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Hospital-acquired infections are nowadays a major health care problem worldwide. The morbidity and mortality associated with them are highest in intensive care units, but their effects are identifiable in virtually any medical department. Information about hospital-acquired infections, especially about their preventive measures, are rarely presented nowadays in a correct fashion to patients. This article aims to present, in a structured manner, the theoretical and practical aspects related to disclosure of hospital-acquired infections–related information to patients and its importance in preventing their spread. We will analyze both the conceptual framework for disclosing medical information related to nosocomial infections (autonomy, veracity, social justice, the principle of double effect, the precautionary principle, and nonmaleficence) and the practicalities regarding the disclosure of proper information to patients.

We present a longitudinal study on the long-term evolution of maintainability in open-source software. Quality assessment remains at the forefront of both software research and practice, with many models and assessment methodologies proposed and used over time. Some of them helped create and shape standards such as ISO 9126 and 25010, which are well established today. Both describe software quality in terms of characteristics such as reliability, security or maintainability. An important body of research exists linking these characteristics with software metrics, and proposing ways to automate quality assessment by aggregating software metric values into higher-level quality models. We employ the Maintainability Index, technical debt ratio and a maintainability model based on the ARiSA Compendium. Our study covers the entire 18 year development history and all released versions for three complex, open-source applications. We determine the maintainability for each version using the proposed models, we compare obtained results and use manual source code examination to put them into context. We examine the common development patterns of the target applications and study the relation between refactoring and maintainability. Finally, we study the strengths and weaknesses of each maintainability model using manual source code examination as the baseline.

Computing devices and associated software govern everyday life, and form the backbone of safety critical systems in banking, healthcare, automotive and other fields. Increasing system complexity, quickly evolving technologies and paradigm shifts have kept software quality research at the forefront. Standards such as ISO's 25010 express it in terms of sub-characteristics such as maintainability, reliability and security. A significant body of literature attempts to link these subcharacteristics with software metric values, with the end goal of creating a metricbased model of software product quality. However, research also identifies the most important existing barriers. Among them we mention the diversity of software application types, development platforms and languages. Additionally, unified definitions to make software metrics truly language-agnostic do not exist, and would be difficult to implement given programming language levels of variety. This is compounded by the fact that many existing studies do not detail their methodology and tooling, which precludes researchers from creating surveys to enable data analysis on a larger scale. In our paper, we propose a comprehensive study of metric values in the context of three complex, open-source applications. We align our methodology and tooling with that of existing research, and present it in detail in order to facilitate comparative evaluation. We study metric values during the entire 18-year development history of our target applications, in order to capture the longitudinal view that we found lacking in existing literature. We identify metric dependencies and check their consistency across applications and their versions. At each step, we carry out comparative evaluation with existing research and present our results.

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