University of Minnesota
Software Engineering Center
/

You are here

Sanjai Rayadurgam

Photo of Sanjai Rayadurgam
Staff Member
Phone Number: 
612-625-0331
Office Location: 
6-202 Keller Hall
Biography: 

Sanjai Rayadurgam is a Research Project Specialist at the University of Minnesota Software Engineering Center. His research interests are in software testing, formal analysis and requirements modeling, with particular focus on safety-critical systems development, where he has significant industrial experience. He earned a B.Sc. in Mathematics from the University of Madras at Chennai, and in Computer Science & Engineering, an M.E. from the Indian Institute of Science at Bangalore and a Ph.D. from the University of Minnesota at Twin Cities. He is a member of IEEE and ACM.

Recent Publications

Toward Rigorous Object-Code Coverage Criteria

Object-branch coverage (OBC) is often used as a measure of the thoroughness of tests suites, augmenting or substituting source-code based structural criteria such as branch coverage and modified condition/decision coverage (MC/DC). In addition, with the increasing use of third-party components for which source-code access may be unavailable, robust object-code coverage criteria are essential to assess how well the components are exercised during testing.

Discovering Instructions for Robust Binary-level Coverage Criteria

Object-Branch Coverage (OBC) is often used to measure e ective- ness of test suites, when source code is unavailable. The traditional OBC de nition can be made more resilient to variations in compil- ers and the structure of generated code by creating more robust de nitions. However nding which instructions should be included in each new de nition is laborious, error-prone, and architecture- dependent. We automate the discovery of instructions to be in- cluded for an improved OBC de nition on the X86 and ARM archi- tectures.

Domain Modeling for Development Process Simulation

Simulating agile processes prior to adoption can reduce the risk of enacting an ill-fitting process. Agent-based simulation is well-suited to capture the individual decision-making valued in agile. Yet, agile's lightweight nature creates simulation difficulties as agents must fill-in gaps within the specified process. Deliberative agents can do this given a suitable planning domain model. However, no such model, nor guidance for creating one, currently exists.

Pages