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  • Shared hosting banwidth limits

    - by mike
    I have a shared hosting account with a 20GB monthly bandwidth limit. I have exceeded my monthly limit and according to my host my counter is never reset, they say they use a continuous 30 day counter. So for example, I make payment on the 1st of each month, say I use 20GB in the last week of the month. My bandwidth counter is not reset on the 1st of the new month and my bandwidth will only become available in the last week of the new month. Is this common practice by shared hosting companies? Sounds a bit shady to me. Surely my counters should be reset on the 1st of every month when I make payment and 20GB of bandwidth should be available from the day payment is made?

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  • Is it normal for programmer to work on multiple projects simultaneously.

    - by gasan
    On a current job I have 2 projects to work on. First is very huge system and the second one is smaller but it also big (first project is being developed for 12 years, second for 4 years). At first I was working only on first project and was trying to get used to it. Then I was moved to second project and tried there, so my knowledge about first project became shady. Now I have to work on both projects at the same time. It's very hard for me because despite they both use java, they use different frameworks and the amount of code and business-logic to understand is very big so I really can't hold both that projects in my head. Is it normal and I should get used to it, although my expertise became very squashy, what won't happen if I would work only on a single project? Or should I raise a concern or maybe change employer?

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  • Sorting Algorithms

    - by MarkPearl
    General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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  • Are there any worse sorting algorithms than Bogosort (a.k.a Monkey Sort)?

    - by womp
    My co-workers took me back in time to my University days with a discussion of sorting algorithms this morning. We reminisced about our favorites like StupidSort, and one of us was sure we had seen a sort algorithm that was O(n!). That got me started looking around for the "worst" sorting algorithms I could find. We postulated that a completely random sort would be pretty bad (i.e. randomize the elements - is it in order? no? randomize again), and I looked around and found out that it's apparently called BogoSort, or Monkey Sort, or sometimes just Random Sort. Monkey Sort appears to have a worst case performance of O(∞), a best case performance of O(n), and an average performance of O(n * n!). Are there any named algorithms that have worse average performance than O(n * n!)? Or are just sillier than Monkey Sort in general?

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  • Integrate forum software into existing Zend site

    - by mrbubblesort
    I've searched around and haven't really found anything on this, so maybe someone here has tried this before. My company already has a website built with Zend, and we'd like to add in a forum as well. All I really need is something that will work with postgresql and has foreign language support (particularly Japanese, but if worst comes to worst, I'll just translate it myself). phpBB fits all my needs though. Is it possible to get the two working together? Or is there another forum software that'll work with Zend? Or is it better to just build the thing from scratch? Thanks!

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  • Javascript substrings multiline replace by RegExp

    - by Radek Šimko
    Hi, I'm having some troubles with matching a regular expression in multi-line string. <script> var str="Welcome to Google!\n"; str = str + "We are proud to announce that Microsoft has \n"; str = str + "one of the worst Web Developers sites in the world."; document.write(str.replace(/.*(microsoft).*/gmi, "$1")); </script> http://jsbin.com/osoli3/3/edit As you may see on the link above, the output of the code looks like this: Welcome to Google! Microsoft one of the worst Web Developers sites in the world. Which means, that the replace() method goes line by line and if there's no match in that line, it returns just the whole line... Even if it has the "m" (multiline) modifier...

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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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  • Feedback Filtration&ndash;Processing Negative Comments for Positive Gains

