Abstract

An approach to generating and optimizing test cases is proposed for Web application testing based on user sessions using genetic algorithm. A large volume of meaningful user sessions are obtained after purging their irrelevant information by analyzing user logs on the Web server. Most of the redundant user sessions are also removed by the reduction process. For test reuse and test concurrency, it divides the user sessions obtained into different groups, each of which is called a test suite, and then prioritizes the test suites and the test cases of each test suite. So, the initial test suites and test cases, and their initial executing sequences are achieved. However, the test scheme generated by the elementary prioritization is not much approximate to the best one. Therefore, genetic algorithm is employed to optimize the results of grouping and prioritization. Meanwhile, an approach to generating new test cases is presented using crossover. The new test cases can detect faults caused by the use of possible conflicting data shared by different users.

Highlights

  • Incapable Web applications can have far-ranging consequences on businesses, economies, scientific progress, health, and so on

  • An approach to generating and optimizing test cases is proposed for Web application testing based on user sessions using genetic algorithm

  • Different from them, this paper investigates a key problem in Web application testing: test case generation and optimization

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Summary

Introduction

Incapable Web applications can have far-ranging consequences on businesses, economies, scientific progress, health, and so on. Et al [4] presented a data flow-based approach to testing Web applications. These methods [1,2,3,4] yields test data according to user sessions. User Session-Based Test Case Generation and Optimization Using Genetic Algorithm analyze test problems with the exception of [5], but not focusing on Web application testing. It delves into an approach to testing and optimizing Web applications based on user sessions using genetic algorithm. When converting a user session to a corresponding test case, we preserve the user input data

Collecting and Reducing User Sessions
Grouping and Prioritizing User Sessions
Testing Web Applications Using Genetic Algorithm
Selection
Crossover
Mutation
The Interacting Testing among User Sessions
Experimental Analysis
Findings
Concluding Remarks and Future Work
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