Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (8): 2071-2080.doi: 10.23940/ijpe.19.08.p6.20712080

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Bug Report Classification based on Vector Space Model

Lele Chen, Song Huang*, Jinlei Sun, Zhanwei Hui, and Sen Yang   

  1. Command and Control Engineering College, Army Engineering University of PLA, Nanjing, 210007, China
  • Submitted on ;
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  • Supported by:
    The project is supported by the National Key Research and Development Program of China (No. 2018YFB1403400).

Abstract: As a vehicle for recording and tracking defects, bug reports provide a basis for solving software quality problems. Currently, software testing is often carried out in a multi-person and parallel state. The integration process of numerous bug reports, such as moving fake or duplication bug reports, is facing severe challenges. Therefore, this paper proposes an automatic detection modus for bug reports based on the vector space model. After pre-processing the bug report, a matching library is created according to the test requirements and test report samples. The vector space model is used to calculate the similarity between the two, and the correctness of the bug report is detected based on this. Experiments with the data of a software test contest show that the modus proposed in this paper can correctly judge most bug reports, effectively improving the efficiency of de-false and de-duplication.

Key words: software testing, vector space model, bug report, quality, natural language processing