Software Bugs Identification and Prediction Approaches and their Interrelationships with Levels of Inheritance: An Empirical Analysis

Authors

  • Varuna Gupta
  • Tarun Kumar Singhal

Abstract

The software applications are experiencing the challenges of ever-growing complexity caused by the increase in the number of bugs. The software development process has been adversely affected due to the wastage of resources caused due to the bugs. It is imperative to identify and predict bugs to facilitate the software development process and prevent rework. The researchers have successfully attributed metrics (product, process and project) as the dominant causes of the bugs. Through this work, the researchers aspire to spread awareness among the developers regarding prominent causes of the bugs while facilitating a smooth software development process.

 

Additionally, the researchers have correlated the effectiveness in the processes related to prediction of severities of the bugs corresponding to the levels and the levels of inheritance. The software quality is predominantly and adversely affected by product metricsoriented software bugs with significant correlation. Different levels of inheritance are associated with the severities of the bugs with a correlation that the severities are bound to rise with an increase in the levels of inheritance. The outcomes of this research work are of particular significance to software developers, software quality expertsandresearchers.The outcomes of this research work while promoting a set of practices to rationalize the inheritance suggest a lookout on severities of the bugs to roll out an acceptable quality of software applications. The outcomes of this research work also suggest rationalizing the efforts to identify and predictthe bugs.

 Keywords: Software Bugs, Bug Prediction, Reasons of Bugs, Neural Networks, Levels of Inheritance.

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Published

2020-01-28

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Articles