Ademar Aguiar

Abstract

Abstract
The development of safety-critical systems is heavily governed by domain-specific standards. In the aerospace industry, the DO-178C - Software Considerations in Airborne Systems and Equipment Certification - serves as the primary certification standard used by agencies such as the FAA and EASA to review and approve software-based systems. Although DO-178C aims to ensure system safety while providing evidence for certification, it does not prescribe a specific software development process, allowing flexibility for traditional Waterfall, Agile, or hybrid methods with appropriate adaptations for the aerospace context. This study proposes Scrum4DO178C, an Agile process based on Scrum, to meet the demanding requirements of aerospace software, including safety, robustness, reliability, and integrity. Scrum4DO178C introduces novel process enhancements specifically tailored to meet these criticality needs, while aligning with the standard. Unlike previous proposals that lack detail, this research presents a comprehensive, validated process applied in a real-world industry project at the highest criticality level (Level A - Catastrophic), offering insights beyond theoretical scenarios. The findings demonstrated that the Scrum4DO178C process improves project performance, allows frequent and manageable requirement changes, reduces Verification & Validation (V&V) effort, and increases efficiency while maintaining full compliance with DO-178C. The study also identifies areas for further improvement and suggests exploring the process in additional case studies, both within the aerospace industry and other domains with similarly stringent safety-critical requirements. Finally, it confirms that appropriate automation, namely for documentation production, is a central element to further improve the process. © 2013 IEEE.

Abstract

Abstract
Domain-specific standards and documents heavily regulate safety-critical systems. One example is the DO-178C standard for aerospace, which guides organizations to achieve system safety and evidence for their certification. Under such regulated contexts, most organizations use traditional development processes, in contrast to the massive adoption of Agile in the software industry. Among other benefits, Agile methods promise faster delivery and better flexibility to address customer needs. Adopting Agile methods and practices are possible in aerospace because the DO-178C standard does not prescribe concrete software development methods. In spite of that, Agile development is not used in DO-178C contexts. To help change that, our research aims to understand whether and how organizations engineering safety-critical software systems for aerospace may benefit from Agile methods and practices. We analyzed the DO-178C standard and confirm that it is compatible with Agile methods. Then, we present a systematic literature mapping of adopting Agile in software development for aerospace, where we identified significant concerns, recurrent issues, and several challenges. Some real industry aerospace projects provided us with important data and the perspective of domain experts about the pros and cons of Agile methods in this context. We conclude by proposing an agenda of research opportunities to improve safety-critical software development towards agility that we consider worthy of further research, application and confirmation in wider contexts.

Abstract
Reading, adapting, and maintaining complex software can be a daunting task. We might need to refactor it to streamline the process and make the code cleaner and self-explanatory. Traditional refactoring tools guide developers to achieve better-quality code. However, the feedback and assistance they provide can take considerable time. To tackle this issue, we explored the concept of Live Refactoring. This approach focuses on delivering real-time, visually-driven refactoring suggestions. That way, we prototyped a Live Refactoring Environment that visually identifies, recommends, and applies several refactorings in real-time. To validate its effectiveness, we conducted a set of experiments. Those showed that our approach significantly improved various code quality metrics and outperformed the results obtained from manually refactoring code.