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  • How to find and fix performance problems in ORM powered applications

    - by FransBouma
    Once in a while we get requests about how to fix performance problems with our framework. As it comes down to following the same steps and looking into the same things every single time, I decided to write a blogpost about it instead, so more people can learn from this and solve performance problems in their O/R mapper powered applications. In some parts it's focused on LLBLGen Pro but it's also usable for other O/R mapping frameworks, as the vast majority of performance problems in O/R mapper powered applications are not specific for a certain O/R mapper framework. Too often, the developer looks at the wrong part of the application, trying to fix what isn't a problem in that part, and getting frustrated that 'things are so slow with <insert your favorite framework X here>'. I'm in the O/R mapper business for a long time now (almost 10 years, full time) and as it's a small world, we O/R mapper developers know almost all tricks to pull off by now: we all know what to do to make task ABC faster and what compromises (because there are almost always compromises) to deal with if we decide to make ABC faster that way. Some O/R mapper frameworks are faster in X, others in Y, but you can be sure the difference is mainly a result of a compromise some developers are willing to deal with and others aren't. That's why the O/R mapper frameworks on the market today are different in many ways, even though they all fetch and save entities from and to a database. I'm not suggesting there's no room for improvement in today's O/R mapper frameworks, there always is, but it's not a matter of 'the slowness of the application is caused by the O/R mapper' anymore. Perhaps query generation can be optimized a bit here, row materialization can be optimized a bit there, but it's mainly coming down to milliseconds. Still worth it if you're a framework developer, but it's not much compared to the time spend inside databases and in user code: if a complete fetch takes 40ms or 50ms (from call to entity object collection), it won't make a difference for your application as that 10ms difference won't be noticed. That's why it's very important to find the real locations of the problems so developers can fix them properly and don't get frustrated because their quest to get a fast, performing application failed. Performance tuning basics and rules Finding and fixing performance problems in any application is a strict procedure with four prescribed steps: isolate, analyze, interpret and fix, in that order. It's key that you don't skip a step nor make assumptions: these steps help you find the reason of a problem which seems to be there, and how to fix it or leave it as-is. Skipping a step, or when you assume things will be bad/slow without doing analysis will lead to the path of premature optimization and won't actually solve your problems, only create new ones. The most important rule of finding and fixing performance problems in software is that you have to understand what 'performance problem' actually means. Most developers will say "when a piece of software / code is slow, you have a performance problem". But is that actually the case? If I write a Linq query which will aggregate, group and sort 5 million rows from several tables to produce a resultset of 10 rows, it might take more than a couple of milliseconds before that resultset is ready to be consumed by other logic. If I solely look at the Linq query, the code consuming the resultset of the 10 rows and then look at the time it takes to complete the whole procedure, it will appear to me to be slow: all that time taken to produce and consume 10 rows? But if you look closer, if you analyze and interpret the situation, you'll see it does a tremendous amount of work, and in that light it might even be extremely fast. With every performance problem you encounter, always do realize that what you're trying to solve is perhaps not a technical problem at all, but a perception problem. The second most important rule you have to understand is based on the old saying "Penny wise, Pound Foolish": the part which takes e.g. 5% of the total time T for a given task isn't worth optimizing if you have another part which takes a much larger part of the total time T for that same given task. Optimizing parts which are relatively insignificant for the total time taken is not going to bring you better results overall, even if you totally optimize that part away. This is the core reason why analysis of the complete set of application parts which participate in a given task is key to being successful in solving performance problems: No analysis -> no problem -> no solution. One warning up front: hunting for performance will always include making compromises. Fast software can be made maintainable, but if you want to squeeze as much performance out of your software, you will inevitably be faced with the dilemma of compromising one or more from the group {readability, maintainability, features} for the extra performance you think you'll gain. It's then up to you to decide whether it's worth it. In almost all cases it's not. The reason for this is simple: the vast majority of performance problems can be solved by implementing the proper algorithms, the ones with proven Big O-characteristics so you know the performance you'll get plus you know the algorithm will work. The time taken by the algorithm implementing code is inevitable: you already implemented the best algorithm. You might find some optimizations on the technical level but in general these are minor. Let's look at the four steps to see how they guide us through the quest to find and fix performance problems. Isolate The first thing you need to do is to isolate the areas in your application which are assumed to be slow. For example, if your application is a web application and a given page is taking several seconds or even minutes to load, it's a good candidate to check out. It's important to start with the isolate step because it allows you to focus on a single code path per area with a clear begin and end and ignore the rest. The rest of the steps are taken per identified problematic area. Keep in mind that isolation focuses on tasks in an application, not code snippets. A task is something that's started in your application by either another task or the user, or another program, and has a beginning and an end. You can see a task as a piece of functionality offered by your application.  Analyze Once you've determined the problem areas, you have to perform analysis on the code paths of each area, to see where the performance problems occur and which areas are not the problem. This is a multi-layered effort: an application which uses an O/R mapper typically consists of multiple parts: there's likely some kind of interface (web, webservice, windows etc.), a part which controls the interface and business logic, the O/R mapper part and the RDBMS, all connected with either a network or inter-process connections provided by the OS or other means. Each of these parts, including the connectivity plumbing, eat up a part of the total time it takes to complete a task, e.g. load a webpage with all orders of a given customer X. To understand which parts participate in the task / area we're investigating and how much they contribute to the total time taken to complete the task, analysis of each participating task is essential. Start with the code you wrote which starts the task, analyze the code and track the path it follows through your application. What does the code do along the way, verify whether it's correct or not. Analyze whether you have implemented the right algorithms in your code for this particular area. Remember we're looking at one area at a time, which means we're ignoring all other code paths, just the code path of the current problematic area, from begin to end and back. Don't