lmms-lab/CSBench_Assertion · Datasets at Hugging Face

ID int64 383 2.08k	Split stringclasses 1 value	Domain stringclasses 4 values	SubDomain stringclasses 24 values	Format stringclasses 1 value	Tag stringclasses 2 values	Language stringclasses 1 value	Question stringlengths 28 336	Answer stringclasses 2 values	Explanation stringlengths 29 771 ⌀
383	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	In data structures, the logical structure can be divided into linear and non-linear structures.	True	null
384	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	In data structures, a data element refers to the basic unit of data, which can be composed of several data items.	True	null
385	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	Data types in computer science refer to the classification of data storage formats.	False	null
386	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	Data structures mainly consist of three aspects: logical structure, storage structure, and data operations.	True	null
387	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	Algorithms possess characteristics such as finiteness, determinacy, feasibility, input, and output.	True	null
388	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	Designing a good algorithm typically requires consideration of correctness, readability, robustness, efficiency, and low storage requirements.	True	null
389	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	The space complexity of an algorithm is defined by the amount of space occupied by the temporary data generated during the execution of the algorithm.	False	null
390	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	An abstract data type can be used to define a complete data structure.	True	null
391	Test	Data Structure and Algorithm	Overview	Assertion	Knowledge	English	A singly linked list belongs to the logical structure.	False	null
392	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In the ListInsert function of the sequential list, when inserting an element into the middle position of the list, it is necessary to move all elements after the insertion position.	True	null
393	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In the LocateElem function of the sequential list, the correct way to find the position of element e is to return i+1 after the element is found.	True	null
394	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In a singly linked list with a head node, when executing the ListDelete function to delete the ith element, the operation involves finding the (i-1)th node, then disconnecting the ith node and linking to the (i+1)th node.	True	null
395	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In a singly linked list, the GetElem function correctly finds and returns the value of the i-th element bitwise, and it returns a pointer to the i-th node.	True	null
396	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In the List_TailInsert function for creating a singly linked list using the tail insertion method, the new node is inserted at the tail in the list.	True	null
397	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In the initialization of a doubly linked list, the prior pointer of the head node points to NULL, and the next pointer also points to NULL.	True	null
398	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	A linear list is a finite sequence with n data items.	False	null
399	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	A sequential list is a storage method for a linear table, where the most common operations are accessing elements at any specified index and performing insertions or deletions at the end, which can save time.	True	null
400	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	When using a sequential storage structure for a non-empty linear list of length n, to insert a data element at the ith position in the list, the valid range for i should be 1≤i≤n.	False	null
401	Test	Data Structure and Algorithm	Linear List	Assertion	Knowledge	English	In a static linked list, the pointer represents the address of the element pointed to by the left link or right link.	False	null
402	Test	Data Structure and Algorithm	Linear List	Assertion	Reasoning	English	In the insertion algorithm for sequential lists, when n spaces are full, an additional m spaces can be requested. If the request fails, it indicates that the system does not have m contiguous spaces available for allocation.	False	Sequential storage requires continuous storage space. When applying, it is necessary to apply for n+m continuous storage spaces, and then copy the original n elements of the linear table to the first n units of the newly applied n+m continuous storage spaces.
403	Test	Data Structure and Algorithm	Linear List	Assertion	Reasoning	English	In a singly linked list, given that the node pointed to by q is the predecessor of the node pointed to by p, to insert node S between q and p, execute q->next=s; s->next=p;.	True	After the insertion of s, q becomes the predecessor of s, while p becomes the successor of s.
404	Test	Data Structure and Algorithm	Linear List	Assertion	Reasoning	English	In a singly linked list h with a head node and a length of n, where there is a tail pointer r, the operation to delete the last element of the linked list is related to the length of the list.	True	To delete the last node of a singly linked list, the pointer field of its predecessor node must be set to NULL. This requires traversing from the beginning to find the predecessor node, taking O(n) time, which is dependent on the length of the list. Other operations are independent of the list length, and readers can simulate them on their own.
405	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	The application of queues in page replacement algorithms is to manage memory pages.	True	null
406	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	Special matrices often use compressed storage to save space.	True	null
407	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	Compared to a sequential stack, a linked stack has a fairly obvious advantage, which is that it generally does not encounter the situation of an empty stack.	True	null
408	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	The circular queue is stored in the array A[0...n], and the operation for enqueuing is rear=(rear+1) mod (n+1).	True	null
409	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	The most suitable linked list for implementing a queue is a non-circular singly linked list with a front pointer and a rear pointer.	True	null
410	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Knowledge	English	When performing a deletion operation on a queue with linked storage, both the head and tail pointers need to be modified.	False	null
