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Question		Answer
Ledger start learning		A structured record of all transactions.
Immutable start learning		Data that, once written to the blockchain, cannot be modified or erased, ensuring long-term integrity.
Consensus start learning		The process through which all nodes agree on the state of the blockchain, ensuring everyone shares the same valid history.
Scalability start learning		A network’s ability to handle increasing transaction volume without slowing down or becoming unstable.
Stake start learning		The amount of cryptocurrency locked by a validator to participate in Proof-of-Stake systems, used as both security and voting power.
Interoperability start learning		The ability of multiple blockchains or systems to communicate and exchange information or assets seamlessly.
Slashing start learning		A penalty in Proof-of-Stake networks where part of a validator’s staked funds is taken for dishonest or incorrect behavior.
Mining start learning		Wydobycie: The process of validating transactions and adding blocks to the chain in Proof-of-Work systems, rewarded with newly created coins.
Tamper-Resistant start learning		Designed so that any attempt to alter stored data becomes immediately detectable.
Cryptography start learning		Advanced mathematical techniques that secure blockchain operations.
Offside start learning		(In particular sports, especially football and ice hockey) in a position that is not allowed by the rules of the game, often in front of the ball.
Infringement start learning		An action that breaks a rule, law, etc.
Goalpost start learning		One of the two vertical posts that are connected with a crossbar to form a goal.
Foul start learning		An unfair or illegal action committed by a player against an opponent or the opposing team during a match.
Expected goals (xG) start learning		A metric used to determine how likely a player is to score a chance and to calculate how many goals a team is expected to score in a match.
Heat map start learning		A visual representation of player or team movement on the pitch — using colour intensity to show activity.
Penalty area start learning		In football, the area surrounded by white lines in front of the goal.
Judge System start learning		An automated software application or server that evaluates a participant's submitted code against predefined test cases to determine its correctness and efficiency.
Algorithm start learning		A precise, step-by-step set of instructions or rules designed to solve a specific problem or perform a computation.
Submission start learning		The act of sending a completed code solution to the judge system for evaluation, or the actual piece of code itself that has been handed in.
Time limit start learning		The strict maximum amount of time allowed by the system for a program to run and produce the correct answer before it is stopped and marked as too slow.
Input/Output Data start learning		The information provided to a program for it to process (input), and the resulting information the program produces and displays after execution (output).
Runtime error start learning		A type of software failure that occurs while a program is actively executing, often caused by illegal operations like dividing by zero or accessing restricted memory.
Test cases start learning		A specific set of input data alongside its expected correct output, used by the evaluating system to verify if a program functions correctly under various conditions.
Verdict start learning		The final decision or result given by the automated system after evaluating a submission, such as "Accepted," "Wrong Answer," or "Time Limit Exceeded."
Hacks start learning		In competitive programming, a deliberate attempt by one participant to provide a tricky, unexpected test case designed to make another participant's code fail.
Rating start learning		A numerical score assigned to a participant that reflects their overall skill level, which increases or decreases based on their performance in competitions.
ECU (Electronic Control Unit) start learning		a small computer in a car that controls things like the engine, brakes, or airbags.
Image Stitching start learning		combining many pictures into one bigger image (for example, to create a 360° view).
ADAS (Advanced Driver Assistance Systems) start learning		systems that help the driver, like lane assist, automatic braking, or parking help.
CAN Bus start learning		a communication system that lets all parts of the car (ECU, sensors, etc.) talk to each other.
Sensor Fusion start learning		combining data from different sensors (camera, radar, LiDAR) to understand the environment better.
Algorithm start learning		a set of steps or rules a computer follows to solve a problem.
LiDAR start learning		a sensor that uses laser light to measure distance and create a 3D map of surroundings.
Powertrain start learning		all parts that make the car move (engine, transmission, etc.).
Latency start learning		delay between sending and receiving information (how fast the system reacts).
Internal Combustion Engine (ICE) start learning		a traditional engine that burns fuel (like petrol or diesel) to create power.

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