dig in and start optimizing at the code level just yet. We're just analyzing. If your analysis reveals big architectural stupidity, it's perhaps a good idea to rethink the architecture at this point. For the rest, we're analyzing which means we collect data about what could be wrong, for each participating part of the complete application. Reviewing the code you wrote is a good tool to get deeper understanding of what is going on for a given task but ultimately it lacks precision and overview what really happens: humans aren't good code interpreters, computers are. We therefore need to utilize tools to get deeper understanding about which parts contribute how much time to the total task, triggered by which other parts and for example how many times are they called. There are two different kind of tools which are necessary: .NET profilers and O/R mapper / RDBMS profilers. .NET profiling .NET profilers (e.g. dotTrace by JetBrains or Ants by Red Gate software) show exactly which pieces of code are called, how many times they're called, and the time it took to run that piece of code, at the method level and sometimes even at the line level. The .NET profilers are essential tools for understanding whether the time taken to complete a given task / area in your application is consumed by .NET code, where exactly in your code, the path to that code, how many times that code was called by other code and thus reveals where hotspots are located: the areas where a solution can be found. Importantly, they also reveal which areas can be left alone: remember our penny wise pound foolish saying: if a profiler reveals that a group of methods are fast, or don't contribute much to the total time taken for a given task, ignore them. Even if the code in them is perhaps complex and looks like a candidate for optimization: you can work all day on that, it won't matter.  As we're focusing on a single area of the application, it's best to start profiling right before you actually activate the task/area. Most .NET profilers support this by starting the application without starting the profiling procedure just yet. You navigate to the particular part which is slow, start profiling in the profiler, in your application you perform the actions which are considered slow, and afterwards you get a snapshot in the profiler. The snapshot contains the data collected by the profiler during the slow action, so most data is produced by code in the area to investigate. This is important, because it allows you to stay focused on a single area. O/R mapper and RDBMS profiling .NET profilers give you a good insight in the .NET side of things, but not in the RDBMS side of the application. As this article is about O/R mapper powered applications, we're also looking at databases, and the software making it possible to consume the database in your application: the O/R mapper. To understand which parts of the O/R mapper and database participate how much to the total time taken for task T, we need different tools. There are two kind of tools focusing on O/R mappers and database performance profiling: O/R mapper profilers and RDBMS profilers. For O/R mapper profilers, you can look at LLBLGen Prof by hibernating rhinos or the Linq to Sql/LLBLGen Pro profiler by Huagati. Hibernating rhinos also have profilers for other O/R mappers like NHibernate (NHProf) and Entity Framework (EFProf) and work the same as LLBLGen Prof. For RDBMS profilers, you have to look whether the RDBMS vendor has a profiler. For example for SQL Server, the profiler is shipped with SQL Server, for Oracle it's build into the RDBMS, however there are also 3rd party tools. Which tool you're using isn't really important, what's important is that you get insight in which queries are executed during the task / area we're currently focused on and how long they took. Here, the O/R mapper profilers have an advantage as they collect the time it took to execute the query from the application's perspective so they also collect the time it took to transport data across the network. This is important because a query which returns a massive resultset or a resultset with large blob/clob/ntext/image fields takes more time to get transported across the network than a small resultset and a database profiler doesn't take this into account most of the time. Another tool to use in this case, which is more low level and not all O/R mappers support it (though LLBLGen Pro and NHibernate as well do) is tracing: most O/R mappers offer some form of tracing or logging system which you can use to collect the SQL generated and executed and often also other activity behind the scenes. While tracing can produce a tremendous amount of data in some cases, it also gives insight in what's going on. Interpret After we've completed the analysis step it's time to look at the data we've collected. We've done code reviews to see whether we've done anything stupid and which parts actually take place and if the proper algorithms have been implemented. We've done .NET profiling to see which parts are choke points and how much time they contribute to the total time taken to complete the task we're investigating. We've performed O/R mapper profiling and RDBMS profiling to see which queries were executed during the task, how many queries were generated and executed and how long they took to complete, including network transportation. All this data reveals two things: which parts are big contributors to the total time taken and which parts are irrelevant. Both aspects are very important. The parts which are irrelevant (i.e. don't contribute significantly to the total time taken) can be ignored from now on, we won't look at them. The parts which contribute a lot to the total time taken are important to look at. We now have to first look at the .NET profiler results, to see whether the time taken is consumed in our own code, in .NET framework code, in the O/R mapper itself or somewhere else. For example if most of the time is consumed by DbCommand.ExecuteReader, the time it took to complete the task is depending on the time the data is fetched from the database. If there was just 1 query executed, according to tracing or O/R mapper profilers / RDBMS profilers, check whether that query is optimal, uses indexes or has to deal with a lot of data. Interpret means that you follow the path from begin to end through the data collected and determine where, along the path, the most time is contributed. It also means that you have to check whether this was expected or is totally unexpected. My previous example of the 10 row resultset of a query which groups millions of rows will likely reveal that a long time is spend inside the database and almost no time is spend in the .NET code, meaning the RDBMS part contributes the most to the total time taken, the rest is compared to that time, irrelevant. Considering the vastness of the source data set, it's expected this will take some time. However, does it need tweaking? Perhaps all possible tweaks are already in place. In the interpret step you then have to decide that further action in this area is necessary or not, based on what the analysis results show: if the analysis results were unexpected and in the area where the most time is contributed to the total time taken is room for improvement, action should be taken. If not, you can only accept the situation and move on. In all cases, document your decision together with the analysis you've done. If you decide that the perceived performance problem is actually expected due to the nature of the task performed, it's essential that in the future when someone else looks at the application and starts asking questions you can answer them properly and new analysis is only necessary if situations changed. Fix After interpreting the analysis results you've concluded that some areas need adjustment. This is the fix step: you're actively correcting the performance problem with proper action targeted at the real cause. In many cases related to