$.$ Initialization and Data Input

Prompting for Data File

User Interaction: Start the application by asking the user to input the name of an initial data file. This could be done via command line input or a simple graphical user interface $($GUI$)$ prompt.

Reading Data

File Reading: Use file I$/$O operations to open and read the specified file. This involves parsing each line or data record, typically formatted in a specific way $($e$.$g$.,$ CSV$,$ JSON$).$

Sorting Data: As data is read, insert it into an ordered linked list that maintains records sorted by RecordID. This ensures that all operations that require data traversal are optimized for speed.

Error Handling

File Accessibility: Check if the file exists and can be read. If not, prompt the user again or terminate the process with a clear message.

Data Validity: Validate the format and integrity of the data. If data is corrupt or improperly formatted, handle this gracefully by notifying the user and potentially skipping the malformed records.

Data Structure Initialization

Ordered Linked List: Implement this data structure to keep records in ascending order based on RecordID. This is crucial for efficient searching and sorting operations.

Hash Table Sizing: Based on the volume of data read, calculate an initial size for a hash table that will store elements for quick access. This size might be adjusted as more data is merged into the system.

$2.$ User Option Loop

This is the main loop where the user interacts with the system, choosing from various operations such as viewing records, merging new data, purging records, or exiting the program.

Implementing Choices

Command Handling: Each user input corresponds to a specific function or method in the code. This modular approach keeps the system organized and simplifies maintenance.

$3.$ Merge Operation

Merging involves integrating new data from another file into the existing dataset while ensuring no duplicates and maintaining order.

Merging Details

Non$-$Duplicate Assurance: Check each new record against existing records to ensure no duplicates are added.

Data Integration: Efficiently add new valid records to both the ordered linked list and the hash table to keep all data structures synchronized.

$4.$ Purge Operation

Purging means removing records from the system based on identifiers found in another specified file.

Purging Process

Record Identification: Each record ID from the purge file is used to locate and remove corresponding records from both the linked list and the hash table.

Structure Updates: After removal, ensure that data structures reflect the current state of the dataset without the purged records.

$5.$ Output Records

Outputting records can be to a file or to the standard console, depending on the user's preference.

Output Implementation

File Output: If a file name is provided, write the records to this file.

Console Output: If no file is specified, print the records directly to the console.

$6.$ Hash Table Display

This involves showing the internal state of the hash table, useful for debugging or understanding the distribution of data.

Display Functionality

Hash Table Traverse: Go through each bucket of the hash table, listing contents along with any overflow due to collisions.

Load Factor and Capacity: Display metrics such as load factor $($a measure of how full the hash table is$)$ and its capacity, which can indicate when resizing might be necessary.

System Design Considerations

Object$-$Oriented Design: Using classes to encapsulate data and methods, inheritance for creating a hierarchical structure of classes when appropriate, and other principles like polymorphism through method overloading and overriding.

Efficiency and Memory Management: Focus on writing efficient code, especially for operations that modify the dataset. Check memory usage to avoid leaks.

Testing and Documentation

JUnit Testing: Systematically test all functionalities using JUnit to ensure reliability and correctness. can you make this code in java