Automated Adaptive Software Maintenance: A Methodology and Its Applications

In modern software development, maintenance accounts for the majority of the total cost and effort in a software project. Especially burdensome are those tasks which require applying a new technology in order to adapt an application to changed requirements or a different environment. This research explores methodologies, techniques, and approaches for automating such adap-tive maintenance tasks. By combining high-level specifications and generative techniques, a new methodology shapes the design of approaches to automating adaptive maintenance tasks in the application domains of high performance computing (HPC) and enterprise software. Despite the vast differences of these domains and their respective requirements, each approach is shown to be effective at alleviating their adaptive maintenance burden. This thesis proves that it is possible to effectively automate tedious and error-prone adaptive maintenance tasks in a diverse set of domains by exploiting high-level specifications to synthesize specialized low-level code. The specific contributions of this thesis are as follows: (1) a common methodology for designing automated approaches to adaptive maintenance, (2) a novel approach to automating the generation of efficient marshaling logic for HPC applications from a high-level visual model, and (3) a novel approach to automatically upgrading legacy enterprise applications to use annotation-based frameworks. The technical contributions of this thesis have been realized in two software tools for automated adaptive maintenance: MPI Serializer, a marshaling logic generator for MPI applications , and Rosemari, an inference and transformation engine for upgrading enterprise applications. This thesis is based on research papers accepted to IPDPS '08 [93] and OOPSLA '08 [92]. iii Acknowledgments No grad student is an island, and I am surely no exception. My friends, family, and colleagues have ameliorated my life and I truly appreciate the kindness they all have shown me. I would like to take this opportunity to thank many of those who have aided me in one way or another along the way. The never-ending support and love of my parents has sustained, comforted, and driven me throughout my life. Any accomplishments that I have achieved in my time here at Virginia Tech would not have been possible if I did not have them by my side. They are the most caring, loving, and genuine people I have ever known. The faith that both my brother and sister have had in me spurred me on through the most difficult challenges. For the five years that I have known her, Lindsay La Forge has …