Senior teaching assistant, University of Sarajevo
Polje Istraživanja: Computer science Software engineering
Ehlimana Krupalija (Graduate Student Member, IEEE) received the B.Sc. and M.Sc. degrees from the Department of Computer Science and Informatics, Faculty of Electrical Engineering, University of Sarajevo, Bosnia and Herzegovina, in 2018 and 2020, respectively, where she is currently pursuing the Ph.D. degree. She is currently a Teaching Assistant at the Department of Computer Science and Informatics, Faculty of Electrical Engineering, University of Sarajevo. Her research interests include software quality, real-time systems, parallelization, and optimization techniques.
The visual layout has an enormous influence on human perception and is a subject of many studies, including research on web page similarity comparison. Structure-based approaches use the possibility of direct access to HTML content, whereas visual methods have widespread usage due to the ability to analyze image screenshots of entire web pages. A solution described within this paper will focus on extracting web page layout in forms needed by both above-mentioned approaches.
— Cause-effect graphing is a commonly used black-box technique with many applications in practice. It is important to be able to create accurate cause-effect graph specifications from system requirements before converting them to test case tables used for black-box testing. In this paper, a new graphical software tool for creating cause-effect graph specifications is presented. The tool uses standardized graphical notation for describing different types of nodes, logical relations and constraints, resulting in a visual representation of the desired cause-effect graph which can be exported for later usage and imported in the tool. The purpose of this work is to make the cause-effect graph specification process easier for users in order to solve some of the problems which arise due to the insufficient amount of understanding of cause-effect graph elements. The proposed tool was successfully used for creating cause-effect graph specifications for small, medium and large graphs. It was also successfully used for performing different types of tasks by users without any prior knowledge of the functionalities of the tool, indicating that the tool is easy to use, helpful and intuitive. The results indicate that the usage of standardized notation is easier to understand than non-standardized approaches from other tools.
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