Predicting the Priority of Bug Reports Using Classification Algorithms

Pushpalatha, M.; Mrunalini, M.; Bista, Sulav Raj

doi:10.21817/indjcse/2020/v11i6/201106076

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…As Table 6 shows, the work by Pushpalatha et al [ 85 ] has the highest amount of highlighted cells. This makes it the best approach concerning the Eclipse dataset.…”

Section: Discussionmentioning

confidence: 99%

Prioritizing tasks in software development: A systematic literature review

Bugayenko¹,

Bakare

Cheverda

et al. 2023

PLoS ONE

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Task prioritization is one of the most researched areas in software development. Given the huge number of papers written on the topic, it might be challenging for IT practitioners–software developers, and IT project managers–to find the most appropriate tools or methods developed to date to deal with this important issue. The main goal of this work is therefore to review the current state of research and practice on task prioritization in the Software Engineering domain and to individuate the most effective ranking tools and techniques used in the industry. For this purpose, we conducted a systematic literature review guided and inspired by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, otherwise known as the PRISMA statement. Based on our analysis, we can make a number of important observations for the field. Firstly, we found that most of the task prioritization approaches developed to date involve a specific type of prioritization strategy—bug prioritization. Secondly, the most recent works we review investigate task prioritization in terms of “pull request prioritization” and “issue prioritization,” (and we speculate that the number of such works will significantly increase due to the explosion of version control and issue management software systems). Thirdly, we remark that the most frequently used metrics for measuring the quality of a prioritization model are f-score, precision, recall, and accuracy.

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“…As Table 6 shows, the work by Pushpalatha et al [ 85 ] has the highest amount of highlighted cells. This makes it the best approach concerning the Eclipse dataset.…”

Section: Discussionmentioning

confidence: 99%