411	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Reasoning	English	After performing Push, Push, Pop, Push, Pop, Push, Pop, Push operations, the value of the stack pointer is 1005H.	False	Each element requires one storage unit, so each time an element is pushed onto the stack, top is incremented by 1, and each time an element is popped from the stack, top is decremented by 1. The value of the pointer top successively is 1001H, 1002H, 1001H, 1002H, 1001H, 1002H, 1001H, 1002H.
412	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Reasoning	English	To insert a node X into a linked stack with a top pointer named 'top' (without a head node), execute x->next=top->next; top->next=x.	False	When a linked stack is represented by a single linked list without a head node, the push operation inserts a node x at the beginning (i.e., x->next=top), and after insertion, top should point to the newly inserted node x. Please consider the situation when the linked stack has a head node.
413	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Reasoning	English	Use S to represent the push operation and X to represent the pop operation. If the push order of elements is 1234, then to achieve the pop order of 1342, the corresponding sequence of S and X operations is SXSSXXSX.	False	null
414	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Reasoning	English	The stack full condition for the sequential shared stack Share[0:n-1] is when top1 equals top2.	False	null
415	Test	Data Structure and Algorithm	Stack, Queue, and Array	Assertion	Reasoning	English	Assuming the length of the queue represented by a circular singly linked list is n, with the front fixed at the end of the list, if only a head pointer is set, then the time complexity of the enqueue operation is O(n).	True	According to the problem statement, the enqueue operation is performed at the end of the queue, which is the head of the linked list. It is clearly stated in the problem that the linked list only has a head pointer, meaning there is no head node or tail pointer. After enqueuing, the circular singly linked list must maintain its circular nature. The time complexity of finding the tail node in a circular singly linked list with only a head pointer is O(n), therefore the time complexity of the enqueue operation is O(n).
416	Test	Data Structure and Algorithm	String	Assertion	Knowledge	English	The position of a character in the main string refers to the frequency of the character in the string.	False	null
417	Test	Data Structure and Algorithm	String	Assertion	Knowledge	English	The function of the StrCopy operation is to assign one string to another string.	False	null
418	Test	Data Structure and Algorithm	String	Assertion	Knowledge	English	The StrEmpty operation is used to check if a string is empty.	True	null
419	Test	Data Structure and Algorithm	String	Assertion	Knowledge	English	The best-case time complexity of the naive pattern matching algorithm is O(m).	True	null
420	Test	Data Structure and Algorithm	String	Assertion	Knowledge	English	The worst-case time complexity of the KMP algorithm is O(mn).	False	null
421	Test	Data Structure and Algorithm	String	Assertion	Reasoning	English	The operation of concatenation refers to finding the first occurrence of string S_1 in string S_2.	False	Linking is the concatenation of two strings.
422	Test	Data Structure and Algorithm	String	Assertion	Reasoning	English	The characteristic of the KMP algorithm is that the pointer of the main string does not decrease during pattern matching.	True	In the comparison process of the KMP algorithm, the main string does not backtrack, so the pointer of the main string will not decrease.
423	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	The recursive characteristic of a tree is that a tree is composed of multiple branches.	False	null
424	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	The number of nodes in a tree is equal to the sum of the degrees of all nodes minus 1.	False	null
425	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	A full binary tree is a binary tree where every node has two children.	False	null
426	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	The time complexity and space complexity of binary tree traversal are O(n) and O(n)	True	null
427	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	A complete binary tree with 124 leaf nodes can have at most 250 nodes.	False	null
428	Test	Data Structure and Algorithm	Tree	Assertion	Knowledge	English	A threaded binary tree with n nodes contains n + 1 threads.	True	null
429	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	In a complete binary tree, if a node does not have a left child, then it must be a leaf node.	True	In a complete binary tree, if there is a node of degree 1, there can only be one, and the node has only the left child and no right child
430	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	Given a binary tree with 2n nodes, where m < n, it is impossible to have 2m nodes with degree 0.	False	Property 1 of binary trees indicates that n_0 = n_2 + 1. The total number of nodes = 2n = n_0 + n_1 + n_2 = n_1 + 2n_2 + 1, thus n_1 = 2(n - n_2) - 1. Therefore, n_1 is odd, which means that it is impossible for the binary tree to have 2m nodes with degree 1.
431	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	If a complete binary tree with a depth of 6 has 3 leaf nodes on the 6th level, then the binary tree has a total of 17 leaf nodes.	True	A complete binary tree with a depth of 6 has 2^4=16 nodes on the 5th level. The 6th level has 3 leaf nodes on the far left, whose parent nodes are the two leftmost nodes on the 5th level. Therefore, the remaining nodes on the 5th level are all leaf nodes, totaling 16-2=14. Adding the 3 leaf nodes from the 6th level, there are a total of 17 leaf nodes.
432	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	During an inorder traversal, the condition for n to come before m is that n is a descendant of m.	False	In-order traversal involves first visiting the left subtree, then visiting the root node, and finally visiting the right subtree.
433	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	The post-order traversal result of this binary tree is FEDCBA.	False	For this kind of traversal sequence oriented problem, the binary tree is obtained according to the traversal results, and the corresponding traversal sequence is found. For example, in this problem, knowing the results of the precedent and intermediate order traversal, we can know that the root node of the tree is A, the left subtree has C and B, and the rest is the right subtree, then in the posterior sequence overtime result, A must be last, and C and B must be in front, and because there is DEF in the precedent and EDF in the middle order, then D is the root of this subtree, so D is ranked after EF in the posterior order, so the answer is false
