相关论文: Towards Continuous Systematic Literature Review in…

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…

Context: Study screening in systematic literature reviews is costly, inconsistency-prone, and risk-asymmetric, since false negatives can compromise validity. Despite rapid uptake of Large Language Models (LLMs), there is limited evidence on…

Literature reviews are an essential component of scientific research, but they remain time-intensive and challenging to write, especially due to the recent influx of research papers. This paper explores the zero-shot abilities of recent…

Identifying the main contributions related to the Automated Test Production (ATP) of Computer Programs and providing an overview about models, methodologies and tools used for this purpose is the aim of this Systematic Literature Review…

The rapid integration of Large Language Models (LLMs) into software engineering (SE) has revolutionized tasks like code generation, producing a massive volume of software artifacts. This surge has exposed a critical bottleneck: the lack of…

Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarkable success of Large Language Models (LLMs), they face…

Despite potential benefits in Software Engineering (SE), adoption of software modelling in industry is low. Technical issues such as tool support have gained significant research before, but individual guidance and training have received…

Managing models in a consistent manner is an important task in the field of Model-Driven Engineering (MDE). Although restoring and maintaining consistency is desired in general, recent work has pointed out that always strictly enforcing…

The exponential growth of financial research has rendered traditional systematic literature reviews (SLRs) increasingly impractical, as manual screening and narrative synthesis struggle to keep pace with the scale and complexity of modern…

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…

Despite a growing ecosystem of tools supporting Systematic Literature Reviews (SLRs), integrating them into user-friendly workflows remains challenging. The Streamlined Workflow for Automating Machine-Actionable Systematic Literature…

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…

[Context] Large Language Models (LLMs) are increasingly used to assist qualitative research in Software Engineering (SE), yet the methodological implications of this usage remain underexplored. Their integration into interpretive processes…

The sheer number of research outputs published every year makes systematic reviewing increasingly time- and resource-intensive. This paper explores the use of machine learning techniques to help navigate the systematic review process. ML…

In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to use LLMs for supporting research or software engineering…

Computing Education Research (CER) is critical for supporting the increasing number of students who need to learn computing skills. To systematically advance knowledge, publications must be clear enough to support replications,…

Unit testing is a fundamental practice in modern software engineering, with the aim of ensuring the correctness, maintainability, and reliability of individual software components. Very recently, with the advances in Large Language Models…

Large Language Models (LLMs) are increasingly embedded in software engineering (SE) tools, powering applications such as code generation, automated code review, and bug triage. As these LLM-based AI for Software Engineering (AI4SE) systems…

Context: Model-Driven Security (MDS) is as a specialised Model-Driven Engineering research area for supporting the development of secure systems. Over a decade of research on MDS has resulted in a large number of publications. Objective: To…

Peer review is essential for scientific progress but faces growing challenges due to increasing submission volumes and reviewer fatigue. Existing automated review approaches struggle with factual accuracy, rating consistency, and analytical…