O/R mapper powered applications it means you'll use different features of the O/R mapper to achieve the same goal, or apply optimizations at the RDBMS level. It could also mean you apply caching inside your application (compromise memory consumption over performance) to avoid unnecessary re-querying data and re-consuming the results. After applying a change, it's key you re-do the analysis and interpretation steps: compare the results and expectations with what you had before, to see whether your actions had any effect or whether it moved the problem to a different part of the application. Don't fall into the trap to do partly analysis: do the full analysis again: .NET profiling and O/R mapper / RDBMS profiling. It might very well be that the changes you've made make one part faster but another part significantly slower, in such a way that the overall problem hasn't changed at all. Performance tuning is dealing with compromises and making choices: to use one feature over the other, to accept a higher memory footprint, to go away from the strict-OO path and execute queries directly onto the RDBMS, these are choices and compromises which will cross your path if you want to fix performance problems with respect to O/R mappers or data-access and databases in general. In most cases it's not a big issue: alternatives are often good choices too and the compromises aren't that hard to deal with. What is important is that you document why you made a choice, a compromise: which analysis data, which interpretation led you to the choice made. This is key for good maintainability in the years to come. Most common performance problems with O/R mappers Below is an incomplete list of common performance problems related to data-access / O/R mappers / RDBMS code. It will help you with fixing the hotspots you found in the interpretation step. SELECT N+1: (Lazy-loading specific). Lazy loading triggered performance bottlenecks. Consider a list of Orders bound to a grid. You have a Field mapped onto a related field in Order, Customer.CompanyName. Showing this column in the grid will make the grid fetch (indirectly) for each row the Customer row. This means you'll get for the single list not 1 query (for the orders) but 1+(the number of orders shown) queries. To solve this: use eager loading using a prefetch path to fetch the customers with the orders. SELECT N+1 is easy to spot with an O/R mapper profiler or RDBMS profiler: if you see a lot of identical queries executed at once, you have this problem. Prefetch paths using many path nodes or sorting, or limiting. Eager loading problem. Prefetch paths can help with performance, but as 1 query is fetched per node, it can be the number of data fetched in a child node is bigger than you think. Also consider that data in every node is merged on the client within the parent. This is fast, but it also can take some time if you fetch massive amounts of entities. If you keep fetches small, you can use tuning parameters like the ParameterizedPrefetchPathThreshold setting to get more optimal queries. Deep inheritance hierarchies of type Target Per Entity/Type. If you use inheritance of type Target per Entity / Type (each type in the inheritance hierarchy is mapped onto its own table/view), fetches will join subtype- and supertype tables in many cases, which can lead to a lot of performance problems if the hierarchy has many types. With this problem, keep inheritance to a minimum if possible, or switch to a hierarchy of type Target Per Hierarchy, which means all entities in the inheritance hierarchy are mapped onto the same table/view. Of course this has its own set of drawbacks, but it's a compromise you might want to take. Fetching massive amounts of data by fetching large lists of entities. LLBLGen Pro supports paging (and limiting the # of rows returned), which is often key to process through large sets of data. Use paging on the RDBMS if possible (so a query is executed which returns only the rows in the page requested). When using paging in a web application, be sure that you switch server-side paging on on the datasourcecontrol used. In this case, paging on the grid alone is not enough: this can lead to fetching a lot of data which is then loaded into the grid and paged there. Keep note that analyzing queries for paging could lead to the false assumption that paging doesn't occur, e.g. when the query contains a field of type ntext/image/clob/blob and DISTINCT can't be applied while it should have (e.g. due to a join): the datareader will do DISTINCT filtering on the client. this is a little slower but it does perform paging functionality on the data-reader so it won't fetch all rows even if the query suggests it does. Fetch massive amounts of data because blob/clob/ntext/image fields aren't excluded. LLBLGen Pro supports field exclusion for queries. You can exclude fields (also in prefetch paths) per query to avoid fetching all fields of an entity, e.g. when you don't need them for the logic consuming the resultset. Excluding fields can greatly reduce the amount of time spend on data-transport across the network. Use this optimization if you see that there's a big difference between query execution time on the RDBMS and the time reported by the .NET profiler for the ExecuteReader method call. Doing client-side aggregates/scalar calculations by consuming a lot of data. If possible, try to formulate a scalar query or group by query using the projection system or GetScalar functionality of LLBLGen Pro to do data consumption on the RDBMS server. It's far more efficient to process data on the RDBMS server than to first load it all in memory, then traverse the data in-memory to calculate a value. Using .ToList() constructs inside linq queries. It might be you use .ToList() somewhere in a Linq query which makes the query be run partially in-memory. Example: var q = from c in metaData.Customers.ToList() where c.Country=="Norway" select c; This will actually fetch all customers in-memory and do an in-memory filtering, as the linq query is defined on an IEnumerable<T>, and not on the IQueryable<T>. Linq is nice, but it can often be a bit unclear where some parts of a Linq query might run. Fetching all entities to delete into memory first. To delete a set of entities it's rather inefficient to first fetch them all into memory and then delete them one by one. It's more efficient to execute a DELETE FROM ... WHERE query on the database directly to delete the entities in one go. LLBLGen Pro supports this feature, and so do some other O/R mappers. It's not always possible to do this operation in the context of an O/R mapper however: if an O/R mapper relies on a cache, these kind of operations are likely not supported because they make it impossible to track whether an entity is actually removed from the DB and thus can be removed from the cache. Fetching all entities to update with an expression into memory first. Similar to the previous point: it is more efficient to update a set of entities directly with a single UPDATE query using an expression instead of fetching the entities into memory first and then updating the entities in a loop, and afterwards saving them. It might however be a compromise you don't want to take as it is working around the idea of having an object graph in memory which is manipulated and instead makes the code fully aware there's a RDBMS somewhere. Conclusion Performance tuning is almost always about compromises and making choices. It's also about knowing where to look and how the systems in play behave and should behave. The four steps I provided should help you stay focused on the real problem and lead you towards the solution. Knowing how to optimally use the systems participating in your own code (.NET framework, O/R mapper, RDBMS, network/services) is key for success as well as knowing what's going on inside the application you built. I hope you'll find this guide useful in tracking down performance problems and dealing with them in a useful way.  

