code-complexity

问题 My friend ran into a question in an interview and he was told that there is an O(n) solution. However, neither of us can think it up. Here is the question: There is a string which contains just ( and ) , find the length of the longest valid parentheses substring, which should be well formed. For example ")()())" , the longest valid parentheses is ()() and the length is 4. I figured it out with dynamic programming, but it is not O(n). Any ideas? public int getLongestLen(String s) { if (s ==

来源： https://stackoverflow.com/questions/60740662/c-sharp-linq-selectmany-complexity

来源： https://stackoverflow.com/questions/60740662/c-sharp-linq-selectmany-complexity

问题 How may I find the time complexity of the following code: (Sorry for adding image, I will re-edit my question once I have access to the laptop) What I have done so far: The first loop iterates n times, the second i times and the third log(i*j) times, So after simplifying I got: Sigma from i=0 to n for i*log i + n * (Sigma from j=0 to i for log i) But why this is equal to O(n^2 log(n))? 回答1: If we look at the outermost 2 loops we observe that there are 1 + 2 + 3 ... + n - 1 iterations. Using

问题 How may I find the time complexity of the following code: (Sorry for adding image, I will re-edit my question once I have access to the laptop) What I have done so far: The first loop iterates n times, the second i times and the third log(i*j) times, So after simplifying I got: Sigma from i=0 to n for i*log i + n * (Sigma from j=0 to i for log i) But why this is equal to O(n^2 log(n))? 回答1: If we look at the outermost 2 loops we observe that there are 1 + 2 + 3 ... + n - 1 iterations. Using

问题 for(int i=0; i<array.length -1; i++){ if(array[i] > array[i+1]){ int temp = array[i]; array[i] = array[i+1]; array[i+1]=temp; i=-1; } } I think the code sorts the input array and that its worst case complexity is O(n). What is the correct big-O complexity of this code? 回答1: It's O(n^3), and it's an inefficient version of bubble sort. The code scans through the array looking for the first adjacent pair of out-of-order elements, swaps them, and then restarts from the beginning of the array. In

问题 for(int i=0; i<array.length -1; i++){ if(array[i] > array[i+1]){ int temp = array[i]; array[i] = array[i+1]; array[i+1]=temp; i=-1; } } I think the code sorts the input array and that its worst case complexity is O(n). What is the correct big-O complexity of this code? 回答1: It's O(n^3), and it's an inefficient version of bubble sort. The code scans through the array looking for the first adjacent pair of out-of-order elements, swaps them, and then restarts from the beginning of the array. In

问题 I want to know how will it affect to the Cyclomatic Complexity when having multiple start or stop nodes in a control flow diagram.If you could explain the relationship between Cyclomatic Complexity and Start/Stop nodes it will be a great help. 回答1: • A control flow graph can consist of many starts and stops. But according to McCabe's theory, if it is consist of multiple starts and stops it doesn't satisfy the formula. 来源： https://stackoverflow.com/questions/60485378/what-would-happen-if-a

问题 I want to know how will it affect to the Cyclomatic Complexity when having multiple start or stop nodes in a control flow diagram.If you could explain the relationship between Cyclomatic Complexity and Start/Stop nodes it will be a great help. 回答1: • A control flow graph can consist of many starts and stops. But according to McCabe's theory, if it is consist of multiple starts and stops it doesn't satisfy the formula. 来源： https://stackoverflow.com/questions/60485378/what-would-happen-if-a

问题 I have looked around, but can't seem to find the answer to my question. Here is the context : I have to connect to a Database in my Java program and execute a SQL request that I have no control over and don't know in advance. To do that I use the code below. public Collection<HashMap<String, String>> runQuery(String request, int maxRows) { List<HashMap<String, String>> resultList = new ArrayList<>(); DataSource datasource = null; try { Context initContext = new InitialContext(); datasource =