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Differential analysis of token metric and object oriented metrics for fault prediction

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Abstract

Due to the scarcity of resources, testing of each module is not possible for large projects. Thus, calculation of fault prone modules can be used for better resource utilization. A proposed token metric and the available object oriented metrics for forecasting the fault prone modules of an open source project has been proposed. The results from both set of metrics are compared to assess the effectiveness of the planned approach. The results concluded that (1) the proposed metric can be utilized for the calculation of fault prone modules with equivalent accuracy as in the case of object oriented metrics; (2) the token metric and object oriented metrics show opposite trends of results in precision and recall; (3) the proposed metric is much better for projects involving high risks.

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Authors and Affiliations

  1. IIT Delhi, New Delhi, India

    Ishleen Kaur

  2. CSIR-NISTADS, New Delhi, India

    Gagandeep Singh Narula

  3. Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi, India

    Vishal Jain

Authors
  1. Ishleen Kaur
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  2. Gagandeep Singh Narula
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  3. Vishal Jain
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Correspondence to Gagandeep Singh Narula.

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Kaur, I., Narula, G.S. & Jain, V. Differential analysis of token metric and object oriented metrics for fault prediction. Int. j. inf. tecnol. 9, 93–100 (2017). https://doi.org/10.1007/s41870-017-0004-0

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  • DOI: https://doi.org/10.1007/s41870-017-0004-0

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