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  • SQL SERVER – SQL in Sixty Seconds – Last Three Episodes – Need Your Opinion

    - by Pinal Dave
    I have been blogging for almost 7 years and building video content for around 2 years. After spending so much time on blogging and creating video, I have got the quite a good idea what people would like to read and what people like to watch. However, there is one thing, which I am constantly struggling after almost a year and I would like to get your opinion about it. Though, this may look very simple to you but it is very crucial to me and I would like to know your opinion about it. I have been building video almost every week for my SQL in Sixty Seconds series and it has been quite popular. So far on my YouTube Channel there are over 2600 subscribers and over 250K views. Here is my problem – there are about 50+ videos on SQL in Sixty Seconds Series but the not every video is popular. There are a few videos which are extremely popular and there are videos which are absolutely struggling to get even single view. I have yet not figured out what people would love to watch on this channel. I noticed lots of people watching various videos but hardly anyone leaving comments or suggestions. At the end of the blog posts associated with the SQL in Sixty Seconds, I always ask which video people would love to watch, but I get a very low response over there too. What I wonder is that why such a low engagement of viewers/readers on the video blog posts where as the channel is success and lots of people are watching the video? What do you think I should change in my video to increase the engagement? Here are my last three videos from SQL in Sixty Seconds channel and I would like to know your feedback. Remove Cached Login from SSMS Connect Dialog – SQL in Sixty Seconds #049 RESEED Identity Column in Database Table – SQL in Sixty Seconds #051 Puzzle SET ANSI_NULLS and Resultset – SQL in Sixty Seconds #052  The feedback which I will like the most will for sure get a special surprise gift for me. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video

