相关论文: Second Product Line Practice Workshop Report
Context: software projects are common resources in Software Engineering experiments, although these are often selected without following a specific strategy, which reduces the representativeness and replication of the results. An option is…
Software Product Lines SPL are recognized as a successful approach to reuse in software development.Its purpose is to reduce production costs. This approach allows products to be different with respect of particular characteristics and…
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…
Context: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by…
Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project…
As any scientific discipline, the software engineering (SE) research community strives to contribute to the betterment of the target population of our research: software producers and consumers. We will only achieve this betterment if we…
Context: Evidence-based software engineering (EBSE) can be an effective resource to bridge the gap between academia and industry by balancing research of practical relevance and academic rigor. To achieve this, it seems necessary to…
Context: Over the past decade Software Engineering research has seen a steady increase in survey-based studies, and there are several guidelines providing support for those willing to carry out surveys. The need for auditing survey research…
In the last couple of years we have witnessed an enormous increase of machine learning (ML) applications. More and more program functions are no longer written in code, but learnt from a huge amount of data samples using an ML algorithm.…
This article summarizes motivations, organization, and activities of the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1) held in Manchester, UK in September 2017. The WSSSPE series promotes sustainable…
In the last 15 years, software architecture has emerged as an important software engineering field for managing the development and maintenance of large, software- intensive systems. Software architecture community has developed numerous…
Integrating research evidence into practice is one of the main goals of Evidence-Based Software Engineering (EBSE). Secondary studies, one of the main EBSE products, are intended to summarize the best research evidence and make them easily…
Software Engineering is a constantly evolving subject area that faces new challenges every day as it tries to automate newer business processes. One of the key challenges to the success of a software solution is attaining sustainability.…
Sentiment analysis methods have become popular for investigating human communication, including discussions related to software projects. Since general-purpose sentiment analysis tools do not fit well with the information exchanged by…
Product Line Engineering (PLE) is a crucial practice in many software development environments where software systems are complex and developed for multiple customers with varying needs. At the same time, many development processes are use…
It is well known that the software process impacts the quality of the resulting product. There are also anecdotal claims that agile processes result in higher level of quality than traditional methodologies. However, still solid evidence of…
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…
Currently, software industries are using different SDLC (software development life cycle) models which are designed for specific purposes. The use of technology is booming in every perspective of life and the software behind the technology…
The number of machine learning, artificial intelligence or data science related software engineering projects using Agile methodology is increasing. However, there are very few studies on how such projects work in practice. In this paper,…
We studied scientists who attended two-day workshops on basic software skills to determine which tools and practices they found most useful. Our pre- and post-workshop surveys showed increases in self-reported familiarity, while our…