Failure detection and fault correction are vital to ensure high quality software. During the development and deployment phases detected failures are commonly classified by severity and tracked to meet quality and reliability requirements. Besides tracking failures, this data can be analyzed and used to qualify the software and to control the development and maintenance process. Our work is focused on failure data collected during the development phase and explores what we can learn by analyzing this data. Change management systems log the failures detected and the code fixes to correct the underlying software defects. By applying software reliability models and statistical techniques to this defect data, we can answer questions such as the following:
- Is the maintenance process increasing the software reliability?
- Is the maintenance process under control?
- How many failures are expected to occur in the field?
- What is the expected time remaining to meet the reliability requirement?
This presentation addresses these questions by using a methodology based on trend analysis, control charts and software reliability growth models. The methodology is applied to a large software system during various stages of testing including customer acceptance testing. What is new about this methodology is the combined use of control charts, trend analysis and software reliability models.
Veena Mendiratta leads the Next-Generation Solutions, Services and Systems Reliability work in the Bell Labs Network Performance and Reliability department at Bell Labs, Alcatel-Lucent.
She began her career at AT&T Bell Labs in 1984 and her work is focused on the reliability and performance analysis for telecommunications systems products, networks and services to guide system architecture solutions. Her technical interests include architecture, system and network dependability analysis, software reliability engineering and data analytics. Current work is focused on LTE (Long Term Evolution, 4G wireless technology) solution reliability engineering, service reliability modeling for the transportation sector, and predictive analytics for the telecommunications domain.
Professional activities include: Program Committee member for IEEE DSN and ISSRE conferences; serving on the MCM Advisory Board as well as an MCM and HiMCM judge for the COMAP sponsored math modeling competitions; member of INFORMS and Senior Member of IEEE; past co-chair of the INFORMS Chicago Chapter; and a member of the Alcatel-Lucent Technical Academy.
She has a B.Tech in Engineering from the Indian Institute of Technology, New Delhi, India and a Ph.D. in Operations Research from Northwestern University, Evanston, Illinois, USA.