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• Why are data structures so important in interviews?

  - by Vamsi Emani

  I am a newbie into the corporate world recently graduated in computers. I am a java/groovy developer. I am a quick learner and I can learn new frameworks, APIs or even programming languages within considerably short amount of time. Albeit that, I must confess that I was not so strong in data structures when I graduated out of college. Through out the campus placements during my graduation, I've witnessed that most of the biggie tech companies like Amazon, Microsoft etc focused mainly on data structures. It appears as if data structures is the only thing that they expect from a graduate. Adding to this, I see that there is this general perspective that a good programmer is necessarily a one with good knowledge about data structures. To be honest, I felt bad about that. I write good code. I follow standard design patterns of coding, I do use data structures but at the superficial level as in java exposed APIs like ArrayLists, LinkedLists etc. But the companies usually focused on the intricate aspects of Data Structures like pointer based memory manipulation and time complexities. Probably because of my java-ish background, Back then, I understood code efficiency and logic only when talked in terms of Object Oriented Programming like Objects, instances, etc but I never drilled down into the level of bits and bytes. I did not want people to look down upon me for this knowledge deficit of mine in Data Structures. So really why all this emphasis on Data Structures? Does, Not having knowledge in Data Structures really effect one's career in programming? Or is the knowledge in this subject really a sufficient basis to differentiate a good and a bad programmer?

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• Uses of persistent data structures in non-functional languages

  - by Ray Toal

  Languages that are purely functional or near-purely functional benefit from persistent data structures because they are immutable and fit well with the stateless style of functional programming. But from time to time we see libraries of persistent data structures for (state-based, OOP) languages like Java. A claim often heard in favor of persistent data structures is that because they are immutable, they are thread-safe. However, the reason that persistent data structures are thread-safe is that if one thread were to "add" an element to a persistent collection, the operation returns a new collection like the original but with the element added. Other threads therefore see the original collection. The two collections share a lot of internal state, of course -- that's why these persistent structures are efficient. But since different threads see different states of data, it would seem that persistent data structures are not in themselves sufficient to handle scenarios where one thread makes a change that is visible to other threads. For this, it seems we must use devices such as atoms, references, software transactional memory, or even classic locks and synchronization mechanisms. Why then, is the immutability of PDSs touted as something beneficial for "thread safety"? Are there any real examples where PDSs help in synchronization, or solving concurrency problems? Or are PDSs simply a way to provide a stateless interface to an object in support of a functional programming style?

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• Serializing Data Structures in C

  - by src

  I've recently read three separate books on algorithms and data structures, tcp/ip socket programming, and programming with memory. The book about memory briefly discussed the topic of serializing data structures for the purposes of storing it to disk, or sending it across a network. I can't help but wonder why the the other two books didn't discuss serialization at all. After an unsuccessful web/book search I'm left wondering where I can find a good book/paper/tutorial on serializing data structures in C? Where or how did you learn it?

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• Clever ways of implementing different data structures in C & data structures that should be used mor

  - by Yktula

  What are some clever (not ordinary) ways of implementing data structures in C, and what are some data structures that should be used more often? For example, what is the most effective way (generating minimal overhead) to implement a directed and cyclic graph with weighted edges in C? I know that we can store the distances in an array as is done here, but what other ways are there to implement this kind of a graph?

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• Data Structures usage and motivational aspects

  - by Aubergine

  For long student life I was always wondering why there are so many of them yet there seems to be lack of usage at all in many of them. The opinion didn't really change when I got a job. We have brilliant books on what they are and their complexities, but I never encounter resources which would actually give a good hint of practical usage. I perfectly understand that I have to look at problem , analyse required operations, look for data structure that does them efficiently. However in practice I never do that, not because of human laziness syndrome, but because when it comes to work I acknowledge time priority over self-development. Over time I thought that when I would be better developer I will automatically use more of them - that didn't happen at all or maybe I just didn't. Then I found that the colleagues usually in the same plate as me - knowing more or less some three of data structures and being totally happy about it and refusing to discuss this matter further with me, coming back to conversations about 'cool new languages' 'libraries that do jobs for you' and the joy to work under scrumban etc. I am stuck with ArrayLists, Arrays and SortedMap , which no matter what I do always suffice or either I tweak them to be capable of fulfilling my task. Yes, it might be inefficient but do we really have to care if Intel increases performance over years no matter if we improve our skills? Does new Xeon or IBM machines really care what we use? What if I like build things, but I am not particularly excited whether it is n log(n) or just n? Over twenty years the processing power increased enormously, which gives us freedom of not being critical about which one to use? On top of that new more optimized languages appear which support multiple cores more efficiently. To be more specific: I would like to find motivational material on complex real areas/cases of possible effective usages of data structures. I would be really grateful if you would provide relevant resources. There is similar question ,but in the end the links again mostly describe or do dumb example(vehicles, students or holy grail quest - yes, very relevant) them and people keep referring to the "scenario decides the data structure to use". I want to know these complex scenarios to be able to identify similarities to my scenario and then use them. The complex scenarios where it really matters and not necessarily of quantitive nature. It seems that data structures only concern is efficiency and nothing else? There seems to be no particular convenience for developer in use one over another. (only when I found scientific resources on why exactly simple carbohydrates are evil I stopped eating sugar and candies completely replacing it with less harmful fruits - I hope you can see the analogy)

