Skip to content
#edge computing Open access

Analysis code and outputs: cryptocurrency designation reaches the addresses that moved the money, not the infrastructure that carries it

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

Code and analysis outputs supporting the manuscript. Every quantity reported in the paper is drawn from the JSON files in analysis/, each produced by a script in scripts/. The study uses three kinds of data: the complete on-chain USDT histories of the 490 addresses named in Israeli counter-terrorism seizure orders and of addresses listed under three OFAC programmes; two-hop transfer neighbourhoods crawled around those addresses; and the complete USDT transfer network on TRON to 1 January 2025, exported from an archival node with no seeding and no sampling (2,375,557,775 transfers, 15.5 trillion USDT, 744,543,633 unique directed pairs between 213,338,784 addresses). The distinction matters because a structural quantity measured in a crawled neighbourhood is not identified: the removal test reverses sign between the one-hop and two-hop boundaries in every sanctions network. Every structural claim in the paper is therefore made on the complete network. The intermediate network exports are large and are not included; the ClickHouse queries that produce them are in analysis/. Address-level role assignments and scores for undesignated addresses are deliberately not released. Version 1.1.0. Adds data/: the record-level inputs named in the manuscript's Data Availability statement — the complete USDT transfer histories of all 490 designated addresses, the Tether blacklist and fund-destruction event logs, the Aid for Ukraine Ethereum history, and the ClickHouse queries that produced them — together with the figure Source Data workbook, so that the analysis outputs can be recomputed rather than only re-read. Also corrects the throughput column of the complete-network removal table, which had included the stranded value, and regenerates the figures and tables affected. Version 1.1.1. Corrects two counts in the enforcement analysis: post-freeze receipts were read from the address-transfer frame, which holds transfers between two designated addresses twice (567 receipts of 10.9 million USDT, not 570 of 11.2 million), and the share of frozen addresses holding any balance was testing a difference of floating-point sums against zero (49% at a threshold of one base unit, not 53%). Adds the per-address and per-order arrays behind the redrawn figures, and regenerates the figures, tables and Source Data. Corresponds to GitHub tag v1.1.1. Version 1.1.2. Deposits the analysis outputs the deposited scripts read but the archive did not carry (zero_value_pairs.json, wcfrm_results.json, verified_metrics.json), so the figure Source Data can be regenerated from the archive alone; adds overflow_records.json and the script that produces it, giving per-network counts of the integer-overflow records dropped from each crawled network; corrects one Source Data sheet and the workbook README; and regenerates the figures. Corresponds to GitHub release v1.1.2. Version 1.1.3. Moves two figure annotations clear of their neighbours in the timing and enforcement figures. No analysis output changes. Corresponds to GitHub release v1.1.3. Version 1.2.0. Corrects the counterparty-persistence statistics, which were computed over every counterparty of a designated address rather than over those that dealt with it before its order: n = 20,295 rather than 22,637, 29% rather than 37% still transacting, 18% rather than 23% after 90 days, 58% rather than 64% of volume after the order. Records how concentrated the event study is (one order supplies 98% of pre-event volume) and the pre-trend in participation that the aggregate volume series does not show. Adds the value-carrying export query, which no deposited script previously produced although every value-weighted result depends on it; a path resolver so the scripts run directly from an extracted archive; the seizure-order list, anchor lists and crawled two-hop edge lists; and an analysis naming the complete network's highest-activity undesignated addresses, of which every labelled one is an exchange or payment processor. Figures revised throughout. Corresponds to GitHub release v1.2.0.

View source

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Related blog posts

GPT-Lab Sep 17, 2026

Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering

AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.

Microsoft Research Blog Aug 31, 2026

GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models

What if pathology foundation models could do more with less? GigaPath-Flash and GigaTIME-Flash cut computational demands while maintaining strong performance, opening the door to larger studies and broader exploration. The post GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.