CareerCup | Cracking The Coding Interview学习记录(C语言实现)

 by   mmc-maodun C++ Version: Current License: No License

kandi X-RAY | CareerCup Summary

kandi X-RAY | CareerCup Summary

CareerCup is a C++ library typically used in Testing applications. CareerCup has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Cracking The Coding Interview 刷题记录.

            kandi-support Support

              CareerCup has a low active ecosystem.
              It has 15 star(s) with 10 fork(s). There are 2 watchers for this library.
              It had no major release in the last 6 months.
              CareerCup has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of CareerCup is current.

            kandi-Quality Quality

              CareerCup has no bugs reported.

            kandi-Security Security

              CareerCup has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              CareerCup does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              CareerCup releases are not available. You will need to build from source code and install.

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            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of CareerCup
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            CareerCup Key Features

            No Key Features are available at this moment for CareerCup.

            CareerCup Examples and Code Snippets

            No Code Snippets are available at this moment for CareerCup.

            Community Discussions


            What does $1 ++ $0 mean in the closure for Swift?
            Asked 2020-Apr-13 at 18:36

            I was looking at the code for how to remove duplicates from a list and I came upon some syntax I am unfamiliar with. What does $1 ++ $0 mean?



            Answered 2020-Apr-13 at 18:36

            $0 is the first parameter passed into the closure.

            $1 is the second parameter.

            ++ is a custom infix operator



            ((PtrToStruct)*(unsigned int*)ADDRESS)
            Asked 2018-Oct-18 at 08:48

            Before I asked I have research similar question. The most closet is this:

            But I still don't understand, what is the meaning of this code?



            Answered 2018-Oct-18 at 08:41

            Many hardware systems have memory mapped registers, places where they store or read data. On small embedded direct-to-hardware systems it's common that those registers are placed in fixed locations, i.e. addresses.

            What the macro does is basically allow access in a nicer way to such a location, instead of having to write all the casting and dereferencing each and every time.

            More specifically, on the location of ADDRESS (0x2000) there seems to be stored a pointer to a structure of type VEC.

            With (unsigned int*)ADDRESS the macro pretends that the value of ADDRESS is really a pointer to unsigned int. The macro then dereference that pointer, to get the value stored in memory at ADDRESS. Lastly, this value is then converted to a pointer to VEC.



            k closest points to the origin
            Asked 2018-Aug-23 at 04:57

            I have a list of points: [(x, y), (x, y), (x ,y) ... (x, y)]. I want the k nearest points to (0, 0).

            I'm trying to implement something like in this link. However, I am implementing the algorithm incorrectly, and I'm not sure where it's going wrong. I think perhaps heapify doesn't know how to maintain order between points. How can I solve this?

            code ...


            Answered 2018-Mar-10 at 15:24

            Since you're already using heapq, you might as well use the nsmallest function instead of reinventing it:



            How to find all possible lengths of a board made up from planks?
            Asked 2018-Apr-08 at 19:58

            The problem is as follows: we want to build a wooden board composed of exactly k planks. We're given two types of planks: shorter and longer. How to determine all possible lengths of such a board?

            The solution to this problem can be found here.

            The pseudocode is:



            Answered 2018-Apr-08 at 19:58

            I think you are misunderstanding the question. The algorithm never takes into account how many of each type of plank you have, only that you have various lengths to choose from. So if you call the function:



            Calculating space complexity of string compression - Cracking the coding interview
            Asked 2018-Mar-06 at 14:06

            I am trying to understand space complexity of the following piece of code. The code compresses Strings from "aabbbb" to "a2b4". The question is Question 5, Chapter 1 from Cracking the coding interview version 5 (2013) and the code is taken from the solutions



            Answered 2018-Mar-06 at 13:16

            You are asking about the space complexity of compressBetter, which includes a call to countCompression, but also performs additional work.

            While the space complexity of countCompression is indeed O(1), compressBetter has linear space complexity (i.e. O(N)) in the worst case (where no two consecutive characters of the input String are equal), since it produces a StringBuffer of 2N characters in that case.



            Algorithms Runtime complexity:
            Asked 2018-Feb-01 at 22:45

            At careercup site, there was this problem (



            Answered 2018-Feb-01 at 20:55

            You are right, in the worst case this is not O(n^2).

            The author obviously assumed that list from map> would contain only few members; it is the assumption similar to the one that we use when we state that the complexity of find operation of a hash table is O(1). Recall, a hash table whose collision resolution is based on separate chaining has a constant complexity of find operation on average, but in case when many elements hash to the same value it can degrade to a linear complexity.

            Implementation-wise, notice that map map> needs to be a hash table (i.e. std::unordered_map in C++, HashMap in Java), not std::map (or TreeMap in Java) because with std::map just the find operation is O(logn).



            Java 2 threads with 2 different objects
            Asked 2018-Jan-31 at 13:55

            Given the below mentioned code and suppose that we have two different threads thread1,thread2 as well as two different objects p1 and p2 of the class BCell. If thread1 executes p1.swap(p2) and thread2 executes p2.swap(p1) simultaneously what is a possible problem that may occur? I have already read here and here but it didn't seem to help.



            Answered 2018-Jan-31 at 13:54

            Here is a synchronized instance method:



            Big(O) of finding K element in a MinHeap build from 2 unsorted arrays
            Asked 2017-Feb-16 at 17:57

            Given the question here. which asks: Given two unsorted int arrays, find the kth element in the merged, sorted array. k element in an index that starts at 1.

            What would be the BigO performance of the solution below (prints 1):



            Answered 2017-Feb-16 at 17:57

            It takes O(n) time to build the heap, and it requires O(n) extra space.

            Finding the kth item is O(k log n) Each call to minheap.dequeue requires O(log n), and you're making k calls.

            This approach works if you have enough memory to hold everything in memory. If you don't have enough memory, say you're doing this with two absolutely huge files, then the process is slightly different. See Time complexity of Kth smallest using Heap.


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


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