PAR platform derived from the Statute of the start

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PAR platform derived from the Statute of the starting and automatic generation algorithm

,[link widoczny dla zalogowanych], 1985,[link widoczny dla zalogowanych],14 (6) :421-437. 【3】 Huang Lin had. Principle and application of rough set 【M】. Chongqing: Chongqing University Press ,1998:15-69. [4] Miao Duo-Qian, Wang Jue. Rough Set Based Decision Tree Method for Multivariate】【J. Software,[link widoczny dla zalogowanych], 1997.8 (6) :425-431. 【5】 Tang Bin, LI Long-shu. Discernibility matrix based on attribute reduction algorithm of 【JJ. Computer Engineering and Applications, 2004,40 (14) :184-186. 【6】 Yangzeng Guang, LI Long-shu. Decision Tree Learning in RoboCup Simulator League Application 【JJ. System Simulation. 2004,[link widoczny dla zalogowanych],16 (4) :653-656. (Continued from page 42) TERMINATION: p <rRECUR: (2) style (3) END (4) construction of loop invariants to solve the above problem has been analyzed in the process, the array of n 【P, r】 always be q divided into three parts, and then on this basis is given P, r, q range of variation that are loop invariant:: s = partition (n, P, r) quieksort (n, P, q A 1) quicksort ( n, q + l, r), O ≤ p ≤ g ≤ r ≤ n-1 (5), (6) (omitted) 3 Conclusion This paper introduces the PAR method and its platform. Algorithm developed two questions to illustrate the typical PAR method and platform development process and points. Can be formalized using the PAR method and derived from the Statute of the progressive algorithm and automatic generation algorithm program. Formal derivation is essentially a constructive proof, which guarantees the correctness of the algorithm process. Automation of the small number generation algorithm with significantly improved the efficiency of the algorithm development process. Loop invariant is to understand the key design an algorithm, using the PAR approach in the process of construction algorithm, loop invariants can be naturally by the recursion relations are constructed. This helps to deeply understand the algorithm design. Derivation of the current form of the algorithm remains a creative and challenging activities that require manual intervention. Difficult to automate. Task Force will further derive more algorithms, search algorithms as much as possible in the form of derivation of the general law, to continue to explore the process of automation efforts.