434	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	To determine if the node *P in a threaded binary tree has a right child, the condition is that P is not null.	False	In a threaded binary tree, ltag/rtag is used to identify whether the left/right pointer field of a node is a thread. When its value is 1, the corresponding pointer field is a thread; when its value is 0, the corresponding pointer field is the left/right child.
435	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	Traversal of a pre-order threaded tree still requires the support of a stack.	False	The traversal of a preorder threaded tree does not require stack support.
436	Test	Data Structure and Algorithm	Tree	Assertion	Reasoning	English	In the forest F, there are 3 trees, with the number of nodes in the first, second, and third trees being M_1, M_2, and M_3, respectively. The number of nodes on the right subtree of the root node of the binary tree corresponding to forest F is M_2 + M_3.	True	The conversion rule from a forest to a binary tree is also "left child, right sibling". However, unlike ordinary trees, each tree in a forest is independent, so we first need to treat the root nodes of each tree as sibling nodes. Therefore, in the given problem, after the conversion of the forest, Tree 2 becomes the right subtree of the root node of Tree 1, and Tree 3 becomes the right subtree of the root node of Tree 2. Thus, the number of nodes on the right subtree of the root node of the binary tree corresponding to forest F is M_2 + M_3.
437	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	The characteristic of a graph's vertex and edge sets is that they can both be empty.	False	null
438	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	A connected graph is characterized by the fact that any two vertices are connected, and an undirected graph has at least n-1 edges.	True	null
439	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	The weight of an edge refers to the number of vertices that the edge connects.	False	null
440	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	In a directed complete graph, the range of the number of edges is from 0 to n.	False	null
441	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	The characteristic of representing a graph with an adjacency list is that it can only represent undirected graphs.	False	null
442	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	The cross-linked list is a storage method with the highest space complexity.	False	null
443	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	The operation NextNeighbor(G, x, y) can be used to determine whether there is an edge from vertex x to vertex y in the graph.	False	null
444	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	To retrieve and set the weight of an edge in a graph, you can use Get_edge_value(G, x, y) to obtain the weight of the edge between node x and node y in graph G, or use Set_edge_value(G, x, y, v) to set the weight of the edge between node x and node y in graph G to v.	True	null
445	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	To find the first adjacent vertex and the next adjacent vertex in a graph, you can use FirstNeighbor(G, x) to find the first adjacent vertex of vertex x, and then use NextNeighbor(G, x, y) to find the next adjacent vertex of vertex x after the adjacent vertex y.	True	null
446	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	An undirected graph with n vertices and n edges must contain a cycle.	True	null
447	Test	Data Structure and Algorithm	Graph	Assertion	Knowledge	English	In a directed graph with n vertices, the degree of each vertex can reach up to 2n.	False	null
448	Test	Data Structure and Algorithm	Graph	Assertion	Reasoning	English	If a single depth-first search from any vertex of an undirected graph can visit all vertices, then the graph must be strongly connected.	False	A strongly connected graph is a directed graph, which contradicts the title; A depth-first search on the undirected connected graph can access all vertices of the connected graph. An undirected graph with a loop is not necessarily a connected graph, because the loop does not necessarily contain all the nodes of the graph; A connectivity graph may be a tree or it may have a ring.
449	Test	Data Structure and Algorithm	Graph	Assertion	Reasoning	English	The adjacency matrix representation of a graph is unique, while the adjacency list representation is not unique.	True	The adjacency matrix representation is unique because the information of the edges in the graph has a fixed position in the matrix, while the adjacency list is not unique because its construction depends on the order in which the edges are read and the insertion algorithm used in the edge list.
450	Test	Data Structure and Algorithm	Graph	Assertion	Reasoning	English	For a disconnected undirected graph G, when visiting all vertices using depth-first traversal, the number of times DFS is called within the DFSTraverse function is exactly equal to the number of connected components.	True	DFS (or BFS) can be used to calculate the number of connected components in a graph, as a single traversal will inevitably visit all vertices within a connected graph, and DFS will not be invoked again for vertices that have already been visited. Therefore, the number of connected components in a graph is exactly the number of times DFS is called within DFSTraverse().
451	Test	Data Structure and Algorithm	Graph	Assertion	Reasoning	English	In addition to using topological sorting, the Dijkstra algorithm for finding the shortest path can also be used to determine whether there are cycles in a directed graph.	False	Dijkstra's algorithm is not designed to detect cycles in directed graphs.
452	Test	Data Structure and Algorithm	Graph	Assertion	Reasoning	English	For a directed graph with n vertices and e edges stored using an adjacency list, the time complexity of performing a breadth-first traversal is O(e).	False	Breadth-first traversal requires the use of a queue for implementation. When using an adjacency list to perform breadth-first traversal on a graph, each vertex needs to be enqueued once (vertex list traversal), so the time complexity is O(n). In the process of searching for the adjacent vertices of all vertices, each edge is visited at least once (edge list traversal), thus the time complexity is O(e). Therefore, the overall time complexity of the algorithm is O(n+e).
453	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The process involves randomly accessing the data set.	False	null
