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  • Big O Complexity of a method

    - by timeNomad
    I have this method: public static int what(String str, char start, char end) { int count=0; for(int i=0;i<str.length(); i++) { if(str.charAt(i) == start) { for(int j=i+1;j<str.length(); j++) { if(str.charAt(j) == end) count++; } } } return count; } What I need to find is: 1) What is it doing? Answer: counting the total number of end occurrences after EACH (or is it? Not specified in the assignment, point 3 depends on this) start. 2) What is its complexity? Answer: the first loops iterates over the string completely, so it's at least O(n), the second loop executes only if start char is found and even then partially (index at which start was found + 1). Although, big O is all about worst case no? So in the worst case, start is the 1st char & the inner iteration iterates over the string n-1 times, the -1 is a constant so it's n. But, the inner loop won't be executed every outer iteration pass, statistically, but since big O is about worst case, is it correct to say the complexity of it is O(n^2)? Ignoring any constants and the fact that in 99.99% of times the inner loop won't execute every outer loop pass. 3) Rewrite it so that complexity is lower. What I'm not sure of is whether start occurs at most once or more, if once at most, then method can be rewritten using one loop (having a flag indicating whether start has been encountered and from there on incrementing count at each end occurrence), yielding a complexity of O(n). In case though, that start can appear multiple times, which most likely it is, because assignment is of a Java course and I don't think they would make such ambiguity. Solving, in this case, is not possible using one loop... WAIT! Yes it is..! Just have a variable, say, inc to be incremented each time start is encountered & used to increment count each time end is encountered after the 1st start was found: inc = 0, count = 0 if (current char == start) inc++ if (inc > 0 && current char == end) count += inc This would also yield a complexity of O(n)? Because there is only 1 loop. Yes I realize I wrote a lot hehe, but what I also realized is that I understand a lot better by forming my thoughts into words...

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  • Is there a shorthand term for O(n log n)?

    - by jemfinch
    We usually have a single-word shorthand for most complexities we encounter in algorithmic analysis: O(1) == "constant" O(log n) == "logarithmic" O(n) == "linear" O(n^2) == "quadratic" O(n^3) == "cubic" O(2^n) == "exponential" We encounter algorithms with O(n log n) complexity with some regularity (think of all the algorithms dominated by sort complexity) but as far as I know, there's no single word we can use in English to refer to that complexity. Is this a gap in my knowledge, or a real gap in our English discourse on computational complexity?

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  • Disable password complexity rule in Active Directory

    - by Dan Revell
    Where do I go to disable the password complexity policy for the domain. I've logged onto the domain controller (Windows Server 2008) and found the option in local policies which is of course locked from any changes. However I can't find the same sort of policies in the group policy manager. Which nodes do I have to expand out to find it?

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  • Tricky Big-O complexity

    - by timeNomad
    public void foo (int n, int m) { int i = m; while (i > 100) i = i/3; for (int k=i ; k>=0; k--) { for (int j=1; j<n; j*=2) System.out.print(k + "\t" + j); System.out.println(); } } I figured the complexity would be O(logn). That is as a product of the inner loop, the outer loop -- will never be executed more than 100 times, so it can be omitted. What I'm not sure about is the while clause, should it be incorporated into the Big-O complexity? For very large i values it could make an impact, or arithmetic operations, doesn't matter on what scale, count as basic operations and can be omitted?

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  • Time Complexities of recursive algorithms

    - by Peter
    Whenever I see a recursive solution, or I write recursive code for a problem, it is really difficult for me to figure out the time complexity, in most of the cases I just say its exponential? How is it exponential actually? How people say it is 2^n, when it is n!, when it is n^n or n^k. I have some questions in mind, let say find all permutations of a string (O(n!)) find all sequences which sum up to k in an array (exponential, how exactly do I calculate). Find all subsets of size k whose sum is 0 (will k come somewhere in complexity , it should come right?). Can any1 help me how to calculate the exact complexity of such questions, I am able to wrote code for them , but its hard understanding the exact time complexity.

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  • Should I consider memmove() O(n) or O(1) ?

