Software Defect Prediction Approaches Revisited
Khaled Shebl; Afify, Yasmine M.; Nagwa Badr;
Abstract
A crucial field in software development and testing is Software Defect Prediction (SDP)
because the quality, dependability, efficiency, and cost of the software are all improved by forecasting
software defects at an earlier stage. Many existing models predict defects to facilitate software testing
process for testers. A comprehensive review of these models from different perspectives is crucial to help
new researchers enter this field and learn about its latest developments. Algorithms, method types,
datasets, and tools were the only perspectives discussed in the current literature. A comprehensive study
that takes into account a wide spectrum of viewpoints hasn't yet been published. Examining the
development and advancement of SDP-related studies is the goal of this literature review. It provides a
comprehensive and updated state-of-the-art that satisfies all stated criteria. Out of 591 papers retrieved
from 6 reputable databases, 73 papers were eligible for analysis. This review addresses relevant research
questions regarding techniques & method types, data details, tools, code syntax, semantics, structural
and domain information. Motivation to conduct this comprehensive review is to equip the readers with
the necessary information and keep them informed about the software defect prediction domain.
because the quality, dependability, efficiency, and cost of the software are all improved by forecasting
software defects at an earlier stage. Many existing models predict defects to facilitate software testing
process for testers. A comprehensive review of these models from different perspectives is crucial to help
new researchers enter this field and learn about its latest developments. Algorithms, method types,
datasets, and tools were the only perspectives discussed in the current literature. A comprehensive study
that takes into account a wide spectrum of viewpoints hasn't yet been published. Examining the
development and advancement of SDP-related studies is the goal of this literature review. It provides a
comprehensive and updated state-of-the-art that satisfies all stated criteria. Out of 591 papers retrieved
from 6 reputable databases, 73 papers were eligible for analysis. This review addresses relevant research
questions regarding techniques & method types, data details, tools, code syntax, semantics, structural
and domain information. Motivation to conduct this comprehensive review is to equip the readers with
the necessary information and keep them informed about the software defect prediction domain.
Other data
Title | Software Defect Prediction Approaches Revisited | Authors | Khaled Shebl; Afify, Yasmine M. ; Nagwa Badr | Keywords | Software Defect Prediction;Software testing;Solve class imbalance issue;Feature selection;Machine learning | Issue Date | 14-Aug-2023 | Journal | International Journal of Intelligent Computing, and Information Sciences (IJICIS) | Volume | 23 | Issue | 3 | Start page | 31 | End page | 58 | DOI | 10.21608/ijicis.2023.200737.1261 |
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