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• What do I need to know about Data Structures and Algorithms in the "real" world

  - by Ray T Champion

  I just finished the data structures and algorithms course in school , I took it during the summer so 6wks course vs a 16 wk course during the regular semester. So not only was the course hard but it was really really really fast. My question is what do I need to know about data structures in the real world? I understand what they do and how they work, for the most part, but I had a real tough time coding them , I wouldn't be able to write the code for a binary tree class or a balanced tree class from scratch .... Is that bad? should I retake it , or is knowledge of how they work sufficient, without being able to write the classes from scratch?

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• Data structures in functional programming

  - by pwny

  I'm currently playing with LISP (particularly Scheme and Clojure) and I'm wondering how typical data structures are dealt with in functional programming languages. For example, let's say I would like to solve a problem using a graph pathfinding algorithm. How would one typically go about representing that graph in a functional programming language (primarily interested in pure functional style that can be applied to LISP)? Would I just forget about graphs altogether and solve the problem some other way?

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• Which useful alternative control structures do you know?

  - by bigown

  Similar question was closed on SO. Sometimes when we're programming, we find that some particular control structure would be very useful to us, but is not directly available in our programming language. What alternative control structures do you think are a useful way of organizing computation? The goal here is to get new ways of thinking about structuring code, in order to improve chunking and reasoning. You can create a wishful syntax/semantic not available now or cite a less known control structure on an existent programming language. Answers should give ideas for a new programming language or enhancing an actual language. Think of this as brainstorming, so post something you think is a crazy idea but it can be viable in some scenario. It's about imperative programming.

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• Graph data structures and journal format for mini-IDE

  - by matec

  Background: I am writing a small/partial IDE. Code is internally converted/parsed into a graph data structure (for fast navigation, syntax-check etc). Functionality to undo/redo (also between sessions) and restoring from crash is implemented by writing to and reading from journal. The journal records modifications to the graph (not to the source). Question: I am hoping for advice on a decision on data-structures and journal format. For the graph I see two possible versions: g-a Graph edges are implemented in the way that one node stores references to other nodes via memory address g-b Every node has an ID. There is an ID-to-memory-address map. Graph uses IDs (instead of addresses) to connect nodes. Moving along an edge from one node to another each time requires lookup in ID-to-address map. And also for the journal: j-a There is a current node (like current working directory in a shell + file-system setting). The journal contains entries like "create new node and connect to current", "connect first child of current node" (relative IDs) j-b Journal uses absolute IDs, e.g. "delete edge 7 - 5", "delete node 5" I could e.g. combine g-a with j-a or combine g-b with j-b. In principle also g-b and j-a should be possible. [My first/original attempt was g-a and a version of j-b that uses addresses, but that turned out to cause severe restrictions: nodes cannot change their addresses (or journal would have to keep track of it), and using journal between two sessions is a mess (or even impossible)] I wonder if variant a or variant b or a combination would be a good idea, what advantages and disadvantages they would have and especially if some variant might be causing troubles later.

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• Internal Mutation of Persistent Data Structures

  - by Greg Ros

  To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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• Is there a way to track data structure dependencies from the database, through the tiers, all the way out to a web page?

  - by Sean Mickey

  When we design applications, we generally end up with the same tiered sets of data structures: A persistent data structure that is described using DDL and implemented as RDBMS tables and columns. A set of domain objects that consist primarily of data structures, usually combined with business-rule level logic, that are implemented in a programming language such as Java. A set of service layer interfaces that directly support use case implementations (which use the domain data structures as parameters), implemented as EJBs or something equivalent in another programming language. UI screens that allow users to C reate, R etrieve, U pdate, and (maybe) D elete all manner of data structures and graphs of data structures, with numerous screens and with multiple UI widgets, all structured to support the same data structures. But if you want to change the data structures in any of these tiers, it always seems extremely difficult to assess the impact(s) the change will have across the application. UML can help, but tracing through diagram after diagram is not a real solution to this problem. The best I have ever seen was a homespun data tracking spreadsheet document that listed all of the data structures and walked the relationships from tier-to-tier. Is there a tool or accepted approach that makes it easy to identify a data structure in any tier and easily obtain a list of all dependent: database table and column data structures domain object data structures service layer interface methods and parameter data structures screen & UI component data structures

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• Is wikipedia a valuable resource for studying data structures? (can we call it complete?)

