Jeff Tian's Research in Software Reliability Engineering

My research in this area concentrates on effective models and techniques that not only help us evaluate product reliability but also improve reliability and testing process for large software systems. Software reliability engineering assumes usage-based statistical testing under the guidance of operational profiles (OPs) that characterize usage patterns and frequencies of target customers. My research in software reliability covers the following topics:

TBRMs for Reliability Improvement

In collaboration with industrial partners, I have developed an integrated approach for reliability measurement and improvement using tree-based reliability models or TBRMs. This integrated approach focuses on reliability improvement by identifying problematic areas for focused remedial actions. This research is summarized in the following papers (see also abstracts for some of these and other recent papers):

J. Tian and J. Palma. "Analyzing and Improving Reliability: A Tree-Based Approach", IEEE Software, Vol. 15, No.2, pp.97-104, March/April,, 1998.
J. Tian, "Reliability Measurement, Analysis, and Improvement for Large Software Systems", Advances in Computers, Vol.46, pp.159-235, Academic Press, 1998.
J. Tian. "Integrating Time Domain and Input Domain Analyses of Reliability Using Tree-Based Models". IEEE Trans. on Software Engineering. Vol.21, No.12, pp.945-958, Dec., 1995.

Workload Measurement and Reliability Modeling

My work for various large commercial software products from IBM revealed that properly captured test activities, workload, execution and defect data can be used for reliability assessment and prediction. This research is summarized in the following papers:

J. Tian and J. Palma. "Test Workload Measurement and Reliability Analysis for Large Commercial Software Systems", Annals of Software Engineering, Vol.4, Aug. 1997.
J. Tian, P. Lu and J. Palma. "Test Execution Based Reliability Measurement and Modeling for Large Commercial Software". IEEE Trans. on Software Engineering. Vol.21, No.5, pp.405-414, May, 1995

Recently, I have been concentrating on reliability analysis for web applications and OO and embedded software systems. Much of these are done in connection with testing of such systems.

New Models Based on Data Clusters

Data clustering can improve reliability modeling results, in terms of stability, accuracy in assessment and prediction, etc. This research is summarized in the following paper (see also online abstract for this paper):

J. Tian, "Better Reliability Assessment and Prediction through Data Clustering", IEEE Trans. on Software Engineering, Vol.28, No.10, pp.997-1007, Oct., 2002.

Tool Support

Tool support for data collection, analysis, and presentation is discussed in connection to tool support for general software measurement and analysis.

Prepared by Jeff Tian (tian@engr.smu.edu).
Last update: May 2, 2003.