    - by Andrei Ciobanu
    Hello, this may be a silly question, but I want to calculate the complexity of one of my algorithms, and I am not sure what complexity to consider for the memmove() function. Can you please help / explain ? void * memmove ( void * destination, const void * source, size_t num ); So is the complexity O(num) or O(1). I suppose it's O(num), but I am not sure as I lack for now the understanding of what's going on under the hood.

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  • A specific data structure

    - by user550413
    Well, this question is a bit specific but I think there is some general idea in it that I can't get it. Lets say I got K servers (which is a constant that I know its size). I have a program that get requests and every request has an id and server id that will handle it. I have n requests - unknown size and can be any number. I need a data structure to support the next operations within the given complexity: GetServer - the function gets the request ID and returns the server id that is supposed to handle this request at the current situation and not necessarily the original server (see below). Complexity: O(log K) at average. KillServer - the function gets as input a server id that should be removed and another server id that all the requests of the removed server should be passed to. Complexity: O(1) at the worst case. -- Place complexity for all the structure is O(K+n) -- The KillServer function made me think using a Union-Find as I can do the union in O(1) as requested but my problem is the first operation. Why it's LogK? Actually, no matter how I "save" the requests if I want to access to any request (lets say it's an AVL tree) so the complexity will be O(log n) at the worst case and said that I can't assume Kn (and probably K Tried thinking about it a couple of hours but I can't find any solution. Known structures that can be used are: B+ tree, AVL tree, skip list, hash table, Union-Find, rank tree and of course all the basics like arrays and such.

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  • How to know whether to create a general system or to hack a solution

    - by Andy K
    I'm new to coding , learning it since last year actually. One of my worst habits is the following: Often I'm trying to create a solution that is too big , too complex and doesn't achieve what needs to be achieved, when a hacky kludge can make the fit. One last example was the following (see paste bin link below) http://pastebin.com/WzR3zsLn After explaining my issue, one nice person at stackoverflow came with this solution instead http://stackoverflow.com/questions/25304170/update-a-field-by-removing-quarter-or-removing-month When should I keep my code simple and when should I create a 'big', general solution? I feel stupid sometimes for building something so big, so awkward, just to solve a simple problem. It did not occur to me that there would be an easier solution. Any tips are welcomed. Best

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  • c++ write own xml parser vs using tinyxml

    - by AdityaGameProgrammer
    Hi , I am currently in a task to generate an XML file for an srt text file containing timestamps and corresponding text. To generate an exe file which accepts file name input and outputs the relevant XML file to be used as part of an automated script. Is it Advisable to use Tinyxml for this? Is this a very simple task that can be done with minimal programming? Is this one of those things which are very basic to c++ programmers? reason i am asking this is I have recently made a shift into c++ programming after over 3 years of action script development. Edit: your comments regarding this are very much appreciated what's the easiest way to generate xml in c++?

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  • Best Upper Bound & Best Lower Bound of an Algorithm

    - by Nayefc
    I am studying for a final exam and I came past a question I had on an earlier test. The questions asks us to find the minimum value in an unsorted array of integers. We must provide the best upper bound and the best lower bound that you can for the problem in the worst case. First, in such an example, the upper and lower bound are the same (hence, we can talk in terms of Big-Theta). In the worst case, we would have to go through the whole list as the minimum value would be at the end of the list. Therefore, the answer is Big-Theta(n). Is this a correct & good explanation?

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  • What can Go chan do that a list cannot?

    - by alpav
    I want to know in which situation Go chan makes code much simpler than using list or queue or array that is usually available in all languages. As it was stated by Rob Pike in one of his speeches about Go lexer, Go channels help to organize data flow between structures that are not homomorphic. I am interested in a simple Go code sample with chan that becomes MUCH more complicated in another language (for example C#) where chan is not available. I am not interested in samples that use chan just to increase performance by avoiding waiting of data between generating list and consuming the list (which can be solved by chunking) or as a way to organize thread safe queue or thread-safe communication (which can be easily solved by locking primitives). I am interested in a sample that makes code simpler structurally disregarding size of data. If such sample does not exist then sample where size of data matters. I guess desired sample would contain bi-directional communication between generator and consumer. Also if someone could add tag [channel] to the list of available tags, that would be great.

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  • How is technical debt best measured? What metric(s) are most useful?

