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Mathematics Department, S-COAM to Sponsor SIAM Visiting Lecture Series

Veena Mendiratta of Alcatel-Lucent will give three lectures on September 30, 2013, as part of the SIAM Visiting Lecturer Program, sponsored by the Mathematics Department and the S-COAM program.

What Can We Learn from Software Failure Data

  • 1:25–2:15 p.m.
  • Room 101 Eberly

Abstract:

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. 

Career Talk for Undergraduates

  • 3:35–4:35 p.m.
  • Rooms 226/229 Stright

Using Social Influence to Predict Subscriber Churn

  • 5:20–6:20 p.m.
  • Rooms 226/229 Stright

Abstract:

The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this talk, a new churn prediction algorithm is described that incorporates the influence churners spread to their social peers. Using data from a major service provider, it is shown that social influence improves churn prediction and is among the most important factors.

Dr. Veena Mendiratta

Veena Mendiratta is a practice leader, Network Reliability and Analytics, in the Corporate CTO organization at Alcatel-Lucent in Naperville, Illinois, USA. Her work is focused on analytics for customer experience and network reliability, cloud network reliability, and service reliability modeling for mission critical networks. She has published over 40 papers in conferences and journals and has presented tutorials on reliability modeling and analysis at several conferences. Other professional activities include: Scientific Committee member for the NetMob Conference, Program Committee member for IEEE, DSN, and ISSRE conferences (past) and IEEE Cloud Engineering conference; Steering Committee member for the ISSRE conference; member of the SIAM Visiting Lecturer Program; invited judge for the annual COMAP-sponsored MCM and HiMCM math modeling competitions; and appointment as a Fulbright Specialist Scholar for a five-year period (2012–2017).  She holds a Ph.D. in Operations Research from Northwestern University and a B.Tech in Engineering from the Indian Institute of Technology, New Delhi, India. 

Department of Mathematics

S-COAM program

Posted on 9/10/2013 8:34:18 AM

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