Ehsan Sharifi

Ehsan Sharifi

Ph.D. in Software Engineering

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Nationality: Iranian
Date of Birth: 1980-1-28
Marital Status: Married

Ph.D. in Software Engineering, (2015-2022)

  • Computer Engineering and Information Technology Faculty, Amirkabir University of Technology, Tehran, Iran

Ehsan Sharifi

Thesis Title:

Semantic Traceability of Quality Attributes based on Architectural Tactics

Abstract:

Traceability is a technique that allows all kinds of software artifacts to be monitored at all stages of the software life cycle. Tracing functional requirements is a relatively mature field of research. However, the traceability of quality attributes remains a challenge. Quality attributes have a wide range of effects on a system and are achieved from various architectural perspectives. Architectural patterns and tactics are commonly used to obtain quality attributes. The main goal of this thesis is to prevent architecture erosion by establishing trace links between quality attributes and source code, which is provided through the identification of architectural tactics in source code. The proposed approach in this thesis has been evaluated by conducting a case study.

This paper introduces a new quality attributes traceability approach based on Clone Microtactics. A Microtactic is a microstructure associated with an architectural tactic that is automatically identifiable in the conceptual representation of the source code. This approach identifies parts of source code with behavioral and contextual similarities with microtactics described in a reference model as Clone Microtactics. Identifying architectural tactics also enables quality attribute traceability in the source code. Identifying Microtactics in the source code as parts of an architectural tactic enables the traceability of quality attributes in the source code by an ontology-based semantic infrastructure. Our approach is evaluated by conducting a case study on a dataset related to the Apache Hadoop framework, which includes ten architectural tactics related to availability, performance, and security. Obtaining an average of 0.99 for recall shows that the proposed approach was able to identify almost all architectural tactics. Also, comparing the results with similar methods in this field indicates that in 80% of cases, the proposed approach has obtained better results.

  • Software Engineering (Requirements Traceability, Software Quality, Software Architecture)
  • Knowledge Engineering (Knowledge Representation, Ontology Engineering)
  • Web Intelligence (Semantic Web, Semantic Web Service, Web Mining)
  • Computer Network (Design, Security, Management)