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Software Fault Prediction pp 23–30Cite as

Types of Software Fault Prediction

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Abstract

A large number of researchers have presented various fault prediction studies to predict the fault-proneness of the given software system. These fault prediction studies reported the results in term of different–different contexts. Depending upon the context of the results, a fault prediction model can classify a software module into faulty or non-faulty class (binary class classification ) or can predict the number of faults in the given software module. Additionally, a fault prediction model can be built by using the fault dataset of other similar software projects (cross-project prediction ). A fault prediction model can be employed to identify fault-inducing changes to provide the earlier feedback to the developers (just-in-time prediction ). In this chapter, we provide an overview of different types of fault prediction. A detailed discussion on the state of the art has been presented.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India

    Sandeep Kumar

  2. Department of Computer Science and Engineering, National Institute of Technology Jalandhar, Jalandhar, India

    Santosh Singh Rathore

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  1. Sandeep Kumar
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  2. Santosh Singh Rathore
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Correspondence to Sandeep Kumar .

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Kumar, S., Rathore, S.S. (2018). Types of Software Fault Prediction. In: Software Fault Prediction. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-8715-8_3

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  • DOI: https://doi.org/10.1007/978-981-10-8715-8_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8714-1

  • Online ISBN: 978-981-10-8715-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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