    - by D'Arcy Lussier
    After doing 7 conferences, 5 code camps, and countless user group events, I feel that this is a post I need to write. I actually toyed with other names for this post, however those names would just lend itself to the type of behaviour I want people to avoid – the reactionary, emotional response that speaks to some deeper issue beyond immediate facts and context. Humans are incredibly complex creatures. We’re also emotional, which serves us well in certain situations but can hinder us in others. Those of us in leadership build up a thick skin because we tend to encounter those reactionary, emotional responses more often, and we’re held to a higher standard because of our positions. While we could react with emotion ourselves, as the saying goes – fighting fire with fire just makes a bigger fire. So in this post I’ll share my thought process for dealing with negative feedback/comments and how you can still get value from them. The Thought Process Let’s take a real-world example. This week I held the Prairie IT Pro & Dev Con event. We’ve gotten a lot of session feedback already, most of it overwhelmingly positive. But some not so much – and some to an extreme I rarely see but isn’t entirely surprising to me. So here’s the example from a person we’ll refer to as Mr. Horrible: How was the speaker? Horrible! Worst speaker ever! Did the session meet your expectations? Hard to tell, speaker ruined it. Other Comments: DO NOT bring this speaker back! He was at this conference last year and I hoped enough negative feedback would have taught you to not bring him back...obviously not...I will not return to this conference next year if this speaker is brought back. Now those are very strong words. “Worst speaker ever!” “Speaker ruined it” “I will not return to this conference next year if the speaker is brought back”. The speakers I invite to speak at my conference are not just presenters but friends and colleagues. When I see this, my initial reaction is of course very emotional: I get defensive, I get angry, I get offended. So that’s where the process kicks in. Step 1 – Take a Deep Breath Take a deep breath, calm down, and walk away from the keyboard. I didn’t do that recently during an email convo between some colleagues and it ended up in my reacting emotionally on Twitter – did I mention those colleagues follow my Twitter feed? Yes, I ate some crow. Ok, now that we’re calm, let’s move on to step 2. Step 2 – Strip off the Emotion We need to take off the emotion that people wrap their words in and identify the root issues. For instance, if I see: “I hated this session, the presenter was horrible! He spoke so fast I couldn’t make out what he was saying!” then I drop off the personal emoting (“I hated…”) and the personal attack (“the presenter was horrible”) and focus on the real issue this person had – that the speaker was talking too fast. Now we have a root cause of the displeasure. However, we’re also dealing with humans who are all very different. Before I call up the speaker to talk about his speaking pace, I need to do some other things first. Back to our Mr. Horrible example, I don’t really have much to go on. There’s no details of how the speaker “ruined” the session or why he’s the “worst speaker ever”. In this case, the next step is crucial. Step 3 – Validate the Feedback When I tell people that we really like getting feedback for the sessions, I really really mean it. Not just because we want to hear what individuals have to say but also because we want to know what the group thought. When a piece of negative feedback comes in, I validate it against the group. So with the speaker Mr. Horrible commented on, I go to the feedback and look at other people’s responses: 2 x Excellent 1 x Alright 1 x Not Great 1 x Horrible (our feedback guy) That’s interesting, it’s a bit all over the board. If we look at the comments more we find that the people who rated the speaker excellent liked the presentation style and found the content valuable. The one guy who said “Not Great” even commented that there wasn’t anything really wrong with the presentation, he just wasn’t excited about it. In that light, I can try to make a few assumptions: - Mr. Horrible didn’t like the speakers presentation style - Mr. Horrible was expecting something else that wasn’t communicated properly in the session description - Mr. Horrible, for whatever reason, just didn’t like this presenter Now if the feedback was overwhelmingly negative, there’s a different pattern – one that validates the negative feedback. Regardless, I never take something at face value. Even if I see really good feedback, I never get too happy until I see that there’s a group trend towards the positive. Step 4 – Action Plan Once I’ve validated the feedback, then I need to come up with an action plan around it. Let’s go back to the other example I gave – the one with the speaker going too fast. I went and looked at the feedback and sure enough, other people commented that the speaker had spoken too quickly. Now I can go back to the speaker and let him know so he can get better. But what if nobody else complained about it? I’d still mention it to the speaker, but obviously one person’s opinion needs to be weighed as such. When we did PrDC Winnipeg in 2011, I surveyed the attendees about the food. Everyone raved about it…except one person. Am I going to change the menu next time for that one person while everyone else loved it? Of course not. There’s a saying – A sure way to fail is to try to please everyone. Let’s look at the Mr. Horrible example. What can I communicate to the speaker with such limited information provided in the feedback from Mr. Horrible? Well looking at the groups feedback, I can make a few suggestions: - Ensure that people understand in the session description the style of the talk - Ensure that people understand the level of detail/complexity of the talk and what prerequisite knowledge they should have I’m looking at it as possibly Mr. Horrible assumed a much more advanced talk and was disappointed, while the positive feedback by people who – from their comments – suggested this was all new to them, were thrilled with the session level. Step 5 – Follow Up For some feedback, I follow up personally. Especially with negative or constructive feedback, its important to let the person know you heard them and are making changes because of their comments. Even if their comments were emotionally charged and overtly negative, it’s still important to reach out personally and professionally. When you remove the emotion, negative comments can be the best feedback you get. Also, people have bad days. We’ve all had one of “those days” where we talked more sternly than normal to someone, or got angry at something we’d normally shrug off. We have various stresses in our lives and sometimes they seep out in odd ways. I always try to give some benefit of the doubt, and re-evaluate my view of the person after they’ve responded to my communication. But, there is such a thing as garbage feedback. What Mr. Horrible wrote is garbage. It’s mean spirited. It’s hateful. It provides nothing constructive at all. And a tell-tale sign that feedback is garbage – the person didn’t leave their name even though there was a field for it. Step 6 – Delete It Feedback must be processed in its raw form, and the end products should drive improvements. But once you’ve figured out what those things are, you shouldn’t leave raw feedback lying around. They are snapshots in time that taken alone can be damaging. Also, you should never rest on past praise. In a future blog post, I’m going to talk about how we can provide great feedback that, even when its critical, can still be constructive.

