PhD Research

Thesis Title:

Q-Star: Data Quality Engineering Framework

Abstract:

Data quality is one of the most important issues in data management. Recently, many approaches have been presented to enhance data quality. One of the major tasks in data quality solutions is record linkage. Most of the conventional approaches use pure algorithmic methods, which can only handle structured datasets with limited diversity of dirty data problems. We introduce a crowdsourcing approach to record linkage in structured, semi-structured and unstructured large datasets. We also introduce some effective algorithms, measures and indicators to enhance the quality of aggregated answers and detect malicious crowd workers.

Thesis Title:

Handling Uncertainty in requirements in Self Adaptive Software Systems Using Model-oriented Self-management

Abstract:

Requirements and environmental conditions have the potential to be misunderstood, mistaken, changeable and generally uncertain intrinsically. Therefore, an exact perception about all aspects of a goal model is hardly ever possible. While missing the real value of some significant requirements can interrupt the system services. What is needed in such cases is an adaptable system which is preferred to be deigned, decide and apply adaptation strategies as automatically as possible (SAS).The main focus in our study is handling uncertainty by measurement which helps to decide about design decisions quantitatively.

 

Thesis Title:

Semantic Traceability of Quality Attributes based on Architectural Tactics

Abstract:

Tracing quality attributes is the most important control approach that allows monitoring these features at all phases of the software development life cycle. But, establishing traceability links for quality attributes is a challenging issue, because they have a wide impact on the system and are realized by different architectural views at different levels of abstraction. Architectural patterns and tactics are commonly used to realize the quality attributes. In this research, we intend to introduce a new traceability solution by introducing the “Microtactic” concept and creating a semantic model of the project source code, enabling automatic traceability and monitoring of quality attributes.

Research Topic:

Internet of Things (IOT)

Abstract:

Internet of Things (IoT) is defined as a paradigm in which objects equipped with sensors, actuators, and processors could communicate each other through a software application to provide a meaningful purpose. Recently, it has seen a huge growth in the number of smart devices, wireless technologies, and sensors. In addition, many organization and industrial companies have expected that billions of devices will be connected to the Internet. Thus, to satisfy such a large number of things, we need architectures that support particular quality such as scalability, flexibility, interoperability, energy-efficiency, and security. For this context, it is necessary to have an engineering solution to satisfy the various requirements of particular application which it help to design a qualify architectures that could be suitable for IoT systems.