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[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,…

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…

Software Engineering · Computer Science 2026-01-30 Henry Edison , Nauman Ali

Understanding software faults is essential for empirical research in software development and maintenance. However, traditional fault analysis, while valuable, typically involves multiple expert-driven steps such as collecting potential…

Software Engineering · Computer Science 2025-10-07 Jiongchi Yu , Weipeng Jiang , Xiaoyu Zhang , Qiang Hu , Xiaofei Xie , Chao Shen

Literature reviews can be time-consuming and tedious to complete. By cataloging and refactoring three state-of-the-art active learning techniques from evidence-based medicine and legal electronic discovery, this paper finds and implements…

Software Engineering · Computer Science 2018-03-09 Zhe Yu , Nicholas A. Kraft , Tim Menzies

We report on the state-of-the-art of software visualization. To ensure reproducibility, we adopted the Systematic Literature Review methodology. That is, we analyzed 1440 entries from IEEE Xplore and ACM Digital Library databases. We…

Software Engineering · Computer Science 2020-06-23 Noptanit Chotisarn , Leonel Merino , Xu Zheng , Supaporn Lonapalawong , Tianye Zhang , Mingliang Xu , Wei Chen

Systematic reviews are essential to summarizing the results of different clinical and social science studies. The first step in a systematic review task is to identify all the studies relevant to the review. The task of identifying relevant…

Information Retrieval · Computer Science 2018-01-30 Gaurav Singh , James Thomas , John Shawe-Taylor

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…

Systematic literature reviews (SLRs) are essential but labor-intensive due to high publication volumes and inefficient keyword-based filtering. To streamline this process, we evaluate Large Language Models (LLMs) for enhancing efficiency…

Machine Learning · Computer Science 2025-06-17 Lucas Joos , Daniel A. Keim , Maximilian T. Fischer

Scientific writing builds upon already published papers. Manual identification of publications to read, cite or consider as related papers relies on a researcher's ability to identify fitting keywords or initial papers from which a…

Digital Libraries · Computer Science 2022-09-08 Christin Katharina Kreutz , Ralf Schenkel

Automatic reviewing helps handle a large volume of papers, provides early feedback and quality control, reduces bias, and allows the analysis of trends. We evaluate the alignment of automatic paper reviews with human reviews using an arena…

Context: The constant growth of primary evidence and Systematic Literature Reviews (SLRs) publications in the Software Engineering (SE) field leads to the need for SLR Updates. However, searching and selecting evidence for SLR updates…

Software Engineering · Computer Science 2024-02-09 Bianca Minetto Napoleão , Ritika Sarkar , Sylvain Hallé , Fabio Petrillo , Marcos Kalinowski

The exponential growth of scientific production makes secondary literature abridgements increasingly demanding. We introduce a new open-source framework for systematic reviews that significantly reduces time and workload for collecting and…

Digital Libraries · Computer Science 2022-02-24 Angelo D'Ambrosio , Hajo Grundmann , Tjibbe Donker

Systematic Literature Reviews aim at investigating current approaches to conclude a research gap or determine a futuristic approach. They represent a significant part of a research activity, from which new concepts stem. However, with the…

Digital Libraries · Computer Science 2022-08-05 Nada Sahlab , Hesham Kahoul , Nasser Jazdi , Michael Weyrich

Background: Academic search engines (i.e., digital libraries and indexers) play an increasingly important role in systematic reviews however these engines do not seem to effectively support such reviews, e.g., researchers confront usability…

Software Engineering · Computer Science 2022-11-02 Zheng Li , Austen Rainer

As academic literature proliferates, traditional review methods are increasingly challenged by the sheer volume and diversity of available research. This article presents a study that aims to address these challenges by enhancing the…

Context: Artificial intelligence (AI) has made its way into everyday activities, particularly through new techniques such as machine learning (ML). These techniques are implementable with little domain knowledge. This, combined with the…

Software Engineering · Computer Science 2021-09-17 Lalli Myllyaho , Mikko Raatikainen , Tomi Männistö , Tommi Mikkonen , Jukka K. Nurminen

Recent advancements in large language models have sparked interest in utilizing them to aid the peer review process of scientific publication amid the peer review crisis. However, having AI models generate full reviews in the same way as…

Computation and Language · Computer Science 2026-04-03 Tianmai M. Zhang , Neil F. Abernethy

Context. Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, they use a well-defined methodology meant to mitigate the…

Software Engineering · Computer Science 2019-08-20 Francesco Osborne , Henry Muccini , Patricia Lago , Enrico Motta

Systematic literature reviews are essential for synthesizing scientific evidence but are costly, difficult to scale and time-intensive, creating bottlenecks for evidence-based policy. We study whether large language models can automate the…

Systematic literature studies have received much attention in empirical software engineering in recent years. They have become a powerful tool to collect and structure reported knowledge in a systematic and reproducible way. We distinguish…

Software Engineering · Computer Science 2016-12-13 M. Kuhrmann , D. Méndez Fernández , M. Daneva