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Training and Preparation


This page features preparation tips and training materials for the International Computer Science Competition (ICSC). To be well-prepared for the competition and gain the most from the experience across the three rounds, we encourage you to:

  1. Understand the Competition Format
    Review the structure of each round, from broad concept tests to detailed algorithmic challenges.
  2. Master the Core Topics
    Focus on fundamental computer science concepts such as: algorithms and datastructures, optimization theory, information theory, machine learning, numerical analysis, cryptography, and computer architecture.
  3. Practice Problem-Solving
    Solve a wide range of theoretical and algorithmic problems on paper and programmatically to build flexibility and confidence.
  4. Learn from Mistakes
    Analyze incorrect answers carefully to close knowledge gaps.
  5. Use All Resources
    Leverage textbooks, papers from other competitions, and online coding platforms.
  6. Prepare for Technical Reading
    Build the ability to comprehend complex problem descriptions and academic papers.
  7. Simulate Timed Rounds
    Practice solving problems within strict time limits to enhance speed and accuracy.
  8. Study with Others
    Collaborate with peers, mentors, or join study groups for motivation and perspective.
  9. Enjoy the Challenge
    Approach ICSC as a fun and enriching journey into the depth of computer science!

Quick Links

CS Concepts


The International Computer Science Competition places a strong emphasis on understanding core computer science concepts - it is not just another coding competition. Success in ICSC relies on the ability to reason through problems, discuss algorithms, and grasp foundations across various topics. While coding is a valuable tool for expressing solutions, true achievement comes from strong conceptual understanding and critical thinking.

Participants will engage with problems spanning a wide range of areas, including algorithms and data structures, optimization theory, information theory, machine learning, numerical analysis, cryptography, and computer architecture. This is a broad spectrum, and we do not expect participants to be familiar across areas. Problems will include supporting information when needed. However, developing familiarity with foundational ideas across these domains can be beneficial.

Recommended Books

  • Thomas H. Cormen et al. (2009). Introduction to Algorithms. MIT Press. View
  • Michael Sipser (2012). Introduction to the Theory of Computation. Cengage Learning. View
  • David C. Lay (2011). Linear Algebra and Its Applications. Pearson. View
  • Stuart Russell and Peter Norvig (2020). Artificial Intelligence: A Modern Approach. Pearson. View
  • Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016). Deep Learning. MIT Press. View
  • Daniel Jurafsky and James H. Martin (2023). Speech and Language Processing. Pearson. View
  • Simon Singh (1999). The Code Book: The Science of Secrecy from Ancient Egypt to Quantum Cryptography. Anchor. View
  • Charles Petzold (2000). Code: The Hidden Language of Computer Hardware and Software. Microsoft Press. View
DTM reverse input

Example: A Deterministic Turing Machine that reverses an input sequence.

Programming


While a strong theoretical foundation is essential, practical programming skills are also important for success in the ICSC. Participants must be able to implement algorithms accurately and efficiently.

Clean code structure, debugging proficiency, the ability to read and implement pseudo code, and effective optimization techniques can significantly impact performance.

Software

A variety of tools are available to support programming, commonly known as Integrated Development Environments (IDEs). You can find suggested IDEs and information on how to start coding on our resources page:

   Resources


Recommended Books

Introductory books in Python, Java, and C++ that help students build foundational programming skills and develop good problem-solving habits:

  • Luciano Ramalho (2015). Fluent Python: Clear, Concise, and Effective Programming (Python). O’Reilly Media. View
  • Cay S. Horstmann (2019). Big Java: Early Objects (Java). Wiley. View
  • Allen B. Downey (2012). Think Like a Programmer (C++). No Starch Press. View
  • Donald E. Knuth (1968–). The Art of Computer Programming (Agnostic). Addison-Wesley. View

Training Problems


Since ICSC is launching its first edition this year, we do not yet have past training problems. However, below you can download two example problems to get a sense of the format and level of challenge at ICSC. One is a conceptual problem, and the other is a programming task.

  Example Problems   Example Code Skeletons (ZIP)


To support you in writing your own solutions, we provide example answers to the problems so you can see what a clear and well-structured submission might look like.

  Example Solution   Code Files (ZIP)

Additionally, we have compiled a list of problem sites from other competitions and challenges that share similarities with ICSC problems. These resources can be a valuable part of your preparation:

  • Raspberry Pi Foundation UK Bebras. Pathfinders/Elite problems and higher. View
  • American Computer Science League ACSL . Junior and Senor Devision. View
  • Seminole State College IPC . View
  • Eric Wastl Advent of Code. View
  • Wolfram Research Wolfram Challenges . View