软件缺陷(bug)分派是将bug报告与适合解决该bug的开发人员进行匹配的过程,能够使bug得到及时修复.目前的bug分派研究大多集中于bug报告的文本分类,但根据帕累托法则,用以分类的bug报告存在数据分布不均衡现象,容易对非活跃开发者产生较差的分派效果;此外,现有的分类模型忽视了对开发人员的建模且难以挖掘bug与开发人员之间的相关性,影响了bug分派效能.为此,提出一种基于多模态融合的软件缺陷协同分派方法CBT-MF (collaborative bug triaging method based on multimodal fusion).该方法首先对bug报告进行预处理并构造bug-开发人员二部图;其次,为了缓减bug修复记录分布不均衡性的影响,通过K-means和正负采样的方法对二部图数据进行增强;为了表征开发者信息,基于图卷积模型提取二部图节点特征;最后,采用内积匹配的方法捕获bug与开发者的相关性,并通过贝叶斯个性化排序实现bug报告与开发人员的推荐与分派.在公开数据集上进行全面的实验评估,实验结果表明, CBT-MF在bug分派方面相较于多个现有先进方法表现出更优越的性能.
In this paper, for the colltact problem in elasticity, we proposed a new mixed variational formulation, which is the base for the dual mixed finite element method of the contact problem.
In this paper, for the colltact problem in elasticity, we proposed a new mixed variational formulation, which is the base for the dual mixed finite element method of the contact problem.
坝体抗震设计和评估需要准确计算无限水库动力响应.基于比例边界有限元法(scaled boundary finite element method,SBFEM)力学推导技术,推导了顺河向地震激励下等横截面无限水域频域响应计算公式,利用Fourier逆变换建立了时域响应控制方...
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坝体抗震设计和评估需要准确计算无限水库动力响应.基于比例边界有限元法(scaled boundary finite element method,SBFEM)力学推导技术,推导了顺河向地震激励下等横截面无限水域频域响应计算公式,利用Fourier逆变换建立了时域响应控制方程,通过线性叠加推导了顺河、横河、竖直三向组合地震激励下的无限水域频域和时域响应的SBFEM计算公式.结合有限元法,建立了无限水库频域和时域响应的FEM-SBFEM耦合方程.分析了地震激励下的二维、三维等横截面无限水库频域、时域响应,数值验证了所建立计算公式的正确性.所发展的FEM-SBFEM公式体系可推广应用于库底库岸具有吸收性的、横截面有任意几何形状的无限水库谐响应及瞬态响应分析.
In this paper, the elastic contact problems in which no friction is present andtheir linear finite element approximation have been considered. First the elasticcontact problems are classified intuitively according to ...
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In this paper, the elastic contact problems in which no friction is present andtheir linear finite element approximation have been considered. First the elasticcontact problems are classified intuitively according to the different location ofcontact boundary, and for one cases a new proof of existence of the solution ofproblem has been presented. Next a general error estimation of linear finite elementapproximation to the contact problem has been obtained under weaker assumptionfor the regularity of the solution of problem.
A Decomposition method for solving quadratic programming (QP) with boxconstraints is presented in this paper. It is similar to the iterative method forsolving linear system of equations. The main ideas of the algorith...
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A Decomposition method for solving quadratic programming (QP) with boxconstraints is presented in this paper. It is similar to the iterative method forsolving linear system of equations. The main ideas of the algorithm are to splitthe Hessian matrix Q of the oP problem into the sum of two matrices N and Hsuch that Q = N + H and (N - H) is symmetric positive definite matrix ((N, H)is called a regular splitting of Q)[5]. A new quadratic programming problem withHessian matrix N to replace the original Q is easier to solve than the originalproblem in each iteration. The convergence of the algorithm is proved under certainassumptions, and the sequence generated by the algorithm converges to optimalsolution and has a linear rate of R-convergence if the matrix Q is positive definite,or a stationary point for the general indefinite matrix Q, and the numerical resultsare also given.
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