454	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	A lookup table is an arbitrary collection of data.	False	null
455	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	Common operations on lookup tables include deleting data elements.	False	null
456	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The search length refers to the duration of the search process.	False	null
457	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The Average Search Length (ASL) is determined by calculating the average number of records accessed during all search processes.	False	null
458	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	Binary search is applicable to ordered sequential lists.	True	null
459	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The characteristic of block search is that both within and between blocks are ordered.	False	null
460	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The characteristic of the direct addressing hash function is its simplicity and the absence of collisions, but it may lead to a waste of storage space.	True	null
461	Test	Data Structure and Algorithm	Searching	Assertion	Knowledge	English	The mid-square method is suitable for situations where only a few digits of the key are significant.	False	null
462	Test	Data Structure and Algorithm	Searching	Assertion	Reasoning	English	For an ordered singly linked list of length n, if the probability of searching for each element is equal, the average search length for a successful search of any element in the list is (n + 1)/2.	True	Performing sequential search on an ordered singly linked list, the average search length for a successful search is the same as that for sequential search on an unordered or ordered sequential list, which is (n+1)/2.
463	Test	Data Structure and Algorithm	Searching	Assertion	Reasoning	English	Hash search is a lookup method that can only be performed on sequential storage structures.	False	binary search can only be performed on sequential storage and requires that the keys are ordered.
464	Test	Data Structure and Algorithm	Searching	Assertion	Reasoning	English	In open addressing, the "clustering" problem that occurs when hashing to the same address is caused by conflicts between synonyms or non-synonyms.	True	In open addressing, the "clustering" issue arises when synonyms and non-synonyms interleave their probing sequences due to hashing to the same address, causing keyword searches to require longer probing distances and reducing the efficiency of hashing. Therefore, it is important to choose a good collision resolution method to avoid "clustering."
465	Test	Data Structure and Algorithm	Searching	Assertion	Reasoning	English	When using chaining to handle collisions, if insertion is restricted to the head of the list, the time to insert any element is the same. However, using chaining to handle collisions can easily lead to clustering.	False	Synonym collision is not equivalent to clustering; when handling collisions with the chaining method, synonyms are placed in the same linked list, which does not cause clustering.
466	Test	Data Structure and Algorithm	Sorting	Assertion	Knowledge	English	Sorting is the process of arranging the elements in a list in a random order.	False	null
467	Test	Data Structure and Algorithm	Sorting	Assertion	Knowledge	English	In direct insertion sort with a sentinel, the role of the sentinel is to speed up the search process.	True	null
468	Test	Data Structure and Algorithm	Sorting	Assertion	Knowledge	English	The average time complexity of direct insertion sort is O(n^2).	True	null
469	Test	Data Structure and Algorithm	Sorting	Assertion	Knowledge	English	The best-case time complexity of quicksort is O(n^1.3).	False	null
470	Test	Data Structure and Algorithm	Sorting	Assertion	Knowledge	English	In a min-heap containing n keys, the record with the maximum key could possibly be stored at position n/2.	False	null
471	Test	Data Structure and Algorithm	Sorting	Assertion	Reasoning	English	Using the direct insertion sort algorithm to sort 21, 32, 46, 40, 80, 69, 90, 94, the number of comparisons is 9	False	In the first pass, inserting 32 requires 1 comparison; in the second pass, inserting 46 requires 1 comparison; in the third pass, inserting 40 requires 2 comparisons because 40 is smaller than 46 but larger than 32; in the fourth pass, inserting 80 requires 1 comparison; in the fifth pass, inserting 69 requires 2 comparisons... resulting in a total of 9 comparisons.
472	Test	Data Structure and Algorithm	Sorting	Assertion	Reasoning	English	If only three passes of multi-way merge sort are performed on 27 elements, the minimum number of merge paths selected must be at least 3.	True	Using the formula logk27, the requirement here is k, and the number of merge paths can be obtained by substituting it as 3.
473	Test	Data Structure and Algorithm	Sorting	Assertion	Reasoning	English	Perform radix sort on the set {05,46,13,55,94,17,42}, the result after one pass is 42, 13, 94, 05, 55, 46, 17.	True	Simulate the cardinality sorting process
474	Test	Data Structure and Algorithm	Sorting	Assertion	Reasoning	English	Under general circumstances, a binary search tree is the data structure with the lowest search efficiency.	False	Binary sorting trees are more efficient
887	Test	Computer Organization	Overview	Assertion	Knowledge	English	The characteristics of the first generation of computers include the use of vacuum tubes as logic elements and programming in machine language.	True	null
888	Test	Computer Organization	Overview	Assertion	Knowledge	English	The PC holds the address of the next instruction to be executed.	True	null
889	Test	Computer Organization	Overview	Assertion	Knowledge	English	Moore's Law primarily describes the phenomenon where the number of transistors on an integrated circuit doubles after a certain period of time.	True	null
890	Test	Computer Organization	Overview	Assertion	Knowledge	English	The function of the Memory Address Register (MAR) is to facilitate addressing.	True	null
891	Test	Computer Organization	Overview	Assertion	Knowledge	English	The basic operational mode of the von Neumann machine is the Multiple Instruction Multiple Data (MIMD) approach.	False	null
892	Test	Computer Organization	Overview	Assertion	Knowledge	English	The bit lengths of MAR and MDR correspond to the address code length and the storage word length, respectively.	True	null
893	Test	Computer Organization	Overview	Assertion	Knowledge	English	The access speed of registers is the fastest, faster than both Cache and memory.	True	null
894	Test	Computer Organization	Overview	Assertion	Knowledge	English	The composition of a CPU does not include memory.	True	null

