As the popularity of open source projects,the volume of incoming pull requests is too large,which puts heavy burden on integrators who are responsible for accepting or rejecting pull requests.An accepted pull request ...As the popularity of open source projects,the volume of incoming pull requests is too large,which puts heavy burden on integrators who are responsible for accepting or rejecting pull requests.An accepted pull request prediction approach can help integrators by allowing them either to enforce an immediate rejection of code changes or allocate more resources to overcome the deficiency.In this paper,an approach CTCPPre is proposed to predict the accepted pull requests in GitHub.CTCPPre mainly considers code features of modified changes,text features of pull requests’description,contributor features of developers’previous behaviors,and project features of development environment.The effectiveness of CTCPPre on 28 projects containing 221096 pull requests is evaluated.Experimental results show that CTCPPre has good performances by achieving accuracy of 0.82,AUC of 0.76 and F1-score of 0.88 on average.It is compared with the state of art accepted pull request prediction approach RFPredict.On average across 28 projects,CTCPPre outperforms RFPredict by 6.64%,16.06%and 4.79%in terms of accuracy,AUC and F1-score,respectively.展开更多
In the field of supercomputing, one key issue for scal-able shared-memory multiprocessors is the design of the directory which denotes the sharing state for a cache block. A good direc-tory design intends to achieve t...In the field of supercomputing, one key issue for scal-able shared-memory multiprocessors is the design of the directory which denotes the sharing state for a cache block. A good direc-tory design intends to achieve three key attributes： reasonable memory overhead, sharer position precision and implementation complexity. However, researchers often face the problem that gain-ing one attribute may result in losing another. The paper proposes an elastic pointer directory （EPD） structure based on the analysis of shared-memory applications, taking the fact that the number of sharers for each directory entry is typical y smal . Analysis re-sults show that for 4 096 nodes, the ratio of memory overhead to the ful-map directory is 2.7%. Theoretical analysis and cycle-accurate execution-driven simulations on a 16 and 64-node cache coherence non uniform memory access （CC-NUMA） multiproces-sor show that the corresponding pointer overflow probability is reduced significantly. The performance is observed to be better than that of a limited pointers directory and almost identical to the ful-map directory, except for the slight implementation complex-ity. Using the directory cache to explore directory access locality is also studied. The experimental result shows that this is a promis-ing approach to be used in the state-of-the-art high performance computing domain.展开更多
基金Project(2018YFB1004202)supported by the National Key Research and Development Program of ChinaProject(61732019)supported by the National Natural Science Foundation of ChinaProject(SKLSDE-2018ZX-06)supported by the State Key Laboratory of Software Development Environment,China
文摘As the popularity of open source projects,the volume of incoming pull requests is too large,which puts heavy burden on integrators who are responsible for accepting or rejecting pull requests.An accepted pull request prediction approach can help integrators by allowing them either to enforce an immediate rejection of code changes or allocate more resources to overcome the deficiency.In this paper,an approach CTCPPre is proposed to predict the accepted pull requests in GitHub.CTCPPre mainly considers code features of modified changes,text features of pull requests’description,contributor features of developers’previous behaviors,and project features of development environment.The effectiveness of CTCPPre on 28 projects containing 221096 pull requests is evaluated.Experimental results show that CTCPPre has good performances by achieving accuracy of 0.82,AUC of 0.76 and F1-score of 0.88 on average.It is compared with the state of art accepted pull request prediction approach RFPredict.On average across 28 projects,CTCPPre outperforms RFPredict by 6.64%,16.06%and 4.79%in terms of accuracy,AUC and F1-score,respectively.
基金supported by the National Natural Science Foundation of China(6123200961370059)+1 种基金the High Technology Research and Development Program of China(863 Program)(2011AA01A205)the Fund of the State Key Laboratory of Software Development Environment(SKLSDE2012ZX06)
文摘In the field of supercomputing, one key issue for scal-able shared-memory multiprocessors is the design of the directory which denotes the sharing state for a cache block. A good direc-tory design intends to achieve three key attributes： reasonable memory overhead, sharer position precision and implementation complexity. However, researchers often face the problem that gain-ing one attribute may result in losing another. The paper proposes an elastic pointer directory （EPD） structure based on the analysis of shared-memory applications, taking the fact that the number of sharers for each directory entry is typical y smal . Analysis re-sults show that for 4 096 nodes, the ratio of memory overhead to the ful-map directory is 2.7%. Theoretical analysis and cycle-accurate execution-driven simulations on a 16 and 64-node cache coherence non uniform memory access （CC-NUMA） multiproces-sor show that the corresponding pointer overflow probability is reduced significantly. The performance is observed to be better than that of a limited pointers directory and almost identical to the ful-map directory, except for the slight implementation complex-ity. Using the directory cache to explore directory access locality is also studied. The experimental result shows that this is a promis-ing approach to be used in the state-of-the-art high performance computing domain.
