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Multi-objective Optimization Method for Regression Test Cases Based on MOEA/D Algorithm

A multi-objective optimization and regression testing technology, applied in software testing/debugging, etc., can solve problems such as the complexity of multi-objective optimization methods, and achieve the effect of effective test case set optimization and simple methods

Inactive Publication Date: 2017-06-06
西安翱翔云测科技有限责任公司
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Problems solved by technology

[0010] In order to overcome the complex deficiencies of existing multi-objective optimization methods for regression test cases, the present invention provides a multi-objective optimization method for regression test cases based on the MOEA / D algorithm

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  • Multi-objective Optimization Method for Regression Test Cases Based on MOEA/D Algorithm
  • Multi-objective Optimization Method for Regression Test Cases Based on MOEA/D Algorithm
  • Multi-objective Optimization Method for Regression Test Cases Based on MOEA/D Algorithm

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Embodiment Construction

[0042] refer to Figure 1-5 . The present invention is based on the regression test case multi-objective optimization method concrete steps of MOEA / D algorithm as follows:

[0043] Pareto optimality is originally a concept from economics. However, with the development and progress of science and technology, this concept is now widely used in other disciplines or fields such as game theory, social science and engineering. The original expression of the concept of Pareto optimality is: if for a given state of resource allocation, all Pareto improvements do not exist, that is, in this state, no change can make at least one person's situation better Without making anyone's situation worse, this state of resource allocation is called Pareto optimal state.

[0044] Based on the above description, the multi-objective optimization problem can be defined as finding a decision vector x that can optimize an objective function f consisting of M vectors i (x), where i=1,2,...,M. The ob...

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Abstract

The invention discloses an MOEA / D algorithm based multi-target optimizing method for a regression test case, and aims at solving the technical problem of complexity of the existing multi-target optimizing method for the regression test case. According to the technical scheme, the method comprises the steps of selecting three properties from all properties which influence the effect of the test case; respectively detecting the influence degree of the three properties to the effect of the test case; detecting code coverage rate through a built-in plug-in GCOV of a GCC coder; analyzing tested program source code through inserting program during detecting the branch coverage; inserting detection codes in the if-else branch, for circulation, do-while and while-do circulation; testing the case execution time through an open-source tool. According to the method, the MOEA / D algorithm is used for performing three-target optimization of a regression test case set; the test case can be effectively optimized under the condition that various test demands are completely covered; the method is simple.

Description

technical field [0001] The invention relates to a multi-objective optimization method for a regression test case, in particular to a multi-objective optimization method for a regression test case based on the MOEA / D algorithm. Background technique [0002] In the whole cycle of software testing, one of the most time-consuming and expensive content is the error location and correction process. Especially after the software fault is located and repaired, the content of the repair may introduce new problems or faults to the software. However, the previous fault re-diagnosis methods often require re-executing all test cases after the found faults are repaired to determine whether the faults have been completely repaired and whether new faults have been introduced. This method is not only very expensive and time-consuming, the execution process Cumbersome and error-prone. Therefore, regression testing is widely used in software testing as a method to improve the efficiency and ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36
Inventor 郑炜李知隆李隆俊阴一溦吴潇雪
Owner 西安翱翔云测科技有限责任公司
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