Prioritizing Tasks in Software Development: a Systematic Literature Review

Citation Author(s):
Yaroslav
Plaksin
Innopolis University, Innopolis, Russia
Ayomide
Bakare
Innopolis University, Innopolis, Russia
Arina
Cheverda
Innopolis University, Innopolis, Russia
Giancarlo
Succi
Innopolis University, Innopolis, Russia
Witold
Pedrycz
University of Alberta, Edmonton, Canada
Mirko
Farina
Innopolis University, Innopolis, Russia
Artem
Kruglov
Innopolis University, Innopolis, Russia
Yegor
Bugayenko
Huawei, Moscow, Russia
Submitted by:
yaroslav plaksin
Last updated:
Fri, 04/29/2022 - 05:25
DOI:
10.21227/kyse-2a84
License:
0
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Abstract 

Task prioritization is one of the most researched areas in software development. Given the huge amount of papers written on the topic, it might be challenging for IT practitioners to find the most appropriate tools or methods developed to date to deal with this important issue. To overcome this problem, we conducted a systematic literature review. The main goal of this work is to review the current state of research and practice on task prioritization among IT practitioners and to individuate the most effective ranking tools and techniques used in the industry. We can make a number of observations based on the results of this work. 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 investigate task prioritization in terms of “pull request prioritization” and “issue prioritization.” Thirdly, the most frequently used metrics for measuring the quality of a model are f-score, precision, recall, and accuracy

Instructions: 

This dataset is part of the systematic literature review (SLR) entitled "Prioritizing Tasks in Software Development: a Systematic Literature Review". The dataset represents the data collected from the studies we included in our final reading log.Specifically, we collected 3 types of relevant data. These are metrics, dataset, and methods. The attributes we collected are as follows:

TitleStudy title.Year of PublicationThe year in which the study was published.AuthorsAuthors of the study.MetricsMetrics used to evaluate the method for task prioritization.KeywordsKeywords of the paper.Conference/JournalConference/Jounral in which paper was published.PublisherPublisher of the paper.AlgorithmsAlgorithms used for prioritizing tasks.DatasetsDatasets used to train and test the model for task prioritization.

Funding Agency: 
Huawei Technologies Co., Ltd.