Related papers: Modelling Guidance in Software Engineering: A Syst…
Software applications often pose barriers for users with accessibility needs, e.g., visual impairments. Model-driven engineering (MDE), with its systematic nature of code derivation, offers systematic methods to integrate accessibility…
Reference management software is a well-known tool for scientific research work. Since the 1980s, it has been the subject of reviews and evaluations in library and information science literature. This paper presents a systematic review of…
This paper reports our extended analysis of the recent literature addressing global software engineering (GSE), using a new Systematic Snapshot Mapping (SSM) technique. The primary purpose of this work is to understand what issues are being…
Most university curricula consider software processes to be on the fringes of software engineering (SE). Students are told there exists a plethora of software processes ranging from RUP over V-shaped processes to agile methods. Furthermore,…
Software engineering (SE) faces significant diversity challenges in both academia and industry, with underrepresented students encountering hostile environments, limited representation, and systemic biases that hinder their academic and…
Nowadays, machine learning (ML) is being used in software systems with multiple application fields, from medicine to software engineering (SE). On the one hand, the popularity of ML in the industry can be seen in the statistics showing its…
The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practice. While top-tier SE venues continue to show sustained or…
Teaching the software engineers of the future to write high-quality code with good style and structure is important. This systematic literature review identifies existing instructional approaches, their objectives, and the strategies used…
Modelling and thus metamodelling have become increasingly important in Software Engineering through the use of Model Driven Engineering. In this paper we present a systematic literature review of instance generation techniques for…
Actually, software products are increasing in a fast way and are used in almost all activities of human life. Consequently measuring and evaluating the quality of a software product has become a critical task for many companies. Several…
Background. Due to the widespread adoption of Artificial Intelligence (AI) and Machine Learning (ML) for building software applications, companies are struggling to recruit employees with a deep understanding of such technologies. In this…
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…
Failure studies are important in revealing the root causes, behaviors, and life cycle of defects in software systems. These studies either focus on understanding the characteristics of defects in specific classes of systems or the…
The increasing availability of data and advancements in computational intelligence have accelerated the adoption of data-driven methods (DDMs) in product development. However, their integration into product development remains fragmented.…
Software engineering research benefited for decades from openly available tools, accessible systems, and problems that could be studied at modest scale. Today, many of the most relevant software systems are large, proprietary, and embedded…
In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In…
Novice programmers benefit from timely, personalized support that addresses individual learning gaps, yet the availability of instructors and teaching assistants is inherently limited. Large language models (LLMs) present opportunities to…
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…
Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in text generation and reasoning tasks. Derivative products, like ChatGPT, have been extensively deployed and highly sought after.…
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs'…