Algorithmic Problem Solving

Aim

• Analyze the efficiency of different approaches to solving a problem to determine which approaches will be reasonably efficient in a given situation.
• Compare different problems in terms of their difficulty.
• Use algorithm design techniques such as greedy algorithms, dynamic programming, divide and conquer, and combinatorial search to construct algorithms to solve given problems.
• Strategies for testing and debugging algorithms and data structures.
• Quickly and correctly implement a given specification of an algorithm or data structure.
• Communicate and cooperate with other students during problem solving in groups.

Content

Successful problem solving in computer science requires a solid theoretical foundation as well as ability to apply the theory to practical problem solving. The aim of this course is to develop your ability to solve complex algorithmic problems by applying knowledge of algorithms, data structures, and complexity theory. As a professional software developer it is essential to be able to analyze a problem, chose or design an algorithm, judge the efficiency of proposed algorithms, and to implement and test them quickly and correctly. In this course you will practice this by solving a large number of homework assignments and working under time constraints during problem solving sessions. The course will also contain a competitive element where individuals and teams should solve algorithmic problems with time and resource constraints.

The purpose is that the students should be able to use programming and algorithms as an effective tool for problem solving, and should get opportunity to apply theoretical knowledge from other courses to solve practical problems.