Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
PSL's invariant that every meaning field is always null has so far been applied within a single module at a time. This report generalizes it into an explicit architectural pattern -- a meaning-free core that is never modified, paired with a separable overlay (for machine-facing derived signals) or skin (for human-facing interpretation) that observes or annotates the core from the outside. We implement and verify two independent instances of this pattern. First, structural_time/realtime_overlay.py wraps CategoryDrift (StructuralTime's core drift tracker) without editing it, recording the correspondence between structural time (which advances only on update() calls) and wall-clock time, and computing whether the anomaly rate immediately after a large real-time gap differs from the baseline anomaly rate -- a concrete instrument for the open question of whether AI continuity leaves a measurable trace across session boundaries. Second, Fieldmap/skin.py renders a FieldMap (nodes, edges, and coupling matrices, with no field for content) as a human-readable 2D diagram, injecting node labels only at render time; we verify this against a real eight-node park FieldMap already used elsewhere in this project, confirming the underlying FieldMap/CategoryDrift classes are untouched. Both instances are motivated by a concrete, non-hypothetical case: production navigation systems already separate a meaning-free routing graph from a heavy, human-facing rendering layer, and the resource cost commonly attributed to that separation is in fact attributable to unrelated factors (planetary-scale graphs, live traffic data, and bundled unrelated services) rather than to the separation itself.
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.· arXiv.org· 727 citations· ⚡54
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.· Empirical Software Engineeri...· 401 citations· ⚡48
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.· Information and Software Tec...· 394 citations· ⚡54
The perception of the impact of agile methods is predominantly positive, and several challenge areas were discovered, but based on this study, agile methods are here to stay.
M. Laanti, O. Salo, P. Abrahamsson· Information and Software Tec...· 260 citations· ⚡20
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MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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