Algorithms and Data Structures

Algorithms and data structures are fundamental notions in computer science. Understanding how they can be exploited in combination for better programming implementations in terms of time and space complexity is vital for writing efficient code. This course equips students with the analytic and implementation skills needed to design, reason about, and deploy efficient solutions in Java.

The course opens with core data structures, beginning with fundamental containers such as arrays and linked lists and then progressing to ordered structures such as stacks, queues, priority queues, heaps, and maps. The students learn to devise and analyse both iterative and recursive operations, and quantify their time- and space-complexity. The syllabus proceeds to sorting, examining selection, insertion, heap, merge, quick, bucket, and radix sorts so that learners can implement, analyse, and judiciously select an algorithm tailored to different constraints on time and space complexities. Next comes searching: balanced search structures (generic search trees, AVL trees, and (2,4)-trees). The programme culminates in graphs and graph algorithms—covering directed and undirected representations, weighted variants, and adjacency schemas—followed by breadth- and depth-first traversals, connectivity and cycle tests, topological ordering, single-source shortest paths, and minimum-spanning trees, enabling participants to select suitable graph representations and implement state-of-the-art algorithms with proven performance guarantees.

The course comprises the following assessment moments:

Week 5: a formative analysis midterm exam (MA)

Week 5: a formative implementation midterm exam (MI)

Week 10: a summative analysis final exam (FA)

Week 10: a summative implementation final exam (FI)

The final course grade GF will be as follows:

If FA >= 5 and FI >= 5, then GF = (FA+FI)/2

Otherwise, GF = NV

For successful completion of the course:

- both grades FA and FI need to be at least 5 (before rounding),

- the final course grade GF needs to be at least 5.8.

The standard TU Delft rounding rules apply.

Note: the midterms do not contribute to the final course grade, their purpose is only to give the student an idea of the progress halfway through the course.

There are separate resits for the analysis (RA) and the implementation (RI) components.

The course grade GR after the resit will be determined as follows:

If MAX(FA,RA) >= 5 and MAX(FI,RI) >= 5, then GR = (MAX(FA,RA)+MAX(FI,RI))/2

Otherwise, GR = NV

For successful completion of the course after the resit:

- FA or RA needs to be at least 5 and also FI or RI needs to be at least 5 (all before rounding),

- the course grade after resit GR needs to be at least 5.8.

The standard TU Delft rounding rules apply.

Partial grades cannot be carried over to future editions of the course.

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 29, sub 4)