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  • Alerts for when Login Failures Strike

    When repeated SQL Server login failures occur, a DBA should investigate. It could just be someone repeatedly typing in the wrong password. Worst case is a virus attack flooding your network with connection requests. Receiving an e-mail while login failures are occurring allows DBAs to investigate and fix the issue as soon as possible. So how is DBA notified of login failures without flooding their inbox?

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  • Red Gate Rolls Out the Red Carpet for SQL Server Users

    SQL in the City, the unique event for database developers and administrators organized by Red Gate Software, hits the streets of London and Seattle this fall. Now in its fourth year, it features presentations by some of the world’s top SQL Server speakers. Can 41,000 DBAs really be wrong? Join 41,000 other DBAs who are following the new series from the DBA Team: the 5 Worst Days in a DBA’s Life. Part 3, As Corrupt As It Gets, is out now – read it here.

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  • What’s in YOUR Recovery Plan?

    Author Craig Outcalt gives advice on preparing for the worst with a look at what you should consider putting in your disaster recovery plan and why. Make working with SQL a breezeSQL Prompt 5.3 is the effortless way to write, edit, and explore SQL. It's packed with features such as code completion, script summaries, and SQL reformatting, that make working with SQL a breeze. Try it now.

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  • Interpolating Matrices

    - by sebf
    Hello, Apologies if I am missing something very obvious (likely!) but is there anything wrong with interpolating between two matrices by: float d = (float)(targetTime.Ticks - keyframe_start.ticks) / (float)(keyframe_end.ticks - keyframe_start.ticks); return ((keyframe_start.Transform * (1 - d)) + (keyframe_end.Transform * d)); As in my app, when I try an use this to interpolate between two keyframes, the model begins to 'shrink' - the severity based on how far between the two keyframes the target time is; its worst when the transform split is ~50/50.

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  • fully encrypt website using SSL

    - by eddywebs
    I had been trying to use SSL for the following site http://bit.ly/e8Lj32 , although the SSL certificate is signed properly by networksolutions , each time the pages are loaded it still displays an SSl warning in browser warning "Some parts of the site are not using SSL" , in I.E, its even worst if you hit "no I dont want view unsecured part of the page" site does not display properly (as it blocks some of the widgets) screenshots upped at http://i.imgur.com/fm5GO.png

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  • Shelving &ndash; What is it &ndash; and more importantly, can it help me?

    - by Chris Skardon
    Since we shifted to TFS we’ve had the ability to perform what is known as ‘shelving’. Shelving (whilst not a wholly new topic in the world of SCC) is new to us, and didn’t exist in our previous SCC solution – SVN. Soo… what is it? What? Shelving is a way to check-in but not check-in your code. By shelving you submit a copy of your ‘pending changes’ to the SCC server, (which maintains a list of the shelvesets) and once that is done you can either continue working, or undo your changes, safe in the knowledge that a backup copy exists on the server. You can unshelve your code at any time and get back to the state you were when you shelved. Yer, that is great but why not just check it in?? Shelvesets don’t have to build. The shelveset you put in there could be entirely broken, or it might solve every bug in the system – shelves aren’t continuously integrated so you can shelve anything. Hmmmm… What else? Shelving allows us to do some pretty cool stuff that beforehand was quite frankly a pain. For instance – Gated Check-ins are implemented via the shelving mechanism, when code is checked-in, what you’re actually doing is shelving it, the Build Controller will build the shelveset with the original code and if it succeeds, the code will be committed, if it fails – well – it’s only you that has to fix the code :) Other nice features are things like the ability to share code you are working on… For example, if I was having trouble with a particular piece of code, I could shelve it, and then you (yes you) could then get that shelveset and check out the problem for yourself, and if you fix it?? Well – you could check-it in! Nice, but day-to-day shizzle? Let’s say you’ve been working on your project and your project manager comes over to you and says: “Hey, errr, bad times, there is an urgent bug we need you to fix, it needs to go out now!” (also for this to play out – we’ll need to assume you’re currently working in the 'release’ branch for another bug fix (maybe))… You could undo all your current changes (obviously you’ll probably backup your code using zip or something I imagine) fix the bug, then re-copy your backup over the top, or you could shelve and unshelve. Perhaps some other uses will awaken the shelver in you… :) Before each checkin – if you shelve, you no longer need to worry (if indeed you do) about resolving conflicts and mysteriously losing your code… Going home at night? Not checking in straight away? Why not shelve, this way – should the worst come to the worst and your local pc gives up, you can just get the shelveset onto another machine and be up and running in literally seconds minutes…

