Block Diagonal Representation (BDR) model can efficiently cluster data by using linear representation, but it cannot make good use of non-linear manifold information commonly appeared in high-dimensional data. To solve this problem, the improved Block Diagonal Representation based on Neighbor Graph (BDRNG) clustering algorithm was proposed to perform the linear fitting of the local geometric structure by the neighbor graph and generate the block-diagonal structure by using the block-diagonal regularization. In BDRNG algorithm, both global information and local data structure were learned at the same time to achieve a better clustering performance. Due to the fact that the model contains the neighbor graph and non-convex block-diagonal representation norm, the alternative minimization was adopted by BDRNG to optimize the solving algorithm. Experimental results show that:on the noise dataset, BDRNG can generate the stable coefficient matrix with block-diagonal form, which proves that BDRNG is robust to the noise data; on the standard datasets, BDRNG has better clustering performance than BDR, especially on the facial dataset, BDRNG has the clustering accuracy 8% higher than BDR.

McCabe's basic path testing method (McCABE T J. A complexity measure. IEEE Transactions on Software Engineering, 1976, SE-2(4): 308-320) is a more rigorous software testing one in dynamic white-box testing techniques, but the efficiency of McCabe method is lower. To solve this problem, this paper proposed an algorithm to design basic path test case according to the basic program structure. The algorithm first created a basic unit chart based on the Z-path coverage. Next, the rules that combined a control flow graph from basic unit were established. On this basis, the combination algorithm of the basic path was constructed. The algorithm collected the path set of basic program structure by scanning a program only once, and then generated the basic path set using those paths by combination ways. This method is more concise than the method proposed by McCabe, and it can improve the efficiency of the basic path test case design.