  - by Amir Nasr

  Can I depend on wikipedia to learn data structures fully using the list of data structures http://en.wikipedia.org/wiki/List_of_data_structures and the links they refer to? The same question for algorithms http://en.wikipedia.org/wiki/List_of_algorithm_general_topics ?... What's after learning algorithms and data structures? Specializing in a certain field of algorithms such as computer graohics, memory management...etc? or what could be the plan for mastering programming after knowing the language syntax and the background about program design and programming logic? I asked about wikipedia because i would like to find a complete resource or are least a resource which would be enough for the field of data structures instead of searching for separate articles in different places in other words an alternative to books which may even be more complete.

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• How often do you use data structures (ie Binary Trees, Linked Lists) in your jobs/side projects?

  - by Chris2021

  It seems to me that, for everyday use, more primitive data structures like arrays get the job done just as well as a binary tree would. My question is how common is to use these structures when writing code for projects at work or projects that you pursue in your free time? I understand the better insertion time/deletion time/sorting time for certain structures but would that really matter that much if you were working with a relatively small amount of data?

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• Why would you use data structures (ie Binary Trees, Linked Lists) in your jobs/side projects? [closed]

  - by Chris2021

  It seems to me that, for everyday use, more primitive data structures like arrays get the job done just as well as a binary tree would. My question is how common is to use these structures when writing code for projects at work or projects that you pursue in your free time? I understand the better insertion time/deletion time/sorting time for certain structures but would that really matter that much if you were working with a relatively small amount of data?

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• Which algorithms/data structures should I "recognize" and know by name?

  - by Earlz

  I'd like to consider myself a fairly experienced programmer. I've been programming for over 5 years now. My weak point though is terminology. I'm self-taught, so while I know how to program, I don't know some of the more formal aspects of computer science. So, what are practical algorithms/data structures that I could recognize and know by name? Note, I'm not asking for a book recommendation about implementing algorithms. I don't care about implementing them, I just want to be able to recognize when an algorithm/data structure would be a good solution to a problem. I'm asking more for a list of algorithms/data structures that I should "recognize". For instance, I know the solution to a problem like this: You manage a set of lockers labeled 0-999. People come to you to rent the locker and then come back to return the locker key. How would you build a piece of software to manage knowing which lockers are free and which are in used? The solution, would be a queue or stack. What I'm looking for are things like "in what situation should a B-Tree be used -- What search algorithm should be used here" etc. And maybe a quick introduction of how the more complex(but commonly used) data structures/algorithms work. I tried looking at Wikipedia's list of data structures and algorithms but I think that's a bit overkill. So I'm looking more for what are the essential things I should recognize?

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• How to present a stable data model in a public API that allows internal data structures to be changed without breaking the public view of the data?

  - by Max Palmer

  I am in the process of developing an application that allows users to write C# scripts. These scripts allow users to call selected methods and to access and manipulate data in a document. This works well, however, in the development version, scripts access the document's (internal) data structures directly. This means that if we were to change the internal data model/structure, there is a good chance that someone's script will no longer compile. We obviously want to prevent this breaking change from happening, but still want to allow the user to write sensible C# code (whilst not restricting how we develop our internal data model as a result). We therefore need to decouple our scripting API and its data structures from our internal methods and data structures. We've a few ideas as to how we might allow the user to access a what is effectively a stable public version of the document's internal data*, but I wanted to throw the question out there to someone who might have some real experience of this problem. NB our internal document's data structure is quite complex and it could be quite difficult to wrap. We know we want to expose as little as possible in our public API, especially as once it's out there, it's out there for good. Can anyone help? How do scripting languages / APIs decouple their public API and data structures from their internal data structures? Is there no real alternative to having to write a complex interaction layer? If we need to do this, what's a good approach or pattern for wrapping complex data structures that include nested objects, including collections? I've looked at the API facade pattern, which looks like it's trying to address these kinds of issues, but are there alternatives? *One idea is to build a data facade that is kept stable across versions of our application. The facade exposes a set of facade data objects that are used in the script code. These maintain backwards compatibility and wrap access to our internal document's data model.

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• Should I keep investing into data structures and algorithms?

  - by 4bu3li

  These days, I'm investing heavily in data structures and algorithms and trying to solve some programming puzzles. I'm trying to code and solve with Java and Clojure. Am I wasting my time? should I invest more in technologies and frameworks that I already know in order to gain deeper knowledge (the ins and the outs) and be able to code with them more quickly? By studying data structures and algorithms, am I going to become a better programmer or those subjects are only important during college years?

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• When and why are certain data structures used in the context of web development?

