I am presently working on automated fault localization techniques. Fault localization techniques hastens program debugging by automatically identifying program statements that are likely to contain the fault. A class of fault localization techniques, referred to as the spectrum-based fault localization techniques, collect information about program behavior in failing and passing runs and analyze them to identify potential faulty statements. Below are the list of projects I am presently working on.

Evaluation of Spectrum Based Fault Localization Techniques for Different fault Classes:

Unlike testing approaches, spectrum-based fault localization approaches have not been evaluated for their effectiveness in localizing different classes of faults. In this project we will fill the gap by empirically evaluating the effectiveness of localizing different fault classes. We will use the results of the empirical evaluation to determine properties of faults that affect its rank calculated by spectrum based fault localization. Initially we started with the traditional fault classes such as different operator faults, variable definition fault, variable reference fault, and constant reference fault. But we quickly realized that the traditional classification does not explain the variation of effectivess. Therefore, we are investigating the effect of other properties such as how hard it is to execute a fault, and how the fault affects the rest of the program under test.

Earlier, I had worked on constraint-solving based test input generation and random test input generation for object oriented programs.

Publications:

  1. Mitigating the Effect of Coincidental Correctness in Spectrum Based Fault Localizationn, A. Bandyopadhyay accepted to the doctoral symposium track of the 5th IEEE Interational Conference on Software Testing, Verification, and Validation, Montreal , Canada, April 17--21, 2012.


  2. Tester Feedback Driven Fault Localization, A. Bandyopadhyay and S. Ghosh, accepted to the 5th IEEE Interational Conference on Software Testing, Verification, and Validation, Montreal, Canada, April 17--21, 2012.


  3. On the Effectiveness of the Tarantula Fault Localization Technique for Different Fault Classes, A. Bandyopadhyay and S. Ghosh, accepted to the 13th International High Assurance Systems Engineering Symposium, Boca Raton, FL, USA, November 10--12, 2011.


  4. Proximity Based Weighting of Test Cases to Improve Spectrum Based Fault Localization, A. Bandyopadhyay and S. Ghosh, accepted to the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE), Oread, Lawrence, KS, USA, November 6--10, 2011.


  5. Improving Spectrum-Based Fault Localization using Proximity-Based Weighting of Test Cases, A. Bandyopadhyay, accepted to the doctoral symposium track of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE), Oread, Lawrence, KS, USA, November 6--10, 2011.


  6. Improving Spectrum Based Fault Localization by Utilizing the Relative Importance of Test Cases, A. Bandyopadhyay, accepted to the doctoral symposium track of the 27th IEEE International Conference on Software Maintenance (ICSM), Williamsburg, VA, USA, September 25--30, 2011. PDF


  7. "Test Input Generation using UML Sequence and State Machines Models", A. Bandyopadhyay and S. Ghosh, accepted to the 2nd International Conference on Software Testing, Verification, and Validation (ICST), Denver, CO, April 1-4, 2009[PDF].


  8. "STUDENT PAPER: Using UML Sequence Diagrams and State Machines for Test Input Generation," A. Bandyopadhyay and S. Ghosh, Proceedings of the 19th International Symposium on Software Reliability Engineering (ISSRE), pp. 309-310, Seattle, Washington, November 11-14, 2008[PDF].


  9. "Developing Model Transformation Tools Using the UML Metamodel: Challenges and Solutions", A. Bandyopadhyay and S. Ghosh, Proceedings of Software Engineering and Applications, pp. 545-550, Cambridge, MA, November 19-21, 2007[PDF].