383

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

In data structures, the logical structure can be divided into linear and non-linear structures.

True

null

384

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

In data structures, a data element refers to the basic unit of data, which can be composed of several data items.

True

null

385

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

Data types in computer science refer to the classification of data storage formats.

False

null

386

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

Data structures mainly consist of three aspects: logical structure, storage structure, and data operations.

True

null

387

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

Algorithms possess characteristics such as finiteness, determinacy, feasibility, input, and output.

True

null

388

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

Designing a good algorithm typically requires consideration of correctness, readability, robustness, efficiency, and low storage requirements.

True

null

389

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

The space complexity of an algorithm is defined by the amount of space occupied by the temporary data generated during the execution of the algorithm.

False

null

390

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

An abstract data type can be used to define a complete data structure.

True

null

391

Test

Data Structure and Algorithm

Overview

Assertion

Knowledge

English

A singly linked list belongs to the logical structure.

False

null

392

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In the ListInsert function of the sequential list, when inserting an element into the middle position of the list, it is necessary to move all elements after the insertion position.

True

null

393

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In the LocateElem function of the sequential list, the correct way to find the position of element e is to return i+1 after the element is found.

True

null

394

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In a singly linked list with a head node, when executing the ListDelete function to delete the ith element, the operation involves finding the (i-1)th node, then disconnecting the ith node and linking to the (i+1)th node.

True

null

395

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In a singly linked list, the GetElem function correctly finds and returns the value of the i-th element bitwise, and it returns a pointer to the i-th node.

True

null

396

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In the List_TailInsert function for creating a singly linked list using the tail insertion method, the new node is inserted at the tail in the list.

True

null

397

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In the initialization of a doubly linked list, the prior pointer of the head node points to NULL, and the next pointer also points to NULL.

True

null

398

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

A linear list is a finite sequence with n data items.

False

null

399

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

A sequential list is a storage method for a linear table, where the most common operations are accessing elements at any specified index and performing insertions or deletions at the end, which can save time.

True

null

400

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

When using a sequential storage structure for a non-empty linear list of length n, to insert a data element at the ith position in the list, the valid range for i should be 1≤i≤n.

False

null

401

Test

Data Structure and Algorithm

Linear List

Assertion

Knowledge

English

In a static linked list, the pointer represents the address of the element pointed to by the left link or right link.

False

null

402

Test

Data Structure and Algorithm

Linear List

Assertion

Reasoning

English

In the insertion algorithm for sequential lists, when n spaces are full, an additional m spaces can be requested. If the request fails, it indicates that the system does not have m contiguous spaces available for allocation.

False

Sequential storage requires continuous storage space. When applying, it is necessary to apply for n+m continuous storage spaces, and then copy the original n elements of the linear table to the first n units of the newly applied n+m continuous storage spaces.

403

Test

Data Structure and Algorithm

Linear List

Assertion

Reasoning

English

In a singly linked list, given that the node pointed to by q is the predecessor of the node pointed to by p, to insert node S between q and p, execute q->next=s; s->next=p;.

True

After the insertion of s, q becomes the predecessor of s, while p becomes the successor of s.

404

Test

Data Structure and Algorithm

Linear List

Assertion

Reasoning

English

In a singly linked list h with a head node and a length of n, where there is a tail pointer r, the operation to delete the last element of the linked list is related to the length of the list.

True

To delete the last node of a singly linked list, the pointer field of its predecessor node must be set to NULL. This requires traversing from the beginning to find the predecessor node, taking O(n) time, which is dependent on the length of the list. Other operations are independent of the list length, and readers can simulate them on their own.

405

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

The application of queues in page replacement algorithms is to manage memory pages.

True

null

406

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

Special matrices often use compressed storage to save space.

True

null

407

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

Compared to a sequential stack, a linked stack has a fairly obvious advantage, which is that it generally does not encounter the situation of an empty stack.

True

null

408

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

The circular queue is stored in the array A[0...n], and the operation for enqueuing is rear=(rear+1) mod (n+1).

True

null

409

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

The most suitable linked list for implementing a queue is a non-circular singly linked list with a front pointer and a rear pointer.

True

null

410

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Knowledge

English

When performing a deletion operation on a queue with linked storage, both the head and tail pointers need to be modified.

False

null

411

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Reasoning

English

After performing Push, Push, Pop, Push, Pop, Push, Pop, Push operations, the value of the stack pointer is 1005H.

False

Each element requires one storage unit, so each time an element is pushed onto the stack, top is incremented by 1, and each time an element is popped from the stack, top is decremented by 1. The value of the pointer top successively is 1001H, 1002H, 1001H, 1002H, 1001H, 1002H, 1001H, 1002H.

412

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Reasoning

English

To insert a node X into a linked stack with a top pointer named 'top' (without a head node), execute x->next=top->next; top->next=x.

False

When a linked stack is represented by a single linked list without a head node, the push operation inserts a node x at the beginning (i.e., x->next=top), and after insertion, top should point to the newly inserted node x. Please consider the situation when the linked stack has a head node.

