@article {2026:fc4mc:jbcra,
	title = {Enhancing Transparency in Transaction Ordering: Dynamic Orderer Selection in Blockchain-driven Collaborative Processes},
	journal = {Blockchain: Research and Applications},
	year = {2025},
	chapter = {100412},
	abstract = {Supporting decentralized and trustless coordination among organizations, blockchain technology holds significant potential for addressing trust-related issues in inter-organizational collaborative processes. In this context, basic blockchain consensus mechanisms often introduce vulnerabilities, such as transaction reordering, manipulation, or censorship by malicious nodes, which can distort business objectives and undermine trust among collaborators.
This paper examines the influence of transaction ordering on decentralized business process choreography, highlighting competitive scenarios where malicious ordering can create unfair advantages. To counter such maximal extractable value attacks, we propose to align transaction ordering with business process logic with three novel strategies for process-aware transaction ordering. Our approach has proven effective in mitigating malicious transaction ordering, thereby enhancing fairness and transparency in the collaborative process execution. However, this comes with a trade-off in terms of time and computational cost, as observed in our extensive experimental evaluation.},
	keywords = {Block selection, blockchain, Process choreography, Transaction ordering Transparency},
	doi = {10.1016/j.bcra.2025.100412},
	author = {Hassan Atwi and Tom Lichtenstein and Cesare Pautasso and Mathias Weske}
}
@demo {2025:apiace:vissoft,
	title = {EVOSCAT: Exploring Software Change Dynamics in Large-Scale Historical Datasets},
	year = {2025},
	month = {September},
	publisher = {IEEE},
	address = {Auckland, New Zealand},
	abstract = {Long lived software projects encompass a large number of artifacts, which undergo many revisions throughout their history. Empirical software engineering researchers studying software evolution gather and collect datasets with millions of events, representing changes introduced to specific artifacts. In this paper, we propose EVOSCAT, a tool that attempts addressing temporal scalability through the usage of interactive density scatterplot to provide a global overview of large historical datasets mined from open source repositories in a single visualization.  EVOSCAT intends to provide researchers with a mean to produce scalable visualizations that can help them explore and characterize evolutions datasets, as well as comparing the histories of individual artifacts, both in terms of 1) observing how rapidly different artifacts age over multiple-year-long time spans 2) how often metrics associated with each artifacts tend towards an improvement or worsening. The paper shows how the tool can be tailored to specific analysis needs (pace of change comparison, clone detection, freshness assessment) thanks to its support for flexible configuration of history scaling and alignment along the time axis, artifacts sorting and interactive color mapping, enabling the analysis of millions of events obtained by mining the histories of tens of thousands of software artifacts. We include in this paper a gallery showcasing datasets gathering specific artifacts (OpenAPI descriptions, GitHub workflow definitions) across multiple repositories, as well as diving into the history of specific popular open source projects.},
	keywords = {Interactive Scatterplot, Large-Scale Historical Data, Software Evolution Visualization},
	doi = {10.1109/VISSOFT67405.2025.00021},
	url = {https://arxiv.org/abs/2508.10852},
	author = {Souhaila Serbout and Diana Carolina Mu{\~n}oz Hurtado and Hassan Atwi and Edoardo Riggio and Cesare Pautasso}
}
