相关论文: Learning From Software Failures: A Case Study at a…
The Department of Homeland Security in the United States estimates that 90% of software vulnerabilities can be traced back to defects in design and software coding. The financial impact of these vulnerabilities has been shown to exceed 380…
Software engineering is knowledge-intensive work, and how to manage software engineering knowledge has received much attention. This systematic review identifies empirical studies of knowledge management initiatives in software engineering,…
Scientific workflow has become essential in software engineering because it provides a structured approach to designing, executing, and analyzing scientific experiments. Software developers and researchers have developed hundreds of…
Software development, despite all the significant improvements it contributes to society, is a very expensive high-risk venture. Every software project commences with the intention to deliver a software product on time and within budget,…
Robots operating in unstructured human environments inevitably encounter failures, especially in robot caregiving scenarios. While humans can often help robots recover, excessive or poorly targeted queries impose unnecessary cognitive and…
Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in…
Security holds an important role in a software. Most people are not aware of the significance of security in software system and tend to assume that they will be fine without security in their software systems. However, the lack of security…
Large Language Models (LLMs) have shown strong potential in accelerating digital hardware design through automated code generation. Yet, ensuring their reliability remains a critical challenge, as existing LLMs trained on massive…
Large Language Models (LLMs) have shown remarkable capabilities in natural language understanding and generation, yet their deployment in enterprise environments reveals a critical limitation: inconsistent adherence to custom instructions.…
For many decades, formal methods are considered to be the way forward to help the software industry to make more reliable and trustworthy software. However, despite this strong belief and many individual success stories, no real change in…
The software ecosystem is a trust-rich part of the world. Collaboratively, software engineers trust major hubs in the ecosystem, such as package managers, repository services, and programming language ecosystems. This trust, however, is…
Context: Continuous practices, i.e., continuous integration, delivery, and deployment, are the software development industry practices that enable organizations to frequently and reliably release new features and products. With the…
Machine learning has the potential to fuel further advances in data science, but it is greatly hindered by an ad hoc design process, poor data hygiene, and a lack of statistical rigor in model evaluation. Recently, these issues have begun…
Not all research leads to fruitful results; trying new ways or methods may surpass the state of the art, but sometimes the hypothesis is not proven or the improvement is insignificant. In a systems discipline like pervasive computing, there…
CONTEXT: There is growing interest in establishing software engineering as an evidence-based discipline. To that end, replication is often used to gain confidence in empirical findings, as opposed to reproduction where the goal is showing…
Turnover consists of moving into and out of professional employees in the company in a given period. Such a phenomenon significantly impacts the software industry since it generates knowledge loss, delays in the schedule, and increased…
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…
As the role of information and communication technologies gradually increases in our lives, source code security becomes a significant issue to protect against malicious attempts Furthermore with the advent of data-driven techniques, there…
Development of machine learning (ML) applications is hard. Producing successful applications requires, among others, being deeply familiar with a variety of complex and quickly evolving application programming interfaces (APIs). It is…
One of the prerequisites of any organization is an unvarying sustainability in the dynamic and competitive industrial environment. Development of high quality software is therefore an inevitable constraint of any software industry. Defect…