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  • Cursor running wild, then crashes on an Asus G73sw

    - by Yarchmon
    The cursor sometimes goes wild, I get random clicks, the windows are resizing, the cursor disappears. In the worst case, clicks and keyboards are disabled. I've tried the solution given on doc.ubuntu-fr.org and add tu grub : i8042.nomux=1 i8042.reset=1 in GRUB_CMDLINE_LINUX_DEFAULT But it didn't work What can I do ? Graphic card : Geforce GTX460M. Ubuntu : 11.10 (64 bits). Laptop Asus G73sw Interface : Unity (since 11.10) - didn't get this problem with Gnome before. Complement: when a window is resizing, it gets drag-boxes at every corner, center of sides and center of the window. It looks like my touchpad sends random info, or like a "ghost" touchscreen. lspci result : 00:00.0 Host bridge: Intel Corporation 2nd Generation Core Processor Family DRAM Controller (rev 09) 00:01.0 PCI bridge: Intel Corporation Xeon E3-1200/2nd Generation Core Processor Family PCI Express Root Port (rev 09) 00:16.0 Communication controller: Intel Corporation 6 Series/C200 Series Chipset Family MEI Controller #1 (rev 04) 00:1a.0 USB Controller: Intel Corporation 6 Series/C200 Series Chipset Family USB Enhanced Host Controller #2 (rev 05) 00:1b.0 Audio device: Intel Corporation 6 Series/C200 Series Chipset Family High Definition Audio Controller (rev 05) 00:1c.0 PCI bridge: Intel Corporation 6 Series/C200 Series Chipset Family PCI Express Root Port 1 (rev b5) 00:1c.1 PCI bridge: Intel Corporation 6 Series/C200 Series Chipset Family PCI Express Root Port 2 (rev b5) 00:1c.3 PCI bridge: Intel Corporation 6 Series/C200 Series Chipset Family PCI Express Root Port 4 (rev b5) 00:1c.5 PCI bridge: Intel Corporation 6 Series/C200 Series Chipset Family PCI Express Root Port 6 (rev b5) 00:1d.0 USB Controller: Intel Corporation 6 Series/C200 Series Chipset Family USB Enhanced Host Controller #1 (rev 05) 00:1f.0 ISA bridge: Intel Corporation HM65 Express Chipset Family LPC Controller (rev 05) 00:1f.2 SATA controller: Intel Corporation 6 Series/C200 Series Chipset Family 6 port SATA AHCI Controller (rev 05) 00:1f.3 SMBus: Intel Corporation 6 Series/C200 Series Chipset Family SMBus Controller (rev 05) 01:00.0 VGA compatible controller: nVidia Corporation GF106 [GeForce GTX 460M] (rev a1) 01:00.1 Audio device: nVidia Corporation GF106 High Definition Audio Controller (rev a1) 03:00.0 Network controller: Atheros Communications Inc. AR9285 Wireless Network Adapter (PCI-Express) (rev 01) 04:00.0 USB Controller: Fresco Logic FL1000G USB 3.0 Host Controller (rev 04) 05:00.0 Ethernet controller: Realtek Semiconductor Co., Ltd. RTL8111/8168B PCI Express Gigabit Ethernet controller (rev 06) Edit 01-09-12: Tried on Ubuntu 2D: the behavior is different: it's like i'm randomly clicking on the workspace switcher icon. In the worst case, it can happen several times in a minute.

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  • Which language is best for OpenGL?

    - by Neurofluxation
    Well, this is silly - I've had to post a question about programming on a site other than stackoverflow... Worst thing they have ever done.. I have the following list of languages: C++ C# VB.Net D Delphi Euphoria GLUT Java Power Basic Python REALbasic Visual Basic I would like to know what people think is the: *a) Best (most efficient) language to work with OpenGL* and b) What is the easiest language to work with OpenGL Thanks in advance guys n gals!

