Table-driven

Table-driven refers to a programming or system design approach where the control flow, logic, or output is determined by data stored in a table (or a similar data structure like an array, list, or dictionary). Instead of hardcoding decisions within the program's source code, the program consults the table to make choices, retrieve data, or perform actions. This method offers flexibility and maintainability, as changes can be made by modifying the table's contents without altering the program's core code. It's particularly valuable when handling complex or frequently changing rules, configurations, or relationships. The table serves as a lookup mechanism, allowing the program to efficiently access and utilize pre-defined information. The table can contain information about conditional statements, function calls, outputs, or data transformations.

Table-driven meaning with examples

• A video game AI might use a table-driven approach for enemy behavior. Instead of writing numerous 'if-then-else' statements, a table could define enemy actions based on factors like player distance, health, and weapon. The table would map specific conditions to actions (e.g., 'player close, health high' -> 'attack', 'player far, health low' -> 'retreat'). This makes it easier to tweak enemy behavior without recompiling the game.
• A configuration management system might use a table-driven architecture to handle different server settings. The table would contain entries for various server types, operating systems, and applications. Each entry would specify configuration parameters, such as memory limits, network settings, and file paths. This method simplifies managing multiple servers with diverse requirements and can be easily adapted to reflect changes in server specifications.
• A compiler uses a table-driven lexical analyzer (or scanner) to determine if an incoming sequence of characters (like source code) represents a valid token. The table contains rules or patterns for token recognition. When a new character stream is analyzed, the scanner uses the table to identify keywords, identifiers, and operators. The architecture makes token analysis quicker and less prone to human error, especially with language evolution.
• A financial model uses a table-driven method to estimate the effects of different economic scenarios. The table contains variables that map out the consequences of market changes on different departments within a company. Then, the table maps out the financial and economic impact of multiple actions. This design is more resilient to changes because the actual model does not change and instead just adjusts the numbers in the table.
• A rule engine leverages a table-driven format to determine which business rules to apply. Each rule is represented as an entry in a rule table that specifies conditions (e.g., customer age, purchase amount) and corresponding actions (e.g., applying a discount, sending a notification). The engine evaluates the conditions against the incoming data, retrieves the appropriate action from the table, and executes it.