Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
CCR 1.8.0 adds an explicit verified_growth_v1 policy while preserving the legacy v1 optimizer, signatures, admission, approval and lease boundaries. Replayable service/cost accounting, delayed reuse, immutable assets, receiver transfer qualification, and lifecycle invalidation/revalidation. Exact bounded dependency-bundle planning, independently checked reservations, verifier-service investment, conservative shared quotas and frozen restricted comparisons. Pinned, evidence-only CAIT/VEK/ALT interchange and packaged offline scenarios using ephemeral keys and real task/workcell transitions. Install with python -m pip install 'collective-capability-runtime[optimizer]==1.8.0', then run ccr optimizer growth-example --json. Distributed dependencies remain optional; Python 3.10+ support is retained. The supported initial checkpoint is empty evidence. Finite forecasts are not observations, asset count is not capital, and joint capacity and causal/statistical improvement remain unresolved. The reoptimized permitted reuse alternative matches the candidate in the packaged null comparison. No companion repository or production provider is modified or contacted. Validation and exact build/public-index receipts: https://github.com/kadubon/collective-capability-runtime/blob/main/docs/verified-growth-validation.md . Distribution assets and SHA256SUMS must match the same Trusted Publishing build; public-index verification is a separate post-publication state. No external empirical collective-intelligence acceleration experiment was performed for this release. The implementation supports evidence-bound coordination, bounded planning, qualified reuse, and reproducible software-level testing. It does not establish causal endogenous capability reproduction, AGI/ASI, indefinite growth, or correctness outside the declared evidence and model boundaries.
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 results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.
O. Salo, P. Abrahamsson· IET Software· 238 citations· ⚡9
Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· Journal of Systems and Softw...· 236 citations· ⚡13
The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
P. Abrahamsson, Antti Hanhineva, H. Hulkko et al.· Conference on Object-Oriente...· 225 citations· ⚡18
Related blog posts
Microsoft Research Blog· microsoft.comOct 30, 2026
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Microsoft Research Blog· microsoft.comOct 29, 2026
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.