In a standard array-based linear queue, the front pointer moves forward as elements are dequeued, but the underlying array does not shift its contents to reclaim that space. This is by design, to keep the operations efficient — shifting elements would require O(n) time, which defeats the purpose of a queue's expected constant-time operations. As a result, even though the front elements are no longer part of the logical queue, they still occupy physical space in the array. The queue appears full when the rear reaches the end of the array, even if there are empty slots at the beginning. This design simplifies the operations but leads to inefficient use of memory. While this issue is solved by circular queues, in a basic linear queue, reclaiming that space would require manually shifting every item one position to the left after each dequeue, which significantly increases processing time and complexity.

If you continually enqueue items without checking whether the queue is full in an array-based linear implementation, it leads to a condition called overflow. Overflow occurs when the rear index exceeds the maximum index of the array, meaning there is no more space to store new elements. Since arrays have fixed sizes, attempting to insert beyond their bounds typically causes a runtime error or unexpected behaviour, depending on the programming language used. In strongly typed languages like Java or C++, this might throw an out-of-bounds exception. In some environments, it might even corrupt memory. This is why checking the isFull condition before enqueueing is essential. The proper response to an overflow should be to alert the system or user and halt further insertions unless memory is expanded, or to implement a dynamic data structure like a linked list or circular queue that handles growth more effectively.

In both array-based and linked list implementations of a queue, the core operations — enqueue and dequeue — are designed to run in O(1) time, assuming no resizing or shifting is involved. However, the time complexity may vary in practice depending on implementation details. For array-based queues, if the array is full and dynamic resizing is implemented (as in some high-level languages), the resizing operation itself takes O(n) time because it involves copying elements to a new array. Also, if an inefficient approach is used where elements are shifted left after each dequeue, that operation would be O(n). In contrast, linked list implementations maintain O(1) complexity for both enqueue and dequeue because new nodes are simply added or removed via pointer manipulation without shifting any data. Therefore, while both structures offer similar theoretical performance, linked lists are more consistent in practice and better suited to scenarios with unpredictable queue sizes.

While it is technically possible to simulate queue behaviour using recursive functions, it is neither efficient nor practical. Recursion is based on function calls stacking on top of each other, which naturally follows a Last-In-First-Out (LIFO) order, making it more suited to stack behaviour. Implementing a queue — which follows a First-In-First-Out (FIFO) order — using recursion requires careful tracking of function calls and returns to simulate the correct removal and insertion behaviour, often involving complex and memory-heavy techniques such as tail recursion with accumulator parameters. Moreover, recursion introduces the risk of stack overflow if too many elements are enqueued without corresponding dequeues, especially in languages with limited call stack sizes. Therefore, queues are more naturally and efficiently implemented using iterative approaches and explicit data structures like arrays or linked lists, which provide direct control over memory and pointer manipulation without relying on the call stack.

While linear queues themselves are not inherently vulnerable, the way they are used and managed in software can lead to security concerns. One key issue is input validation. If enqueue operations are not properly checked for overflow, an attacker might exploit this by pushing more data than the queue can handle, leading to buffer overflows in low-level languages like C or C++. This can result in memory corruption, unexpected crashes, or even execution of malicious code. Similarly, failing to check for isEmpty before dequeuing can cause null reference errors or undefined behaviour, which could be exploited in rare cases. Another concern is resource exhaustion — attackers might flood a system with inputs to fill up the queue (known as a denial-of-service attack), causing it to block or crash if not designed to handle such loads. To mitigate these risks, queue operations must include strict bounds checking, error handling, and resource monitoring to ensure stability and security.