Related papers: Enterprise-Driven Open Source Software: A Case Stu…
In modern software development workflows, the open-source software supply chain contributes significantly to efficient and convenient engineering practices. With increasing system complexity, using open-source software as third-party…
Business success of companies heavily depends on the availability and performance of their client applications. Due to modern development paradigms such as DevOps and microservice architectural styles, applications are decoupled into…
Background: Continuous Integration (CI) systems are now the bedrock of several software development practices. Several tools such as TravisCI, CircleCI, and Hudson, that implement CI practices, are commonly adopted by software engineers.…
DevOps is a modern software engineering paradigm that is gaining widespread adoption in industry. The goal of DevOps is to bring software changes into production with a high frequency and fast feedback cycles. This conflicts with software…
Invisible labor is work that is either not fully visible or not appropriately compensated. In open source software (OSS) ecosystems, essential tasks that do not involve code (like content moderation) often become invisible to the detriment…
In this paper, we study the benefits and challenges of monitoring Continuous Integration (CI) practices in software development. Our aim is to evaluate the impact of monitoring seven CI practices in industry using three organizations in…
This research, undertaken in highly structured software-intensive organizations, outlines challenges associated to agile, lean and DevOps practices and principles adoption. The approach collected data via a series of thirty (30) interviews,…
Recent trends in the software engineering (i.e., Agile, DevOps) have shortened the development life-cycle limiting resources spent on security analysis of software designs. In this context, architecture models are (often manually) analyzed…
Automated machine learning (AutoML) has emerged as a promising paradigm for automating machine learning (ML) pipeline design, broadening AI adoption. Yet its reliability in complex domains such as cybersecurity remains underexplored. This…
Secure applications implement software protections against side-channel and physical attacks. Such protections are meaningful at machine code or micro-architectural level, but they typically do not carry observable semantics at source…
Modern organizations increasingly rely on log data and monitoring signals to protect products against account takeovers and abuse, yet integrating security analytics into fast-moving Agile workflows remains challenging. While it is…
The digital economy runs on Open Source Software (OSS), with an estimated 90\% of modern applications containing open-source components. While this widespread adoption has revolutionized software development, it has also created critical…
BACKGROUND: Vulnerable dependencies are a known problem in today's open-source software ecosystems because OSS libraries are highly interconnected and developers do not always update their dependencies. AIMS: In this paper we aim to present…
Open source software (OSS) forms the backbone of industrial data workflows and enterprise systems. However, many OSS projects face operational risks due to informal or centralized governance. This paper presents a practical case study of…
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…
Caveat emptor, or let the buyer beware, is commonly attributed to open source software (OSS)-the onus is on the OSS consumer to ensure that it is fit for use in the consumer's context. OSS has been compared to an open market bazaar where…
The acceleration of software development and delivery requires rigorous continuous testing and deployment of software systems, which are being deployed in increasingly diverse, complex, and dynamic environments. In recent years, the…
Development of scientific and engineering software is usually different and could be more challenging than the development of conventional enterprise software. The authors were involved in a technology-transfer project between academia and…
Open Source Software (OSS) history is traced to initial efforts in 1971 at Massachusetts Institute of Technology (MIT) Artificial Intelligence (AI) Lab, the initial goals of OSS around Free vs. Freedom, and its evolution and impact on…
Several studies have revealed the fact that nearly two-thirds of all software process improvement (SPI) efforts have failed or have at least fallen short of expectations. Literature and practice have shown that commitment to SPI at all…