413

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Reasoning

English

Use S to represent the push operation and X to represent the pop operation. If the push order of elements is 1234, then to achieve the pop order of 1342, the corresponding sequence of S and X operations is SXSSXXSX.

False

null

414

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Reasoning

English

The stack full condition for the sequential shared stack Share[0:n-1] is when top1 equals top2.

False

null

415

Test

Data Structure and Algorithm

Stack, Queue, and Array

Assertion

Reasoning

English

Assuming the length of the queue represented by a circular singly linked list is n, with the front fixed at the end of the list, if only a head pointer is set, then the time complexity of the enqueue operation is O(n).

True

According to the problem statement, the enqueue operation is performed at the end of the queue, which is the head of the linked list. It is clearly stated in the problem that the linked list only has a head pointer, meaning there is no head node or tail pointer. After enqueuing, the circular singly linked list must maintain its circular nature. The time complexity of finding the tail node in a circular singly linked list with only a head pointer is O(n), therefore the time complexity of the enqueue operation is O(n).

416

Test

Data Structure and Algorithm

String

Assertion

Knowledge

English

The position of a character in the main string refers to the frequency of the character in the string.

False

null

417

Test

Data Structure and Algorithm

String

Assertion

Knowledge

English

The function of the StrCopy operation is to assign one string to another string.

False

null

418

Test

Data Structure and Algorithm

String

Assertion

Knowledge

English

The StrEmpty operation is used to check if a string is empty.

True

null

419

Test

Data Structure and Algorithm

String

Assertion

Knowledge

English

The best-case time complexity of the naive pattern matching algorithm is O(m).

True

null

420

Test

Data Structure and Algorithm

String

Assertion

Knowledge

English

The worst-case time complexity of the KMP algorithm is O(mn).

False

null

421

Test

Data Structure and Algorithm

String

Assertion

Reasoning

English

The operation of concatenation refers to finding the first occurrence of string S_1 in string S_2.

False

Linking is the concatenation of two strings.

422

Test

Data Structure and Algorithm

String

Assertion

Reasoning

English

The characteristic of the KMP algorithm is that the pointer of the main string does not decrease during pattern matching.

True

In the comparison process of the KMP algorithm, the main string does not backtrack, so the pointer of the main string will not decrease.

423

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

The recursive characteristic of a tree is that a tree is composed of multiple branches.

False

null

424

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

The number of nodes in a tree is equal to the sum of the degrees of all nodes minus 1.

False

null

425

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

A full binary tree is a binary tree where every node has two children.

False

null

426

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

The time complexity and space complexity of binary tree traversal are O(n) and O(n)

True

null

427

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

A complete binary tree with 124 leaf nodes can have at most 250 nodes.

False

null

428

Test

Data Structure and Algorithm

Tree

Assertion

Knowledge

English

A threaded binary tree with n nodes contains n + 1 threads.

True

null

429

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

In a complete binary tree, if a node does not have a left child, then it must be a leaf node.

True

In a complete binary tree, if there is a node of degree 1, there can only be one, and the node has only the left child and no right child

430

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

Given a binary tree with 2n nodes, where m < n, it is impossible to have 2m nodes with degree 0.

False

Property 1 of binary trees indicates that n_0 = n_2 + 1. The total number of nodes = 2n = n_0 + n_1 + n_2 = n_1 + 2n_2 + 1, thus n_1 = 2(n - n_2) - 1. Therefore, n_1 is odd, which means that it is impossible for the binary tree to have 2m nodes with degree 1.

431

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

If a complete binary tree with a depth of 6 has 3 leaf nodes on the 6th level, then the binary tree has a total of 17 leaf nodes.

True

A complete binary tree with a depth of 6 has 2^4=16 nodes on the 5th level. The 6th level has 3 leaf nodes on the far left, whose parent nodes are the two leftmost nodes on the 5th level. Therefore, the remaining nodes on the 5th level are all leaf nodes, totaling 16-2=14. Adding the 3 leaf nodes from the 6th level, there are a total of 17 leaf nodes.

432

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

During an inorder traversal, the condition for n to come before m is that n is a descendant of m.

False

In-order traversal involves first visiting the left subtree, then visiting the root node, and finally visiting the right subtree.

433

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

The post-order traversal result of this binary tree is FEDCBA.

False

For this kind of traversal sequence oriented problem, the binary tree is obtained according to the traversal results, and the corresponding traversal sequence is found. For example, in this problem, knowing the results of the precedent and intermediate order traversal, we can know that the root node of the tree is A, the left subtree has C and B, and the rest is the right subtree, then in the posterior sequence overtime result, A must be last, and C and B must be in front, and because there is DEF in the precedent and EDF in the middle order, then D is the root of this subtree, so D is ranked after EF in the posterior order, so the answer is false

434

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

To determine if the node *P in a threaded binary tree has a right child, the condition is that P is not null.

False

In a threaded binary tree, ltag/rtag is used to identify whether the left/right pointer field of a node is a thread. When its value is 1, the corresponding pointer field is a thread; when its value is 0, the corresponding pointer field is the left/right child.

435

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

Traversal of a pre-order threaded tree still requires the support of a stack.

