Software

Graph generalization is a powerful concept with a wide range of potential applications, while established algorithms exist for generalizing simple graphs, practical approaches for more complex graphs remain elusive. We introduce a novel formal model and algorithm (GGA) that generalizes labeled directed graphs without assuming label identity. We evaluate GGA by focusing on its information preservation relative to its input graphs, its scalability in execution, and its utility for three applications: abstract syntax trees, class graphs, and call graphs. Our findings reveal the superiority of GGA over alternative tools. GGA outperforms ASGard by an average of 5–18% on metrics related to information preservation; GGA matches 100% with diffsitter, indicating the correctness of the output. For class graphs, GGA achieves 77.1% in precision at 5, while for call graphs, it exhibits 60% in precision at 5 for a specific application problem. We also test performance for the first two applications: GGA’s execution time scales linearly with respect to the product of vertex count and edge count. Our research demonstrates the ability of GGA to preserve information in diverse applications while performing efficiently, signaling its potential to advance the field.

Regulated web systems require traceable, rollback-safe UI delivery, yet conventional static deployments and Boolean flagging struggle to provide per-user versioning, deterministic fallbacks, and audit-grade observability. The objective of this research is to develop and validate a runtime frontend architecture that enables per-session component versioning with deterministic fallbacks and audit-grade traceability for regulated systems. We present a dynamic frontend architecture that integrates typed GraphQL flag schemas, runtime module federation, and structured observability to enable per-session and per-route component versioning with deterministic fallbacks. We formalize a version-resolution function v = f(u, r, t) and implement a production system that achieved a 96% reduction in MTTR, a P90 fallback rate below 0.7%, and over 280 k session-level logs across 45 days. Compared to static delivery and standard flag evaluators, our approach adds schema-driven targeting, component-level isolation, and audit-ready render traces suitable for compliance. Limitations include cold-start overhead and governance complexity; we provide mitigation strategies and discuss portability beyond fintech.

Organizations increasingly rely on Agile software development to navigate the complexities of digital transformation. Agile emphasizes flexibility, empowerment, and emergent design, yet large-scale initiatives often extend beyond single teams to include multiple subsidiaries, business units, and regulatory stakeholders. In such contexts, team-level mechanisms such as retrospectives, backlog refinement, and planning events may prove insufficient to achieve alignment across diverse perspectives, organizational boundaries, and compliance requirements. To address this limitation, this paper introduces a complementary framework and a supporting software tool that enable systematic cross-stakeholder alignment. Rather than replacing Agile practices, the framework enhances them by capturing heterogeneous stakeholder views, surfacing tacit knowledge, and systematically reconciling differences into a shared alignment artifact. The methodology combines individual Functional Resonance Analysis Method (FRAM)-based process modeling, iterative harmonization, and an evidence-supported selection mechanism driven by quantifiable performance indicators, all operationalized through a prototype tool. The approach was evaluated in a real industrial case study within the regulated gaming sector, involving practitioners from both a parent company and a subsidiary. The results show that the methodology effectively revealed misalignments among stakeholders’ respective views of the development process, supported structured negotiation to reconcile these differences, and produced a consolidated process model that improved transparency and alignment across organizational boundaries. The study demonstrates the practical viability of the methodology and its value as a complementary mechanism that strengthens Agile ways of working in complex, multi-stakeholder environments.