Texas Tech University, Department of Computer Science
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AVESTA: Research


Research Projects

Several projects are active in the AVESTA group.

Cyber Security Modeling and Testing

Investigators: Dr. Namin, Dr. Hewett, and Dr. Zhang

The project aims at modeling security policies, attack detection, and security testing including secure programming, and modeling through software engineering practice.


Bayesian Techniques for Program Analysis

Investigators: Dr. Mohan Sridharan, Dr. Namin

This project is a joint work with Dr. Mohan Sridharan’s group. The main goal of this project is to develop and adapt Bayesian online learning techniques to several software testing problems. Several problems associated with program analysis have been discussed and planned. A Tutorial for introducing Bayesian data analysis was offered by Dr. Sridhana and myself.


The Role of Code Coverage on Defect Coverage

Investigators: Dr. Namin, Sahitya Kakarla

This project is addressing the fundamental question concerning whether coverage plays any role in predicting the effectiveness of test suites. The question is very challenging sue to misunderstanding of the effect of coverage on fault detection.


Testing Multi−Threaded and Multi−Core Applications

Investigators: Dr. Namin, Kunjal Rathod

The multicore software engineering is one of research interest of AVESTA group. We seek tools and techniques to model and test multithreaded applications. This includes producing a tool to generate interleavings for threads scheduling, auto−tuning, etc.


Mutation Analysis and Tools

Investigators: Dr. Namin, Prachi Devalapurkar, Pratyusha Madirajua, Cheranaya Chidambaram

The mutation testing research includes designing techniques to reduce the cost of mutation testing, to model the relationship between faults and mutants, and to develop new tools to the research community.


Adaptive Random Testing

Investigators: Dr. Namin, Selina Momotaz

Several researchers have been working on adaptive random testing. We mainly focus on application of probabilistic reasoning to build new tools.


Testing Probabilistic Systems

Investigators: Dr. Barbara Millet, Dr. Mohan Sridharan, Dr. Namin, Pulkit Tomar

Probabilistic systems are very interesting but difficult systems to test. The purpose of this project is to conduct empirical studies to investigate the possibility of developing new algorithms and techniques addressing non−deterministic nature of these systems. Probabilistic model checking is the major tool we use to test human-computer interaction and simulate the human factors.