Academic Journal
Application Generators in Enterprise Front-End Platforms: Architectural Principles, Governance Patterns, and Sustainable Delivery.
| Τίτλος: | Application Generators in Enterprise Front-End Platforms: Architectural Principles, Governance Patterns, and Sustainable Delivery. |
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| Συγγραφείς: | Chennuru, Anilraj |
| Πηγή: | International Journal of Computer Information Systems & Industrial Management Applications; 2026 Supplement, Vol. 18, p322-335, 14p |
| Θεματικοί όροι: | Program generators (Computer programs), Computer software development, Software engineering, Artificial intelligence, Software frameworks |
| Περίληψη: | Enterprise front-end development at scale is characterized by a persistent tension between the need for organizational consistency and the demand for product-team autonomy. Left unresolved, this tension produces fragmented codebases, duplicated infrastructure decisions, inconsistent security postures, and compounding onboarding costs. Application generators address this problem by encoding architectural standards, security defaults, and delivery contracts directly into the project creation process. Rather than relying on documentation and developer discipline to propagate platform conventions, generators make correct behavior the automatic outcome of project initialization. This article examines application generators as first-class platform infrastructure across their full operational lifecycle. The scope covers scaffold design and baseline contract definition, governance and security enforcement through generated defaults, extensibility architecture that preserves product-team autonomy without sacrificing platform coherence, pipeline and observability integration, developer experience as a technical requirement, shared asset distribution, and the governance models required to prevent generator sprawl. The article further addresses the implications of AI-assisted development for generator design, arguing that embedded static analysis and dependency governance become especially critical as AI-generated code enters enterprise codebases at an increasing rate. The article establishes that generator value is not realized at project creation alone. It builds up over time through consistent delivery pipelines, less time spent on compliance remediation, faster onboarding, and measuring at the portfolio level. Sustaining that value requires treating the generator as a versioned, owned, and actively maintained platform product, governed by the same rigor applied to the applications it produces. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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