Files: Basics and Handling

Related lectures (39)

Explores external libraries integration, advanced CMake features, and Fourier series representation of signals.

Covers in-place tokenization in C, focusing on modifying strings directly to extract tokens.

Provides an overview of standard input and output management in C programming, covering printf, scanf, and file handling techniques.

Covers the course objectives, administration, C language, program structure, variables, operators, and expressions.

Explores dynamic memory allocation in C, covering malloc, calloc, and realloc functions, emphasizing proper memory management and dynamic arrays.

Explains implementing an OCR program in C for sudoku number recognition.

Covers the basics of C programming, including syntax, structure, and compilation processes.

Introduces control structures in C programming, covering branches, loops, and best practices for writing clear code.

Covers instruction set extensions and high-level synthesis techniques for optimizing embedded processors.

Explores precompilation directives in C language, handling main() arguments, and passing arguments to a program.

Explores quantum chemistry, covering the Heisenberg Uncertainty Principle and mathematical aspects of quantum mechanics.

Explores parallel and distributed databases, covering architectures, query optimization, data storage, and distributed transactions.

Covers the architecture of parallel databases, benefits of parallelism, distributed databases, and replication methods.

Explores indexing in database systems, covering storage, files, and efficient data retrieval techniques using various types of indexes.

Covers phase change materials, integrated photonics, memories, computing, optoelectronics, in-memory computing, and quantum computing advancements.

Covers pointers in C++, memory addresses, dynamic allocation, arrays, and memory management techniques.

Covers the design of a heat exchanger using exhaust gas to generate steam.

Explores Poincaré sections, chaos, and strange attractors in nonlinear physics.

Covers derivation, integration, and simulation in Matlab, along with the representation of numbers and potential errors.

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