Abstract Syntax Tree
/ˌeɪˌɛsˈtiː/
noun … “Structural map of code for analysis and execution.”
Concurrency
/kənˈkʌrənsi/
noun … “Multiple computations overlapping in time.”
Profiling
/ˈproʊfaɪlɪŋ/
noun … “Measuring code to find performance bottlenecks.”
Profiling is the process of analyzing a program’s execution to collect data about its runtime behavior, resource usage, and performance characteristics. It is used to identify bottlenecks, inefficient algorithms, memory leaks, or excessive I/O operations. Profiling can be applied to CPU-bound, memory-bound, or I/O-bound code and is essential for optimization in software development.
Hypervisor
/ˈhaɪpərˌvaɪzər/
noun … “Manages virtual machines on a physical host.”
Multiprocessing
/ˌmʌltiˈprəʊsɛsɪŋ/
noun … “Multiple processes running in parallel.”
Threading
/ˈθrɛdɪŋ/
noun … “Parallel paths of execution within a program.”
Optimization
/ˌɒptɪmaɪˈzeɪʃən/
noun … “Making code run faster, smaller, or more efficient.”
Optimization in computing is the process of modifying software or systems to improve performance, resource utilization, or responsiveness while maintaining correctness. It applies to multiple layers of computation, including algorithms, source code, memory management, compilation, and execution. The goal of Optimization is to reduce time complexity, space usage, or energy consumption while preserving the intended behavior of the program.
Virtual Machine
/ˈvɜːrtʃuəl məˈʃiːn/
noun … “An emulated computer inside a host system.”
Read-Eval-Print Loop
/ˌriːˈpl/
noun … “Interactive coding, one line at a time.”
REPL, short for Read-Eval-Print Loop, is an interactive programming environment that reads user input as source code, evaluates it, prints the result, and loops back to accept more input. It provides immediate feedback, allowing developers to experiment with language features, test functions, and inspect data structures dynamically. REPLs are common in interpreted languages such as Python, Ruby, JavaScript, and Lisp.
Global Interpreter Lock
/ˈɡloʊbəl ɪnˈtɜːrprɪtər lɒk/
noun … “A single-thread lock for memory safety in Python.”
Global Interpreter Lock, commonly abbreviated as GIL, is a mutex used in the CPython implementation of Python to ensure that only one thread executes Python bytecode at a time within a single process. The primary purpose of the GIL is to protect access to Python objects, preventing data corruption caused by concurrent modifications and simplifying memory management, especially in reference counting-based garbage collection.