False

The traversal of a preorder threaded tree does not require stack support.

436

Test

Data Structure and Algorithm

Tree

Assertion

Reasoning

English

In the forest F, there are 3 trees, with the number of nodes in the first, second, and third trees being M_1, M_2, and M_3, respectively. The number of nodes on the right subtree of the root node of the binary tree corresponding to forest F is M_2 + M_3.

True

The conversion rule from a forest to a binary tree is also "left child, right sibling". However, unlike ordinary trees, each tree in a forest is independent, so we first need to treat the root nodes of each tree as sibling nodes. Therefore, in the given problem, after the conversion of the forest, Tree 2 becomes the right subtree of the root node of Tree 1, and Tree 3 becomes the right subtree of the root node of Tree 2. Thus, the number of nodes on the right subtree of the root node of the binary tree corresponding to forest F is M_2 + M_3.

437

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

The characteristic of a graph's vertex and edge sets is that they can both be empty.

False

null

438

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

A connected graph is characterized by the fact that any two vertices are connected, and an undirected graph has at least n-1 edges.

True

null

439

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

The weight of an edge refers to the number of vertices that the edge connects.

False

null

440

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

In a directed complete graph, the range of the number of edges is from 0 to n.

False

null

441

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

The characteristic of representing a graph with an adjacency list is that it can only represent undirected graphs.

False

null

442

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

The cross-linked list is a storage method with the highest space complexity.

False

null

443

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

The operation NextNeighbor(G, x, y) can be used to determine whether there is an edge from vertex x to vertex y in the graph.

False

null

444

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

To retrieve and set the weight of an edge in a graph, you can use Get_edge_value(G, x, y) to obtain the weight of the edge between node x and node y in graph G, or use Set_edge_value(G, x, y, v) to set the weight of the edge between node x and node y in graph G to v.

True

null

445

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

To find the first adjacent vertex and the next adjacent vertex in a graph, you can use FirstNeighbor(G, x) to find the first adjacent vertex of vertex x, and then use NextNeighbor(G, x, y) to find the next adjacent vertex of vertex x after the adjacent vertex y.

True

null

446

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

An undirected graph with n vertices and n edges must contain a cycle.

True

null

447

Test

Data Structure and Algorithm

Graph

Assertion

Knowledge

English

In a directed graph with n vertices, the degree of each vertex can reach up to 2n.

False

null

448

Test

Data Structure and Algorithm

Graph

Assertion

Reasoning

English

If a single depth-first search from any vertex of an undirected graph can visit all vertices, then the graph must be strongly connected.

False

A strongly connected graph is a directed graph, which contradicts the title; A depth-first search on the undirected connected graph can access all vertices of the connected graph. An undirected graph with a loop is not necessarily a connected graph, because the loop does not necessarily contain all the nodes of the graph; A connectivity graph may be a tree or it may have a ring.

449

Test

Data Structure and Algorithm

Graph

Assertion

Reasoning

English

The adjacency matrix representation of a graph is unique, while the adjacency list representation is not unique.

True

The adjacency matrix representation is unique because the information of the edges in the graph has a fixed position in the matrix, while the adjacency list is not unique because its construction depends on the order in which the edges are read and the insertion algorithm used in the edge list.

450

Test

Data Structure and Algorithm

Graph

Assertion

Reasoning

English

For a disconnected undirected graph G, when visiting all vertices using depth-first traversal, the number of times DFS is called within the DFSTraverse function is exactly equal to the number of connected components.

True

DFS (or BFS) can be used to calculate the number of connected components in a graph, as a single traversal will inevitably visit all vertices within a connected graph, and DFS will not be invoked again for vertices that have already been visited. Therefore, the number of connected components in a graph is exactly the number of times DFS is called within DFSTraverse().

451

Test

Data Structure and Algorithm

Graph

Assertion

Reasoning

English

In addition to using topological sorting, the Dijkstra algorithm for finding the shortest path can also be used to determine whether there are cycles in a directed graph.

False

Dijkstra's algorithm is not designed to detect cycles in directed graphs.

452

Test

Data Structure and Algorithm

Graph

Assertion

Reasoning

English

For a directed graph with n vertices and e edges stored using an adjacency list, the time complexity of performing a breadth-first traversal is O(e).

False

Breadth-first traversal requires the use of a queue for implementation. When using an adjacency list to perform breadth-first traversal on a graph, each vertex needs to be enqueued once (vertex list traversal), so the time complexity is O(n). In the process of searching for the adjacent vertices of all vertices, each edge is visited at least once (edge list traversal), thus the time complexity is O(e). Therefore, the overall time complexity of the algorithm is O(n+e).

453

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The process involves randomly accessing the data set.

False

null

454

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

A lookup table is an arbitrary collection of data.

False

null

455

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

Common operations on lookup tables include deleting data elements.

False

null

456

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The search length refers to the duration of the search process.

False

null

457

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The Average Search Length (ASL) is determined by calculating the average number of records accessed during all search processes.

False

null

458

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

Binary search is applicable to ordered sequential lists.

True

null

459

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The characteristic of block search is that both within and between blocks are ordered.

