Algorithms and Data Structures

This is a collection of implementations of standard algorithms and data structures taught at introductory CS courses.

The following principles guided our implementation:

• Maximize comprehensibility.
• Name as many concepts explicitly as possible.
• Do not abbreviate variable or method names.
• Do not use comments to explain what the code does or how. This is better done in source code by choosing intent-revealing names and appropriate structures. Use comments to explain why a specific implementation was used.
• Provide an extensive set of regression tests, preferably by employing Test-Driven Development.
• Favor objects over primitive data types, e.g. use Integer instead of int and use List instead of bare arrays.
• Minimize duplication.
• Program defensively; the environment may try to corrupt our code. Prevent problems by checking parameters and giving meaningful exception descriptions.
• We try to provide a self-contained code base. Because this is intended for programming novices, we strive for minimizing dependencies to any libraries, be it the language SDK or especially third-party libraries.
• Maximizing comprehensibility requires trading performance and/or memory requirements sometimes.

Resources

• Robert Sedgewick, Kevin Wayne: Algorithms, 4th Edition