    - by throp
    If I wanted to help a customer understand the degree of technical debt in his application, what would be the best metric to use? I've stumbled across Erik Doernenburg's code toxicity, and also Sonar's technical debt plugin, but was wondering what others exist. Ideally, I'd like to say "system A has a score of 100 whereas system B has a score of 50, so system A will most likely be more difficult to maintain than system B". Obviously, I understand that boiling down a complex concepts like "technical debt" or "maintainability" into a single number might be misleading or inaccurate (in some cases), however I need a simple way to convey the to a customer (who is not hands-on in the code) roughly how much technical debt is built into their system (relative to other systems), for the goal of building a case for refactoring/unit tests/etc. Again, I'm looking for one single number/graph/visualization, and not a comprehensive list of violations (e.g. CheckStyle, PMD, etc.).

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  • Guidance in naming awkward objects?

    - by GlenH7
    I'm modeling a chemical system, and I'm having problems with naming my objects within an enum. I'm not sure if I should use: the atomic formula the chemical name an abbreviated chemical name. For example, sulfuric acid is H2SO4 and hydrochloric acid is HCl. With those two, I would probably just use the atomic formula as they are reasonably common. However, I have others like sodium hexafluorosilicate which is Na2SiF6. In that example, the atomic formula isn't as obvious (to me) but the chemical name is hideously long: myEnum.SodiumHexaFluoroSilicate. I'm not sure how I would be able to safely come up with an abbreviated chemical name that would have a consistent naming pattern. From a maintenance point of view, which of the options would you prefer to see and why? Audience for the code will be just programmers, not chemists. If that guides the particulars: I'm using C#; I'm starting with 10 - 20 compounds and would have at most 100 compounds. The enum is to facilitate common calculations - the equation is the same for all compounds but you insert a property of the compound to complete the equation.

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  • Guidance in naming awkward domain-specific objects?

    - by GlenH7
    I'm modeling a chemical system, and I'm having problems with naming my objects within an enum. I'm not sure if I should use: the atomic formula the chemical name an abbreviated chemical name. For example, sulfuric acid is H2SO4 and hydrochloric acid is HCl. With those two, I would probably just use the atomic formula as they are reasonably common. However, I have others like sodium hexafluorosilicate which is Na2SiF6. In that example, the atomic formula isn't as obvious (to me) but the chemical name is hideously long: myEnum.SodiumHexaFluoroSilicate. I'm not sure how I would be able to safely come up with an abbreviated chemical name that would have a consistent naming pattern. From a maintenance point of view, which of the options would you prefer to see and why? Some details from comments on this question: Audience for the code will be just programmers, not chemists. I'm using C#, but I think this question is more interesting when ignoring the implementation language I'm starting with 10 - 20 compounds and would have at most 100 compounds. The enum is to facilitate common calculations - the equation is the same for all compounds but you insert a property of the compound to complete the equation. For example, Molar mass (in g/mol) is used when calculating the number of moles from a mass (in grams) of the compound. Another example of a common calculation is the Ideal Gas Law and its use of the Specific Gas Constant

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  • single for-loop runtime explanation problem

    - by owwyess
    I am analyzing some running times of different for-loops, and as I'm getting more knowledge, I'm curious to understand this problem which I have still yet to find out. I have this exercise called "How many stars are printed": for (int i = N; i > 1; i = i/2) System.out.println("*"); The answers to pick from is A: ~log N B: ~N C: ~N log N D: ~0.5N^2 So the answer should be A and I agree to that, but on the other side.. Let's say N = 500 what would Log N then be? It would be 2.7. So what if we say that N=500 on our exercise above? That would most definitely print more han 2.7 stars? How is that related? Because it makes sense to say that if the for-loop looked like this: for (int i = 0; i < N; i++) it would print N stars. I hope to find an explanation for this here, maybe I'm interpreting all these things wrong and thinking about it in a bad way. Thanks in advance.

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  • How does one rein in the complexities of web development ?

