Login| Sign Up| Help| Contact|

Patent Searching and Data


Title:
METHOD FOR LOCATING PROGRAM REGRESSION FAULT USING SLICING MODEL
Document Type and Number:
WIPO Patent Application WO/2017/201853
Kind Code:
A1
Abstract:
A method for locating a program regression fault using a slicing model, comprising: in a program pre-processing phase, comparing source codes of two versions of a program to identify parts that differ therebetween, and rearranging the source codes according to the identification result; in a trajectory association phase, on the basis of execution trajectories of the two acquired program versions, dependencies among statements thereof, and information of variables thereof, associating and classifying the statements of two execution trajectories; in a slicing analysis phase, taking an execution failure point of a new-version program as a starting point and performing slicing analysis; according to the statement entity classification and the dependencies thereof, backtracking to a statement entity causing the program execution failure, until there are no further dependency statements to be analyzed and the dependency of the current statement under analysis no longer needs to be analyzed; and using all statement entities analyzed in all phases in the slicing analysis as program behavior slicing output causing a regression error. The present invention explains the mechanism by which a regression fault is generated, and provides guidance for recovery from the regression fault.

Inventors:
LIU TING (CN)
WANG HAIJUN (CN)
ZHENG QINGHUA (CN)
GUAN XIAOHONG (CN)
CHEN ZEHUA (CN)
ZHU HAIPING (CN)
Application Number:
PCT/CN2016/090956
Publication Date:
November 30, 2017
Filing Date:
July 22, 2016
Export Citation:
Click for automatic bibliography generation   Help
Assignee:
UNIV XIAN JIAOTONG (CN)
International Classes:
G06F11/36
Foreign References:
CN101916222A2010-12-15
CN101859276A2010-10-13
CN103970845A2014-08-06
US20110239204A12011-09-29
Attorney, Agent or Firm:
XI'AN TONG DA PATENT AGENCY CO., LTD. et al. (CN)
Download PDF: