.2013:323-326. [17]GOUSIOS G,KALLIAMVAKOU E,SPINELLIS D.Measuring developer contribution from software repository data[C]//Proceedings of the 2008 International Working Conference on Mi-ning Software Repositories(MSR '08).New York,NY,USA,2008:129-132. [18]ZHOU M,MOCKUS A.Who will stay in the floss community? modeling participant's initial behavior[J].IEEE Transactions on Software Engineering,2015,41(1):82-99. |
[1] | YU Bin, LI Xue-hua, PAN Chun-yu, LI Na. Edge-Cloud Collaborative Resource Allocation Algorithm Based on Deep Reinforcement Learning [J]. Computer Science, 2022, 49(7): 248-253. |
[2] | LI Meng-fei, MAO Ying-chi, TU Zi-jian, WANG Xuan, XU Shu-fang. Server-reliability Task Offloading Strategy Based on Deep Deterministic Policy Gradient [J]. Computer Science, 2022, 49(7): 271-279. |
[3] | XIE Wan-cheng, LI Bin, DAI Yue-yue. PPO Based Task Offloading Scheme in Aerial Reconfigurable Intelligent Surface-assisted Edge Computing [J]. Computer Science, 2022, 49(6): 3-11. |
[4] | HONG Zhi-li, LAI Jun, CAO Lei, CHEN Xi-liang, XU Zhi-xiong. Study on Intelligent Recommendation Method of Dueling Network Reinforcement Learning Based on Regret Exploration [J]. Computer Science, 2022, 49(6): 149-157. |
[5] | LI Peng, YI Xiu-wen, QI De-kang, DUAN Zhe-wen, LI Tian-rui. Heating Strategy Optimization Method Based on Deep Learning [J]. Computer Science, 2022, 49(4): 263-268. |
[6] | OUYANG Zhuo, ZHOU Si-yuan, LYU Yong, TAN Guo-ping, ZHANG Yue, XIANG Liang-liang. DRL-based Vehicle Control Strategy for Signal-free Intersections [J]. Computer Science, 2022, 49(3): 46-51. |
[7] | DAI Shan-shan, LIU Quan. Action Constrained Deep Reinforcement Learning Based Safe Automatic Driving Method [J]. Computer Science, 2021, 48(9): 235-243. |
[8] | CHENG Zhao-wei, SHEN Hang, WANG Yue, WANG Min, BAI Guang-wei. Deep Reinforcement Learning Based UAV Assisted SVC Video Multicast [J]. Computer Science, 2021, 48(9): 271-277. |
[9] | LIANG Jun-bin, ZHANG Hai-han, JIANG Chan, WANG Tian-shu. Research Progress of Task Offloading Based on Deep Reinforcement Learning in Mobile Edge Computing [J]. Computer Science, 2021, 48(7): 316-323. |
[10] | WANG Ying-kai, WANG Qing-shan. Reinforcement Learning Based Energy Allocation Strategy for Multi-access Wireless Communications with Energy Harvesting [J]. Computer Science, 2021, 48(7): 333-339. |
[11] | ZHOU Shi-cheng, LIU Jing-ju, ZHONG Xiao-feng, LU Can-ju. Intelligent Penetration Testing Path Discovery Based on Deep Reinforcement Learning [J]. Computer Science, 2021, 48(7): 40-46. |
[12] | LI Bei-bei, SONG Jia-rui, DU Qing-yun, HE Jun-jiang. DRL-IDS:Deep Reinforcement Learning Based Intrusion Detection System for Industrial Internet of Things [J]. Computer Science, 2021, 48(7): 47-54. |
[13] | FAN Yan-fang, YUAN Shuang, CAI Ying, CHEN Ruo-yu. Deep Reinforcement Learning-based Collaborative Computation Offloading Scheme in VehicularEdge Computing [J]. Computer Science, 2021, 48(5): 270-276. |
[14] | HUANG Zhi-yong, WU Hao-lin, WANG Zhuang, LI Hui. DQN Algorithm Based on Averaged Neural Network Parameters [J]. Computer Science, 2021, 48(4): 223-228. |
[15] | LI Li, ZHENG Jia-li, LUO Wen-cong, QUAN Yi-xuan. RFID Indoor Positioning Algorithm Based on Proximal Policy Optimization [J]. Computer Science, 2021, 48(4): 274-281. |
|