Abstract
Abstract—According to our informal survey, Branch & Bound strategy is considerably difficult to learn compared to other strategies. This strategy consists of several complex algorithmic steps such as Reduced Cost Matrix (RCM) calculation and Breadth First Search. Thus, to help students understanding this strategy, AP-BB, an educational tool for learning Branch & Bound is developed. This tool includes four modules which are Brute Force solving visualization, Branch & Bound solving visualization, RCM calculator, and case-based performance comparison. These modules are expected to enhance student’s understanding about Branch & Bound strategy and its characteristics. Furthermore, our work incorporates TSP as its case study and Brute Force strategy as a baseline to provide a concrete impact of Branch & Bound strategy. According to our qualitative evaluation, AP-BB and all of its features fulfil student necessities for learning Branch & Bound strategy. Keywords— Educational Tool; Branch & Bound; Algorithm Strategy; Algorithm Visualization
Highlights
Despite the fact that Algorithm is the core topic of Computer Science (CS), not all undergraduate CS students can understand it properly by only relying on in-class session
AP-BB consists of four modules which are Brute Force solving visualization, Branch & Bound solving visualization, Reduced Cost Matrix (RCM) calculator, and case-based performance comparison
We have proposed AP-BB, an educational tool for learning Branch &Bound strategy and its characteristics
Summary
Despite the fact that Algorithm is the core topic of Computer Science (CS), not all undergraduate CS students can understand it properly by only relying on in-class session. GreedEx (Velázquez-Iturbide & Pérez-Carrasco, 2009), GreedExCol(Debdi, Paredes-Velasco, & Velázquez-Iturbide, 2015), AP-SA (Jonathan, Karnalim, & Ayub, 2016), and Complexitor (Elvina & Karnalim, in press) are several tools which fall into this category Using these tools, students are encouraged to observe and differentiate various algorithms through their respective characteristics. Some of them lack of visual imagination which makes them harder to visualize Branch & Bound logical tree for solving a problem To overcome this issue, this paper proposes AP-BB, a CS educational tool for learning Branch & Bound with TSP as its case study. Brute Force is incorporated in our AP-BB module as a baseline for exploiting Branch & Bound strategy Both strategies are compared based on their respective characteristics on case-based performance comparison module
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