    - by Rahul
    I have been a server-side programmer for most of my career and have only recently started spending more time on web development. I am amazed at the number of things I need to master in order to write a decent web application. Just to list down a few tools/technologies I need to learn, Server side programming language (Java/JSP, ASP, PHP, Ruby or something else) A decent web framework (for any medium to big size application). HTML & CSS Javascript Javascript library (JQuery/ExtJS etc. primarily for AJAX). Good to know even if not necessary. At least a basic knowledge of web design - layouts, colors, fonts etc. A good understanding of web security. A good understanding of Performance/scalability issues. Testing, browser compatibility issues etc. The list goes on. So, my question to seasoned web developers is - How do you guys manage to learn and keep yourself updated on so many things? While developing a web application, how do you handle the complexities involved in these areas and yet manage to write an application that is well designed, user friendly, secure, performant and scalable. As a web developer, does one have to be a jack of all trades or should one specialize in one or two areas and leave the rest to other members of the team ?

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  • Need help with this question [closed]

    - by Jaime
    Occasionally, multiplying the sizes of nested loops can give an overestimate for the Big-Oh running time. This result happens when an innermost loop is infrequently executed. Give the Big-O analysis of the running time. Implement the following code and run for several values of N, and compare your analysis with the actual running times. for(int i = 1; i <= n; i++) for(int j = 1; j<=i * i; j++) if(j%i == 0) for(int k = 0; k < j; k++) sum++;

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  • Simplicity-efficiency tradeoff

    - by sarepta
    The CTO called to inform me of a new project and in the process told me that my code is weird. He explained that my colleagues find it difficult to understand due to the overly complex, often new concepts and technologies used, which they are not familiar with. He asked me to maintain a simple code base and to think of the others that will inherit my changes. I've put considerable time into mastering LINQ and thread-safe coding. However, others don't seem to care nor are impressed by anything other than their paycheck. Do I have to keep it simple (stupid), just because others are not familiar with best practices and efficient coding? Or should I continue to do what I find best and write code my way?

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  • Can too much abstraction be bad?

    - by m3th0dman
    As programmers I feel that our goal is to provide good abstractions on the given domain model and business logic. But where should this abstraction stop? How to make the trade-off between abstraction and all it's benefits (flexibility, ease of changing etc.) and ease of understanding the code and all it's benefits. I believe I tend to write code overly abstracted and I don't know how good is it; I often tend to write it like it is some kind of a micro-framework, which consists of two parts: Micro-Modules which are hooked up in the micro-framework: these modules are easy to be understood, developed and maintained as single units. This code basically represents the code that actually does the functional stuff, described in requirements. Connecting code; now here I believe stands the problem. This code tends to be complicated because it is sometimes very abstracted and is hard to be understood at the beginning; this arises due to the fact that it is only pure abstraction, the base in reality and business logic being performed in the code presented 1; from this reason this code is not expected to be changed once tested. Is this a good approach at programming? That it, having changing code very fragmented in many modules and very easy to be understood and non-changing code very complex from the abstraction POV? Should all the code be uniformly complex (that is code 1 more complex and interlinked and code 2 more simple) so that anybody looking through it can understand it in a reasonable amount of time but change is expensive or the solution presented above is good, where "changing code" is very easy to be understood, debugged, changed and "linking code" is kind of difficult. Note: this is not about code readability! Both code at 1 and 2 is readable, but code at 2 comes with more complex abstractions while code 1 comes with simple abstractions.

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  • Simplicity-effecincy tradeoff

    - by sarepta
    The CTO called to inform me of a new project and in the process told me that my code is weird. He explained that my colleagues find it difficult to understand due to the overly complex, often new concepts and technologies used, which they are not familiar with. He asked me to maintain a simple code base and to think of the others that will inherit my changes. I've put considerable time into mastering LINQ and thread-safe coding. However, others don't seem to care nor are impressed by anything other than their paycheck. Do I have to keep it simple (stupid), just because others are not familiar with best practices and efficient coding? Or should I continue to do what I find best and write code my way?

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  • Is there a common programming term for the problems of adding features to an already-featureful program?

