Building trustworthy evidence in Software Engineering and Digital Forensics
I am Edson OliveiraJr, Associate Professor of Software Engineering at the State University of Maringá (UEM), Brazil.
I investigate how empirical methods, open science, and reproducible research practices can strengthen the evidence we produce and use in Software Engineering and Digital Forensics.
My research focuses on the design, execution, and evaluation of controlled experiments and quasi-experiments, as well as on the development of research artifacts, metadata, conceptual models, and ontologies that support transparency, traceability, and long-term reuse.
A central question guides my work: How can we make scientific evidence more trustworthy, reproducible, and useful for research and practice?
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Selected Research Contributions
My research connects empirical methods, open science, and software modeling through three complementary areas of contribution.
Open and Reproducible Experimentation
Methods, metadata, and conceptual models to support the planning, reporting, sharing, and reuse of controlled experiments and quasi-experiments in Software Engineering. This work connects methodological rigor with practical support for transparent research.
Evidence-Based Digital Forensics
Research on experimental protocols, ontologies, and methodological foundations for Digital Forensics. This work examines how experimental rigor, provenance, and traceability can support the assessment and reproducibility of forensic research.
UML-Based Variability Management
The SMarty approach and related methods and tools for modeling, inspecting, and evaluating variability in UML-based software product lines. This work combines software modeling with empirical evaluation to support systematic variability management.
Current Research Agenda
My current research explores how scientific evidence can be produced, assessed, and reused with greater transparency and methodological rigor. Three questions guide this agenda:
How can reproducibility be built into empirical studies from the beginning?
I investigate how experimental protocols, metadata, and data management practices can support the research lifecycle, from study planning to the sharing and reuse of results and artifacts.
How can software systems be designed to support forensic readiness?
I explore how software engineering practices can support the availability, provenance, and traceability of digital evidence, connecting forensic requirements with software design, development, and evolution.
What makes research artifacts understandable and reusable?
I study how documentation, metadata, and sharing practices can preserve the context needed to interpret, assess, and reuse research artifacts in Software Engineering and Digital Forensics.