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Adaptive test case sorting method based on greedy algorithm and clustering analysis

A test case, greedy algorithm technology, applied in software testing/debugging, computing, computer parts, etc., can solve the problem of low efficiency, reduce test costs, reduce sorting speed and time, and improve sorting efficiency.

Pending Publication Date: 2021-12-10
JIANGSU UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

This method is suitable for general test cases, but when the number of test cases is large, this method is not efficient

Method used

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  • Adaptive test case sorting method based on greedy algorithm and clustering analysis
  • Adaptive test case sorting method based on greedy algorithm and clustering analysis
  • Adaptive test case sorting method based on greedy algorithm and clustering analysis

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Embodiment Construction

[0036] In order to understand more clearly the technical content of a method for sorting adaptive test cases based on greedy algorithm and cluster analysis of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and specific implementation cases. It should be pointed out that the described The implementation examples given are intended to facilitate the understanding of the present invention without any limiting requirements.

[0037] The flow chart of a kind of self-adaptive test case sorting method based on greedy algorithm and cluster analysis that the present invention provides is as shown in Figure 1, and the first step reads original test case, calculates the Manhattan distance matrix of original test case; According to the Manhattan distance matrix, the original test cases are divided into k (5% of the total number of test cases) clusters by using the improved K center point clustering method for the o...

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Abstract

The invention discloses a adaptive test case sorting method based on a greedy algorithm and clustering analysis, and belongs to the field of software engineering. The method comprises the following steps: step 1, reading original test cases, calculating a Manhattan distance matrix of the original test cases, and dividing a test case set into k (5% of the total number of the test cases) clusters for the original test cases according to the distance matrix by using an improved K center point clustering method; step 2, on the basis of the distance matrix, sorting each cluster subjected to K center point clustering by using a greedy algorithm; and step 3, after each cluster is sequenced, selecting the test cases from each cluster in sequence, and combining the test cases into a test case set for testing. The method has the advantage of low time overhead under the condition that the sorting effect is ensured, and compared with an existing greedy algorithm for sorting, the advantages of effectiveness and low time overhead of the method are verified.

Description

technical field [0001] The invention belongs to the technical field of test case priority in software testing, and relates to an adaptive test case sorting method based on a greedy algorithm and cluster analysis. Background technique [0002] The rapid development of the software industry has prompted various types of software to emerge one after another, and the quality of software products needs to be improved urgently. When the requirements of the software project are determined, the software testing work should start. Since software testing runs through the whole process of software life cycle, the time cost of software testing is relatively high. However, many companies in China generally hand over the testing work to software testers for testing in the integration testing phase after the initial completion of the software. If defects are found during testing, testers need to select appropriate test cases to test the system. Testing may exist in all stages of the ent...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36G06K9/62
CPCG06F11/3684G06F11/3688G06F18/23213
Inventor 陈锦富顾月超蔡赛华陈海波张翅陈静怡黄创飞
Owner JIANGSU UNIV
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