Semantically configurable software modelling notations and tools

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Errors in operational software significantly impact both users and software developers, in terms of rework to undo the effects of errors, extra work to avoid or mitigate errors, lost business due to shutdowns or delays in services, and increased customer support. Most of these errors are due to omissions, ambiguities, inconsistencies, or mistakes in the initial specification of what the software is to do, as opposed to design or coding errors introduced during development. Moreover, specification errors become more expensive to correct the later they are detected.Much of my research focuses on modelling and analyzing software specifications to detect errors in the early phases of software development, when errors are cheaper and easier to fix. For the past few years, my research group has been working on developing semantically configurable tools that support multiple modelling notations.  We have developed a way of structuring the definition of a modelling notation such that the definition can be interpreted and used to configure modelling tools, such as model editors and model verifiers.Continuing this research, I plan to study how to ease the task of configuring the definition of a new modelling notation.  I also intend to investigate whether our work can be adapted to accommodate heterogeneous models, thereby enabling specifiers to combine models written in different modelling notations.  In addition, I plan to explore ways of optimizing the performance of semantically configurable tools.This research will enable software specifiers to create their own modelling notations - that match the problems they are modelling and that domain experts can read and validate - but still have access to traditional tools for editing, manipulating, and checking their models.  Such technology will ultimately lead to improved software.