Related papers: Towards Traceability in Data Ecosystems using a Bi…
Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating…
In a circular economy, tracking the flow of second-life components for quality control is critical. Tokenization can enhance the transparency of the flow of second-life components. However, simple tokenization does not correspond to real…
Software organizations are increasingly incorporating machine learning (ML) into their product offerings, driving a need for new data management tools. Many of these tools facilitate the initial development of ML applications, but…
Previous studies have shown that software traceability, the ability to link together related artifacts from different sources within a project (e.g., source code, use cases, documentation, etc.), improves project outcomes by assisting…
Modern software applications heavily rely on diverse third-party components, libraries, and frameworks sourced from various vendors and open source repositories, presenting a complex challenge for securing the software supply chain. To…
Despite Information and Communication Technologies (ICT) have reduced the information asymmetry and increased the degree of interorganizational collaboration, the companies participating a supply chain are less inclined to share data when…
In this paper we present the design and evaluation of a UAV-based system aimed at automating inventory tasks and keeping the traceability of industrial items attached to Radio-Frequency IDentification (RFID) tags. To confront current…
Software traceability is the process of establishing and maintaining relationships between artifacts in a software system. This process is crucial to many engineering processes, particularly for safety critical projects; however, it is…
In application domains that are regulated, software vendors must maintain traceability links between the regulatory items and the code base implementing them. In this paper, we present a traceability approach based on the intuition that the…
The state-of-the-art for auditing and reproducing scientific applications on high-performance computing (HPC) systems is through a data provenance subsystem. While recent advances in data provenance lie in reducing the performance overhead…
The food supply chain, following its globalization, has become very complex. Such complexities, introduce factors that influence adversely the quality of intermediate and final products. Strict constraints regarding parameters such as…
Blockchain technology has evolved from being an immutable ledger of transactions for cryptocurrencies to a programmable interactive the environment for building distributed reliable applications. Although, blockchain technology has been…
Practitioners are poorly supported by the scientific literature when managing traceability information models (TIMs), which capture the structure and semantics of trace links. In practice, companies manage their TIMs in very different ways,…
Social navigation and pedestrian behavior research has shifted towards machine learning-based methods and converged on the topic of modeling inter-pedestrian interactions and pedestrian-robot interactions. For this, large-scale datasets…
Easy access to data is one of the main avenues to accelerate scientific research. As a key element of scientific innovations, data sharing allows the reproduction of results, helps prevent data fabrication, falsification, and misuse.…
We present a methodology for evidence based design of cryptoeconomic systems, and elucidate a real-world example of how this methodology was used in the design of a blockchain network. This work provides a rare insight into the application…
Cryptocurrencies aim to replicate physical cash in the digital realm while removing centralized and trusted intermediaries. Decentralization is achieved by the blockchain, a permanent public ledger that contains a record of every…
The production, shipping, usage, and disposal of consumer goods have a substantial impact on greenhouse gas emissions and the depletion of resources. Machine Learning (ML) can help to foster sustainable consumption patterns by accounting…
Blockchain technology has evolved as a promising means to transform data management models in many domains including healthcare, agricultural research, tourism domains etc. In the research community, a usable blockchain-based system can…
The adoption of permissioned blockchain networks in enterprise settings has seen an increase in growth over the past few years. While encouraging, this is leading to the emergence of new data, asset and process silos limiting the potential…