Skip to content
#large language models Dataset Open access

FPA supplementary derivations for FPA-FRESHNESS-PORTABILITY-003

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research) · 1 citation
Logic, programming, and type systems

Abstract

This supplement records five additional target paradigms for the Freshness Portability Agent (FPA-FRESHNESS-PORTABILITY-003): Common Lisp, Brainfuck, spreadsheet formulas, an Analytical Engine-style program, and AWK. It is separate from the canonical FPA package and its Non-Normative Tests (NNT) companion. The supplement Manifest names and hashes the canonical FPA package Manifest as its parent artifact. The FPA Specification, Conformance Tests, Semantic Index, Coverage Matrix, and Ambiguity Register define the rules and acceptance criteria. Integrity. Freshness_Portability_Agent_Supplement.zip, 22 files, SHA-256 0d72c75d10ab3f3afb54730e23272e0e2e59f9a50daa7af939ffe07d6a704828. Supplement Manifest (FPA_Supplement_Manifest.json), SHA-256 86b7db7de10889366fc1b6b6dd9fe45cf47c0c9b0eff2de6de97144df01664c6; its parent is the FPA package Manifest, manifest_ref e8c2e05e564eaa83a1a0853350661b056f7716175586684d100c5b9b2fcfe0b0. The FPA package is archived as a separate record: https://doi.org/10.5281/zenodo.23390618. Use of AI tools. The author designed and calibrated the harnesses of the derivations in this supplement. Large language models were used openly, as tools to accelerate research and production, with manual review: they produced the renderings (Common Lisp, Brainfuck, spreadsheet formulas, an Analytical Engine-style program and AWK) and the comparators (the Rust rendering and the reference output spec_252.txt) in an AI-provider environment, as the study artifacts reported in Section 6 of the article; they are not reference implementations. No tool is an author; the author is accountable for the content. What matters is not which tools touched the files but whether they can be verified: the supplement has its own Manifest, which names the pack Manifest as its parent.

View source

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Conference Open access Dec 2013

Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment

The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.

P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al. · 110 citations · ⚡7
#computer vision Review Open access May 2017

Are Software Startups Applying Agile Practices? The State of the Practice from a Large Survey

The findings show that speed related agile practices are used to a greater extent in comparison to quality practices, and that software startups who adopt the Lean Startup approach do not sacrifice quality for speed more than other startups do.

Jevgenija Pantiuchina, Marco Mondini, Dron Khanna et al. · 84 citations · ⚡4

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar 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.