Related papers: Landscaping Systematic Mapping Studies in Software…
Context: Behaviour Driven Development (BDD) uses scenarios written in semi-structured natural language to express software requirements in a way that can be understood by all stakeholders. The resulting natural language specifications can…
Platforms such as Stack Overflow are available for software practitioners to solicit solutions to their challenges and knowledge needs. The practices therein have in recent times however triggered quality related concerns. This is a…
With the increase of research in self-adaptive systems, there is a need to better understand the way research contributions are evaluated. Such insights will support researchers to better compare new findings when developing new knowledge…
Context: The utility of prediction models in empirical software engineering (ESE) is heavily reliant on the quality of the data used in building those models. Several data quality challenges such as noise, incompleteness, outliers and…
Software engineering (SE) is a dynamic field that involves multiple phases all of which are necessary to develop sustainable software systems. Machine learning (ML), a branch of artificial intelligence (AI), has drawn a lot of attention in…
A recent research trend has emerged to identify developers' emotions, by applying sentiment analysis to the content of communication traces left in collaborative development environments. Trying to overcome the limitations posed by using…
Containerization in multi-cloud environments has received significant attention in recent years both from academic research and industrial development perspectives. However, there exists no effort to systematically investigate the state of…
BACKGROUND: Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE: This paper aims to identify and…
Machine learning (ML) has been widely used in the literature to automate software engineering tasks. However, ML outcomes may be sensitive to randomization in data sampling mechanisms and learning procedures. To understand whether and how…
Data is a cornerstone of empirical software engineering (ESE) research and practice. Data underpin numerous process and project management activities, including the estimation of development effort and the prediction of the likely location…
Social Media Site (SMS) usage has grown rapidly in the last few years. This sudden increase in SMS usage creates an opportunity for data leakage which could compromise personal and/or professional life. In this work, we have reviewed…
One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently…
The use of AI in microservices (MSs) is an emerging field as indicated by a substantial number of surveys. However these surveys focus on a specific problem using specific AI techniques, therefore not fully capturing the growth of research…
With modern requirements, there is an increasing tendency of considering multiple objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a multi-objective optimization scenario comes with an important issue --…
This paper presents a systematic mapping study on the model-driven engineering of safety and security concerns in systems. Integrated modeling and development of both safety and security concerns is an emerging field of research. Our…
Large language models (LLMs) are gaining increasing popularity in software engineering (SE) due to their unprecedented performance across various applications. These models are increasingly being utilized for a range of SE tasks, including…
Model-driven engineering (MDE) is believed to have a significant impact in software quality. However, researchers and practitioners may have a hard time locating consolidated evidence on this impact, as the available information is…
Objective: To present an overview on the current state of the art concerning metrics-based quality evaluation of software components and component assemblies. Method: Comparison of several approaches available in the literature, using a…
Representative sampling appears rare in empirical software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This article therefore reports a…
Protocol for a Systematic Mapping of the Literature, which aims to identify and classify the estimations techniques used in software development agile methodologies based on the results found, and to compare their estimation accuracies…