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  • Analysing Indexes - reducing scans.

    - by GrumpyOldDBA
    The whole subject of database/application tuning is sometimes akin to a black art, it's pretty easy to find your worst 20 whatever but actually seeking to reduce operational overhead can be slightly more tricky. If you ever read through my analysing indexes post you'll know I have a number of ways of seeking out ways to tune the database. -- This is a slightly different slant on one of those which produced an interesting side effect. -- We all know that except for very small tables avoiding...(read more)

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  • Speaking - Red Gate's SQL in the City

    - by AllenMWhite
    The great folks at Red Gate have invited me to join the festivities at the SQL in the City events in both Chicago on October 5, and in Seattle on November 5. In both cities I'll be presenting a session entitled Automated Deployment: Application And Database Releases Without The Headache . Here's the abstract: Ever since applications were first created, the deployment of updates and changes has been a headache, with the potential of disruption of the application at best and data corruption at worst....(read more)

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  • Google Page Ranking - Now You See it, Now You Don't

    Probably the worst nightmare internet marketers and even experienced SEO specialists encounter when they promote their websites on the web is the severe dropping of their websites rankings in Google. Now you may be in trouble if you are an SEO consultant, and you have a client, and he gets to know that his website has disappeared on the first page of Google when you've just told him a few days ago that his site landed on the number 1 spot of Google.

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  • Google and Linux are coming to your TV

    <b>Cyber Cynic:</b> "In what may have been Google's worst kept secret in years, Google, along with its partners, Intel, Logitech and Sony, is on its way to delivering the Web to your television. What will they be using to do this? Why, they'll be using Google's Android Linux, of course."

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  • Great Websites Are the Windows of Your Online Success

    The World Wide Web is continuing to expand unabated at phenomenal rates, even in recent times, when many conventional businesses and individuals are suffering from the worst economic downturn in decades. The reason behind this amazing explosion of activity is quite clear. More and more people are turning to the internet as a means of earning either a second income stream, or indeed, making the internet their main source of income, and creating new websites is the premier choice of "shop window" for most online businesses.

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  • Applying the Knuth-Plass algorithm (or something better?) to read two books with different length and amount of chapters in parallel

    - by user147133
    I have a Bible reading plan that covers the whole Bible in 180 days. For the most of the time, I read 5 chapters in the Old Testament and 1 or 2 (1.5) chapters in the New Testament each day. The problem is that some chapters are longer than others (for example Psalm 119 which is 7 times longer than a average chapter in the Bible), and the plan I'm following doesn't take that in count. I end up with some days having a lot more to read than others. I thought I could use programming to make myself a better plan. I have a datastructure with a list of all chapters in the bible and their length in number of lines. (I found that the number of lines is the best criteria, but it could have been number of verses or number of words as well) I then started to think about this problem as a line wrap problem. Think of a chapter like a word, a day like a line and the whole plan as a paragraph. The "length" of a word (a chapter) is the number of lines in that chapter. I could then generate the best possible reading plan by applying a simplified Knuth-Plass algorithm to find the best breakpoints. This works well if I want to read the Bible from beginning to end. But I want to read a little from the new testament each day in parallel with the old testament. Of course I can run the Knuth-Plass algorithm on the Old Testament first, then on the New Testament and get two separate plans. But those plans merged is not a optimal plan. Worst-case days (days with extra much reading) in the New Testament plan will randomly occur on the same days as the worst-case days in the Old Testament. Since the New Testament have about 180*1.5 chapters, the plan is generally to read one chapter the first day, two the second, one the third etc... And I would like the plan for the Old Testament to compensate for this alternating length. So I will need a new and better algorithm, or I will have to use the Knuth-Plass algorithm in a way that I've not figured out. I think this could be a interesting and challenging nut for people interested in algorithms, so therefore I wanted to see if any of you have a good solution in mind.

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  • T-SQL User-Defined Functions: Ten Questions You Were Too Shy To Ask

    SQL Server User-Defined Functions are good to use in most circumstances, but there just a few questions that rarely get asked on the forums. It's a shame, because the answers to them tend to clear up some ingrained misconceptions about functions that can lead to problems, particularly with locking and performance Can 41,000 DBAs really be wrong? Join 41,000 other DBAs who are following the new series from the DBA Team: the 5 Worst Days in a DBA’s Life. Part 3, As Corrupt As It Gets, is out now – read it here.

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