  - by Ein Doofus

  While browsing around the MSDN I came across: http://msdn.microsoft.com/en-us/library/aa287104%28v=vs.71%29 which lists various data structures such as: Queues Stacks Hashtables Binary Trees Binary Search Trees Graphs (I believe there are also Lists) and I was hoping to get a high-level overview of when these various data structures can be used in the broad context of web development, and when used, why one data structure is generally used instead of any other one.

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• Should I keep investing into data structures and algorithms?

  - by Chiron

  These days, I'm investing heavily in data structures and algorithms and trying to solve some programming puzzles. I'm trying to code and solve with Java and Clojure. Am I wasting my time? should I invest more in technologies and frameworks that I already know in order to gain deeper knowledge (the ins and the outs) and be able to code with them more quickly? By studying data structures and algorithms, am I going to become a better programmer or those subjects are only important during college years?

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• Explaining persistent data structures in simple terms

  - by Jason Baker

  I'm working on a library for Python that implements some persistent data structures (mainly as a learning exercise). However, I'm beginning to learn that explaining persistent data structures to people unfamiliar with them can be difficult. Can someone help me think of an easy (or at least the least complicated) way to describe persistent data structures to them? I've had a couple of people tell me that the documentation that I have is somewhat confusing. (And before anyone asks, no I don't mean persistent data structures as in persisted to the file system. Google persistent data structures if you're unclear on this.)

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• Serializing persistent/functional data structures

  - by Rob

  Persistent data structures depend on the sharing of structure for efficiency. For an example, see here. How can I preserve the structure sharing when I serialize the data structures and write them to a file or database? If I just naively traverse the datastructures, I'll store the correct values, but I'll lose the structure sharing. I'd like to be able to save data-structures with shared components to a file, restore them, and still have most of the structure shared in the restored data.

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• java: libraries for immutable functional-style data structures

  - by Jason S

  This is very similar to another question (Functional Data Structures in Java) but the answers there are not particularly useful. I need to use immutable versions of the standard Java collections (e.g. HashMap / TreeMap / ArrayList / LinkedList / HashSet / TreeSet). By "immutable" I mean immutable in the functional sense (e.g. purely functional data structures), where updating operations on the data structure do not change the original data, but instead return a new instance of the same kind of data structure. Also typically new and old instances of the data structure will share immutable data to be efficient in time and space. From what I can tell my options include: Functional Java Scala Clojure but I'm not sure whether any of these are particularly appealing to me. I have a few requirements/desirements: the collections in question should be usable directly in Java (with the appropriate libraries in the classpath). FJ would work for me; I'm not sure if I can use Scala's or Clojure's data structures in Java w/o having to use the compilers/interpreters from those languages and w/o having to write Scala or Clojure code. Core operations on lists/maps/sets should be possible w/o having to create function objects with confusing syntaxes (FJ looks slightly iffy) They should be efficient in time and space. I'm looking for a library which ideally has done some performance testing. FJ's TreeMap is based on a red-black tree, not sure how that rates. Documentation / tutorials should be good enough so someone can get started quickly using the data structures. FJ fails on that front. Any suggestions?

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• List of generic algorithms and data structures

  - by Jake Petroules

  As part of a library project, I want to include a plethora of generic algorithms and data structures. This includes algorithms for searching and sorting, data structures like linked lists and binary trees, path-finding algorithms like A*... the works. Basically, any generic algorithm or data structure you can think of that you think might be useful in such a library, please post or add it to the list. Thanks! (NOTE: Because there is no single right answer I've of course placed this in community wiki... and also, please don't suggest algorithms which are too specialized to be provided by a generic library) The List: Data structures AVL tree B-tree B*-tree B+-tree Binary tree Binary heap Binary search tree Linked lists Singly linked list Doubly linked list Stack Queue Sorting algorithms Binary tree sort Bubble sort Heapsort Insertion sort Merge sort Quicksort Selection sort Searching algorithms

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• Define "cyclic data structures"

  - by Earlz

  At the JSON site it says JSON does not support cyclic data structures, so be careful to not give cyclical structures to the JSON stringifier. What does it mean by this? Can someone give me an example of such a data structure in Javascript?

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• Is using MultiMaps code smell? If so what alternative data structures fit my needs?

  - by Pureferret

  I'm trying to model nWoD characters for a roleplaying game in a character builder program. The crux is I want to support saving too and loading from yaml documents. One aspect of the character's is their set of skills. Skills are split between exactly three 'types': Mental, Physical, and Social. Each type has a list of skills under if. My Yaml looks like this: PHYSICAL: Athletics: 0 Brawl: 3 MENTAL: Academics: 2 Computers My initial thought was to use a Multimap of some sort, and have the skill type as an Enum, and key to my map. Each Skill is an element in the collection that backs the multimap. However, I've been struggling to get the yaml to work. On explaining this to a colleague outside of work they said this was probably a sign of code smell, and he's never seen it used 'well'. Are multiMaps really code smell? If so what alternate data structures would suit my goals?

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