The research of the Algorithms, Logic, and Graphs section covers Algorithmics, Computational Logic, and Graph Theory and is the scientific foundation for constructing robust, efficient, and intelligent software applications based on mathematically sound solutions. Two crucial aspects when designing efficient software are large data sets and intrinsically hard problems. The naive algorithm or data structure usually only suffices for solving small scale problems. A simple search engine can easily index the contents of a drive on a personal computer, but indexing the web is much more difficult. 

Similarly, an autonomous robot can plan its actions optimally by an exhaustive state space search only if the number of possible actions and states is very limited. Thus more advanced algorithms/methods are needed to solve these problems. In software applications for complex problems, often some degree of intelligence is needed in addition to efficiency. Intelligence means that the software is able to collect and categorize knowledge, do logical reasoning, learn from experiences, and communicate and negotiate with other software applications. The scientific foundation for such applications includes computational logic and logic-based AI. 

Graph Theory plays a fundamental role in Computer Science, in particular in the design and analysis of algorithms. For example graphs are used for modeling networks, modeling the structure computer software, visualize the command flow within a program to name just a few. In addition, Graph Theory is an independent mathematical discipline with ties to other branches of mathematics (geometry, topology, probability, logic) and to engineering sciences (electrical networks and optimization).