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相关论文: A guide to performing systematic literature review…

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[Context] Systematic Literature Review (SLR) has been a major type of study published in Software Engineering (SE) venues for about two decades. However, there is a lack of understanding of whether an SLR is really needed in comparison to a…

软件工程 · 计算机科学 2023-07-13 Xiaofeng Wang , Henry Edison , Dron Khanna , Usman Rafiq

Context: New scientific evidence continuously arises with advances in Software Engineering (SE) research. Conventionally, Systematic Literature Reviews (SLRs) are not updated or updated intermittently, leaving gaps between updates, during…

软件工程 · 计算机科学 2022-06-10 Bianca Minetto Napoleão , Fabio Petrillo , Sylvain Hallé , Marcos Kalinowski

Systematic Literature Reviews (SLRs) play an important role in the Evidence-Based Software Engineering scenario. With the advance of the computer science field and the growth of research publications, new evidence continuously arises. This…

软件工程 · 计算机科学 2021-08-31 Bianca Minetto Napoleão , Fabio Petrillo , Sylvain Hallé

Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully…

软件工程 · 计算机科学 2020-06-11 Claes Wohlin , Emilia Mendes , Katia Romero Felizardo , Marcos Kalinowski

Systematic literature review (SLR) is foundational to evidence-based research, enabling scholars to identify, classify, and synthesize existing studies to address specific research questions. Conducting an SLR is, however, largely a manual…

A systematic literature review (SLR) is a methodology used to find and aggregate all relevant existing evidence about a specific research question of interest. Important decisions need to be made at several points in the review process,…

软件工程 · 计算机科学 2020-12-22 Katia R. Felizardo , Stephen G. MacDonell , Emília Mendes , José Carlos Maldonado

Systematic Literature Review (SLR) is a rigorous methodology applied for Evidence-Based Software Engineering (EBSE) that identify, assess and synthesize the relevant evidence for answering specific research questions. Benefiting from the…

软件工程 · 计算机科学 2017-04-26 Zheng Li , Yan Liu

Background: Systematic literature reviews (SLRs) have become prevalent in software engineering research. Several researchers may conduct SLRs on similar topics without a prospective register for SLR protocols. However, even ignoring these…

软件工程 · 计算机科学 2026-01-30 Henry Edison , Nauman Ali

Context: Systematic literature reviews (SLRs) have become standard practise as part of software engineering research, although their quality varies. To build on the reviews, both for future research and industry practice, they need to be of…

软件工程 · 计算机科学 2024-10-08 Muhammad Usman , Nauman bin Ali , Claes Wohlin

This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates previous research on a given…

人工智能 · 计算机科学 2024-08-07 Francisco Bolanos , Angelo Salatino , Francesco Osborne , Enrico Motta

In the medical domain, a Systematic Literature Review (SLR) attempts to collect all empirical evidence, that fit pre-specified eligibility criteria, in order to answer a specific research question. The process of preparing an SLR consists…

信息检索 · 计算机科学 2020-11-20 Athanasios Lagopoulos , Grigorios Tsoumakas

Background: The software engineering community has increasingly conducted systematic literature reviews (SLR) as a means to summarize evidence from different studies and bring to light the state of the art of a given research topic. While…

Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and…

软件工程 · 计算机科学 2018-09-19 Vahid Garousi , Michael Felderer , Mika V. Mäntylä

Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently manipulate texts and…

信息检索 · 计算机科学 2024-01-23 José de la Torre-López , Aurora Ramírez , José Raúl Romero

Systematic literature reviews (SLR) have been increasingly conducted in software engineering and they provide significant benefits in terms of summarizing the state of the research. The process of conducting SLR is complex, involving…

软件工程 · 计算机科学 2025-01-06 Vinicius dos Santos , Rick Kazman , Rafael Capilla , Elisa Yumi Nakagawa

[Background] Systematic literature reviews (SLRs) are essential for synthesizing evidence in Software Engineering (SE), but keeping them up-to-date requires substantial effort. Study selection, one of the most labor-intensive steps,…

This paper introduces an algorithmic framework for conducting systematic literature reviews (SLRs), designed to improve efficiency, reproducibility, and selection quality assessment in the literature review process. The proposed method…

综合金融 · 定量金融 2026-01-08 Gabin Taibi , Joerg Osterrieder

The creation of systematic literature reviews (SLR) is critical for analyzing the landscape of a research field and guiding future research directions. However, retrieving and filtering the literature corpus for an SLR is highly…

机器学习 · 计算机科学 2026-02-18 Lucas Joos , Daniel A. Keim , Maximilian T. Fischer

Systematic literature reviews (SLRs) are one of the most common and useful form of scientific research and publication. Tens of thousands of SLRs are published each year, and this rate is growing across all fields of science. Performing an…

人机交互 · 计算机科学 2018-03-28 Evgeny Krivosheev , Fabio Casati , Boualem Benatallah

Systematic literature reviews (SLRs) are at the heart of evidence-based research, setting the foundation for future research and practice. However, producing good quality timely contributions is a challenging and highly cognitive endeavor,…

数字图书馆 · 计算机科学 2020-12-16 Maisie Badami , Marcos Baez , Shayan Zamanirad , Wei Kang
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