Research & publications.
146 peer-reviewed works published between 2013–2026 — software security and vulnerability prediction, AI for software engineering, mining software repositories, empirical software quality, and software engineering education — plus 10 working papers from the 2026 programme on AI-native software engineering.
Ranked #10 worldwide and #1 in Saudi Arabia in Engineering Education and Technology in the Top1000 Scholar 2026 ranking — top 0.54%, impact score 96.41.
AI-native and agentic software engineering.
One question approached from nine directions: if agents write and maintain most of the code, what is left of the engineering discipline — and what has to change in architecture, lifecycle, governance and education? Published as working papers while under review.
- How AI Changes DevOps Performance: A Mechanism-Based SimulationarXiv:2609.32414
Separates AI-generated code from agentic AI and simulates their effect on all five DORA metrics — showing that delivery performance responds to AI through queueing, batching and oversight, not only code quality, with guardrails for agentic remediation and a field-validation protocol.
- The Rise of AI-Native Software EngineeringarXiv:2606.12986
A systematic review of 48 peer-reviewed studies (2016–2026) on what generative and agentic AI change for practice, competencies, professional roles and the outcomes universities must deliver.
- Rethinking Software Engineering for Agentic AI SystemsarXiv:2604.10599
If most code is machine-generated, should the discipline reorganise around orchestration, verification and human–AI collaboration — and what follows for education, tooling and process?
- Specification-Driven Development as the Foundation of AI-Native Enterprise Software EngineeringarXiv:2607.16680
Vibe coding versus specification-driven development: why structured specifications, not observed behaviour, have to be the authoritative source of truth at enterprise scale.
- From Determinism to DelegationarXiv:2606.28791
The emergence of the agentic engineer — how delegation to autonomous agents redraws the boundaries of engineering responsibility.
- Human–AI Collaboration and the Transformation of Software Engineering WorkarXiv:2606.03394
Evidence from large-scale observation of autonomous coding agents, and how the locus of engineering work shifts from individual productivity to orchestration, verification and governance.
- Reshaping the SDLC for Data- and AI-Centric SystemsarXiv:2608.17824
A five-layer adaptive lifecycle for systems whose behaviour emerges from code, data and learned models together — with evaluation-led specifications and validation gates.
- Educating the Agentic EngineerarXiv:2607.29610
Curricula, collaboration models and continuous learning for engineers whose job is to direct and verify AI systems.
- From Prompt-Response to Goal-Directed SystemsarXiv:2602.10479
Connecting classical agent architectures — reactive, deliberative, BDI — to today's LLM-centred agentic designs.
- Auditable DevOps Automation via VSM and GQMarXiv:2601.03574
A traceable framework that ties automation investment to delivery predictability, waste reduction and customer-facing quality.
Bibliometrics from Google Scholar; the publication list below is maintained by hand.
Indexed profiles.
Citation counts, co-author networks and full-text versions are maintained on the indexing services.