Software Engineering Research

The ISS software engineering research team aims at creating and adapting innovative techniques and tools that will lead to better quality products and more productive developers.

Our research currently focuses on:

Software Testing
Our research in software testing aims to improve our ability to detect defects before release, as well as push defect detection as early as possible. To this end, we create and adapt techniques that automate test input generation and create GUI test scripts.
We collaborate with a number of researchers, including:

Software Maintenance
Our research seeks to reduce the cost of ABB’s software maintenance activities by leveraging advanced techniques and tools. We focus on improving developer productivity, automating redundant tasks, enabling maintenance decisions based on improved information, and try to identify and remove redundant functionality from common products.
We collaborate with a number of researchers, including: Decision Support
Our research in predictive models focuses on the generation of robust measurements of software development artifacts that provide decision support for project and product level operational decisions, as well as to support development improvement programs. Techniques explored in this research include the following:
  • Researching decision support models that optimize long-run product quality or productivity improvement initiatives to maximize profitability of software intensive products.
  • Defining decision guidance for business decision points based on key project operational measurements.
  • Defining decision support for design alterative selection and verification prioritization based on source code change history artifacts and static complexity metrics.
  • Creating automated techniques to capture usage patterns that guide decisions on development features, training focus, and verification prioritization.
We currently collaborate with
Last edited 2012-01-10
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