Related papers: Software Supply Chain Attribute Integrity (SCAI)
Artificial Intelligence frameworks should allow for ever more autonomous and general systems in contrast to very narrow and restricted (human pre-defined) domain systems, in analogy to how the brain works. Self-constructive Artificial…
Context: In continuous deployment, software and services are rapidly deployed to end-users using an automated deployment pipeline. Defects in infrastructure as code (IaC) scripts can hinder the reliability of the automated deployment…
Software metrics offer a quantitative basis for predicting the software development process. In this way, software quality can be improved very easily. Software quality should be achieved to satisfy the customer with decreasing the software…
In recent years, defect prediction has received a great deal of attention in the empirical software engineering world. Predicting software defects before the maintenance phase is very important not only to decrease the maintenance costs but…
The process of creating working software from source code and other components (like libraries, database files, etc.) is called "software build". Apart from linking and compiling, it can include other steps like automated testing, static…
Systems Engineering (SE) is the set of processes and documentation required for successfully realising large-scale engineering projects, but the classical approach is not a good fit for software-intensive projects, especially when the needs…
Software is a central part of modern science, and knowledge of its use is crucial for the scientific community with respect to reproducibility and attribution of its developers. Several studies have investigated in-text mentions of software…
Software Quality Assurance (SQA) and Software Process Improvement (SPI) are topics of crucial importance for software engineers; however, teaching them in a lecture room comes with several limitations due to lack of practical experience.…
Spatial Representations for Artificial Intelligence (srai) is a Python library for working with geospatial data. The library can download geospatial data, split a given area into micro-regions using multiple algorithms and train an…
Many software products are composed of components integrated from other teams or external parties. Each additional link in a software product's supply chain increases the risk of the injection of malicious behavior. To improve supply chain…
Artificial Intelligence (AI) systems are increasingly dependent on complex, multi-layered software supply chains that introduce challenges for reproducibility, transparency, and security assurance. This study presents an Artificial…
Software Quality Assurance (SQA) planning aims to define proactive plans, such as defining maximum file size, to prevent the occurrence of software defects in future releases. To aid this, defect prediction models have been proposed to…
Scientific advancement relies on the ability to share and reproduce results. When data analysis or calculations are carried out using software written by scientists there are special challenges around code versions, quality and code…
Data quality describes the degree to which data meet specific requirements and are fit for use by humans and/or downstream tasks (e.g., artificial intelligence). Data quality can be assessed across multiple high-level concepts called…
In Software Engineering, early detection of architectural issues is key. It helps mitigate the risk of poor performance, and lowers the cost of repairing these issues. Metrics give a quick overview of the project which helps designers with…
Among the entities involved in software citation, software source code requires special attention, due to the role it plays in ensuring scientific reproducibility. To reference source code we need identifiers that are not only unique and…
With the increasing adoption of Continuous Integration and Continuous Deployment pipelines, securing software supply chains has become a critical challenge for modern DevOps teams. This study addresses these challenges by applying a…
The SolarWinds attack, which exploited weaknesses in a software update mechanism, highlights the critical need for organizations to have better visibility into their software dependencies and potential vulnerabilities associated with them.…
Internal software quality determines the maintainability of the software product and influences the quality in use. There is a plethora of metrics which purport to measure the internal quality of software, and these metrics are offered by…
The increased use of AI systems is associated with multi-faceted societal, environmental, and economic consequences. These include non-transparent decision-making processes, discrimination, increasing inequalities, rising energy consumption…