Research on Object-oriented Software Testing Cases of Automatic Generation

In the research on automatic generation of testing cases, there are different execution paths under drivers of different testing cases. The probability of these paths being executed is also different. For paths which are easy to be executed, more redundant testing case tend to be generated; But only fewer testing cases are generated for the control paths which are hard to be executed. Genetic algorithm can be used to instruct the automatic generation of testing cases. For the former paths, it can restrict the generation of these kinds of testing cases. On the contrary, the algorithm will encourage the generation of such testing cases as much as possible. So based on the study on the technology of path-oriented testing case automatic generation, the genetic algorithm is adopted to construct the process of automatic generation. According to the triggering path during the dynamic execution of program, the generated testing cases are separated into different equivalence class. The number of testing case is adjusted dynamicly by the fitness corresponding to the paths. The method can create a certain number of testing cases for each execution path to ensure the sufficiency. It also reduces redundant testing cases so it is an effective method for automatic generation of testing cases.

[1]  Nicola Orio,et al.  An Efficient Identification Methodology for Improved Access to Music Heritage Collections , 2012, J. Multim..

[2]  Xie Jiancang Test Case Generation for Component-based Software Based on Immune Genetic Algorithm , 2006 .

[3]  Elaine J. Weyuker,et al.  More Experience with Data Flow Testing , 1993, IEEE Trans. Software Eng..

[4]  David Cordes,et al.  Automated flow graph-based testing of object-oriented software modules , 1993, J. Syst. Softw..

[5]  Yao Li RESEARCH ON COVERAGE METRICS FOR OO SOFTWARE AND IMPLEMENTATION OF AN OO SOFTWARE TESTING TOOL , 2002 .

[6]  Michael D. Smith,et al.  Extending Object-Oriented Optimizations for Concurrent Programs , 2007, 16th International Conference on Parallel Architecture and Compilation Techniques (PACT 2007).

[7]  Bai Jie,et al.  Mathematical Model and Hybrid Scatter Search for Cost Driven Job-shop Scheduling Problem , 2011 .

[8]  E.Eugene Schultz,et al.  Feature: A systematic methodology for firewall penetration testing , 1996 .

[9]  Lv Ge-jing Study on Method of Improving Efficiency of Software Testing , 2010 .

[10]  Wu Jian-guo Study on Method of Improving Efficiency of Software Testing , 2006 .

[11]  Jie Bai,et al.  Mathematical Model and Hybrid Scatter Search for Cost Driven Job-shop Scheduling Problem , 2011, J. Networks.

[12]  Christoph Meinel,et al.  Supporting Object-Oriented Programming of Semantic-Web Software , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[13]  An Jin Dynamic Evaluation Method Based Multi-Dimensional Test Coverage for Software Testing , 2010 .

[14]  Charles Rankin,et al.  The Software Testing Automation Framework , 2002, IBM Syst. J..

[15]  Lionel C. Briand,et al.  An object-oriented high-level design-based class cohesion metric , 2010, Inf. Softw. Technol..

[16]  Ding Xiao-ming,et al.  Research of software test process measurement based on CMMI , 2007 .

[17]  Lionel C. Briand,et al.  A Precise Method-Method Interaction-Based Cohesion Metric for Object-Oriented Classes , 2012, TSEM.

[18]  Paul C. Jorgensen,et al.  Software Testing: A Craftsman's Approach , 1995 .

[19]  Jin Hu Design of Software Test Cases of Genetic Algorithm Based on DD-Path , 2010 .

[20]  Zhen Liu,et al.  An Application of the Modification of Slow Start Algorithm in Campus Network , 2011, J. Networks.