    - by Jeremy Friesner
    I'm looking for a commonly used programming term to describe a software-engineering phenomenon, which (for lack of a better way to describe it) I'll illustrate first with a couple of examples-by-analogy: Scenario 1: We want to build/extend a subway system on the outskirts of a small town in Wyoming. There are the usual subway-problems to solve, of course (hiring the right construction company, choosing the best route, buying the subway cars), but other than that it's pretty straightforward to implement the system because there aren't a huge number of constraints to satisfy. Scenario 2: Same as above, except now we need to build/extend the subway system in downtown Los Angeles. Here we face all of the problems we did in case (1), but also additional problems -- most of the applicable space is already in use, and has a vocal constituency which will protest loudly if we inconvenience them by repurposing, redesigning, or otherwise modifying the infrastructure that they rely on. Because of this, extensions to the system happen either very slowly and expensively, or they don't happen at all. I sometimes see a similar pattern with software development -- adding a new feature to a small/simple program is straightforward, but as the program grows, adding further new features becomes more and more difficult, if only because it is difficult to integrate the new feature without adversely affecting any of the large number of existing use-cases or user-constituencies. (even with a robust, adaptable program design, you run into the problem of the user interface becoming so elaborate that the program becomes difficult to learn or use) Is there a term for this phenomenon?

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  • Too complex/too many objects?

    - by Mike Fairhurst
    I know that this will be a difficult question to answer without context, but hopefully there are at least some good guidelines to share on this. The questions are at the bottom if you want to skip the details. Most are about OOP in general. Begin context. I am a jr dev on a PHP application, and in general the devs I work with consider themselves to use many more OO concepts than most PHP devs. Still, in my research on clean code I have read about so many ways of using OO features to make code flexible, powerful, expressive, testable, etc. that is just plain not in use here. The current strongly OO API that I've proposed is being called too complex, even though it is trivial to implement. The problem I'm solving is that our permission checks are done via a message object (my API, they wanted to use arrays of constants) and the message object does not hold the validation object accountable for checking all provided data. Metaphorically, if your perm containing 'allowable' and 'rare but disallowed' is sent into a validator, the validator may not know to look for 'rare but disallowed', but approve 'allowable', which will actually approve the whole perm check. We have like 11 validators, too many to easily track at such minute detail. So I proposed an AtomicPermission class. To fix the previous example, the perm would instead contain two atomic permissions, one wrapping 'allowable' and the other wrapping 'rare but disallowed'. Where previously the validator would say 'the check is OK because it contains allowable,' now it would instead say '"allowable" is ok', at which point the check ends...and the check fails, because 'rare but disallowed' was not specifically okay-ed. The implementation is just 4 trivial objects, and rewriting a 10 line function into a 15 line function. abstract class PermissionAtom { public function allow(); // maybe deny() as well public function wasAllowed(); } class PermissionField extends PermissionAtom { public function getName(); public function getValue(); } class PermissionIdentifier extends PermissionAtom { public function getIdentifier(); } class PermissionAction extends PermissionAtom { public function getType(); } They say that this is 'not going to get us anything important' and it is 'too complex' and 'will be difficult for new developers to pick up.' I respectfully disagree, and there I end my context to begin the broader questions. So the question is about my OOP, are there any guidelines I should know: is this too complicated/too much OOP? Not that I expect to get more than 'it depends, I'd have to see if...' when is OO abstraction too much? when is OO abstraction too little? how can I determine when I am overthinking a problem vs fixing one? how can I determine when I am adding bad code to a bad project? how can I pitch these APIs? I feel the other devs would just rather say 'its too complicated' than ask 'can you explain it?' whenever I suggest a new class.

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  • How can I compute the Big-O notation for a given piece of code?

    - by TheNew Rob Mullins
    So I just took a data structure midterm today and I was asked to determine the run time, in Big O notation, of the following nested loop: for (int i = 0; i < n-1; i++) { for(int j = 0; j < i; j++2) { //1 Statement } } I'm having trouble understanding the formula behind determining the run time. I thought that since the inner loop has 1 statement, and using the series equation of: (n * (n - 1)) / 2, I figured it to be: 1n * (n-1) / 2. Thus equaling (n^2 - 1) / 2. And so I generalized the runtime to be O(n^2 / 2). I'm not sure this is right though haha, was I supposed to divide my answer again by 2 since j is being upped in intervals of 2? Or is my answer completely off?

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  • Finding the median of the merged array of two sorted arrays in O(logN)?

    - by user176517
    Refering to the solution present at MIT handout I have tried to figure out the solution myself but have got stuck and I believe I need help to understand the following points. In the function header used in the solution MEDIAN -SEARCH (A[1 . . l], B[1 . . m], max(1,n/2 - m), min(l, n/2)) I do not understand the last two arguments why not simply 1, l why the max and min respectively. Thanking You.

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