False

null

460

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The characteristic of the direct addressing hash function is its simplicity and the absence of collisions, but it may lead to a waste of storage space.

True

null

461

Test

Data Structure and Algorithm

Searching

Assertion

Knowledge

English

The mid-square method is suitable for situations where only a few digits of the key are significant.

False

null

462

Test

Data Structure and Algorithm

Searching

Assertion

Reasoning

English

For an ordered singly linked list of length n, if the probability of searching for each element is equal, the average search length for a successful search of any element in the list is (n + 1)/2.

True

Performing sequential search on an ordered singly linked list, the average search length for a successful search is the same as that for sequential search on an unordered or ordered sequential list, which is (n+1)/2.

463

Test

Data Structure and Algorithm

Searching

Assertion

Reasoning

English

Hash search is a lookup method that can only be performed on sequential storage structures.

False

binary search can only be performed on sequential storage and requires that the keys are ordered.

464

Test

Data Structure and Algorithm

Searching

Assertion

Reasoning

English

In open addressing, the "clustering" problem that occurs when hashing to the same address is caused by conflicts between synonyms or non-synonyms.

True

In open addressing, the "clustering" issue arises when synonyms and non-synonyms interleave their probing sequences due to hashing to the same address, causing keyword searches to require longer probing distances and reducing the efficiency of hashing. Therefore, it is important to choose a good collision resolution method to avoid "clustering."

465

Test

Data Structure and Algorithm

Searching

Assertion

Reasoning

English

When using chaining to handle collisions, if insertion is restricted to the head of the list, the time to insert any element is the same. However, using chaining to handle collisions can easily lead to clustering.

False

Synonym collision is not equivalent to clustering; when handling collisions with the chaining method, synonyms are placed in the same linked list, which does not cause clustering.

466

Test

Data Structure and Algorithm

Sorting

Assertion

Knowledge

English

Sorting is the process of arranging the elements in a list in a random order.

False

null

467

Test

Data Structure and Algorithm

Sorting

Assertion

Knowledge

English

In direct insertion sort with a sentinel, the role of the sentinel is to speed up the search process.

True

null

468

Test

Data Structure and Algorithm

Sorting

Assertion

Knowledge

English

The average time complexity of direct insertion sort is O(n^2).

True

null

469

Test

Data Structure and Algorithm

Sorting

Assertion

Knowledge

English

The best-case time complexity of quicksort is O(n^1.3).

False

null

470

Test

Data Structure and Algorithm

Sorting

Assertion

Knowledge

English

In a min-heap containing n keys, the record with the maximum key could possibly be stored at position n/2.

False

null

471

Test

Data Structure and Algorithm

Sorting

Assertion

Reasoning

English

Using the direct insertion sort algorithm to sort 21, 32, 46, 40, 80, 69, 90, 94, the number of comparisons is 9

False

In the first pass, inserting 32 requires 1 comparison; in the second pass, inserting 46 requires 1 comparison; in the third pass, inserting 40 requires 2 comparisons because 40 is smaller than 46 but larger than 32; in the fourth pass, inserting 80 requires 1 comparison; in the fifth pass, inserting 69 requires 2 comparisons... resulting in a total of 9 comparisons.

472

Test

Data Structure and Algorithm

Sorting

Assertion

Reasoning

English

If only three passes of multi-way merge sort are performed on 27 elements, the minimum number of merge paths selected must be at least 3.

True

Using the formula logk27, the requirement here is k, and the number of merge paths can be obtained by substituting it as 3.

473

Test

Data Structure and Algorithm

Sorting

Assertion

Reasoning

English

Perform radix sort on the set {05,46,13,55,94,17,42}, the result after one pass is 42, 13, 94, 05, 55, 46, 17.

True

Simulate the cardinality sorting process

474

Test

Data Structure and Algorithm

Sorting

Assertion

Reasoning

English

Under general circumstances, a binary search tree is the data structure with the lowest search efficiency.

False

Binary sorting trees are more efficient

887

Test

Computer Organization

Overview

Assertion

Knowledge

English

The characteristics of the first generation of computers include the use of vacuum tubes as logic elements and programming in machine language.

True

null

888

Test

Computer Organization

Overview

Assertion

Knowledge

English

The PC holds the address of the next instruction to be executed.

True

null

889

Test

Computer Organization

Overview

Assertion

Knowledge

English

Moore's Law primarily describes the phenomenon where the number of transistors on an integrated circuit doubles after a certain period of time.

True

null

890

Test

Computer Organization

Overview

Assertion

Knowledge

English

The function of the Memory Address Register (MAR) is to facilitate addressing.

True

null

891

Test

Computer Organization

Overview

Assertion

Knowledge

English

The basic operational mode of the von Neumann machine is the Multiple Instruction Multiple Data (MIMD) approach.

False

null

892

Test

Computer Organization

Overview

Assertion

Knowledge

English

The bit lengths of MAR and MDR correspond to the address code length and the storage word length, respectively.

True

null

893

Test

Computer Organization

Overview

Assertion

Knowledge

English

The access speed of registers is the fastest, faster than both Cache and memory.

True

null

894

Test

Computer Organization

Overview

Assertion

Knowledge

English

The composition of a CPU does not include memory.

True

null