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  • Do most companies not know how to write software?

    - by SnOrfus
    If you're an active reader here, try to think about how many times you've heard (and even agreed) when someone here has told someone else to start looking for a new job. Personally, I've seen it a lot more than I expected: it's almost starting to sound cliche. I get that there are bound to be a number of companies that are bad at developing software or managing a software project, but it almost seems like it's getting worse and more frequent, maybe we're just hearing from them and not all of the places that have decent work atmospheres/conditions. So I ask: In your experience, and through your developer friends do you find that it is common that companies have bad development environments and if so: Why do you think it's common? What do you think could be done to fix it as a developer, as a manager, as an industry? Do you think it's improving?

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  • Downloading large files hangs system

    - by Igor
    When Im trying to download large files, i.e. 1gb or more under FireFox, first of all it starts with very big download speed and in few seconds in almost get up to max (~11 MBps). It is downloading very fast, but when downloaded size becomes near 700-800mb and more, my system almost completely hangs, so I can do nothing - I just have to wait until it finishes downloading. Also when it hangs, I can't see the download progress - it looks like it completely hangs. Sometimes, however, if the file size is near 1gb, the system comes back from hang, finishing download, but sometimes I just cant wait before system comes back and have to kill FF from top (it takes me 2 minutes to do this, because of very slow system performance). I use Firefox as primary browser. If I use wget with direct link to file - everything is fine. Speed at max, no performance decrease. So what can I do?

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  • Why are most websites optimized for viewing in portrait mode?

    - by NVM
    I simply cannot figure this out. Almost all monitors have an aspect ratio where width is much bigger than the height and yet almost all websites are designed exactly for the other way round? I am not really a web developer and am just experimenting stuff at the moment but this madness baffles me!!! Edit: The point is not that I would like to limit the height of a website. The point is that I'd wat it to somehow fill all available space when I have my 1920x1080 in landscape mode. Edit 2: See this to understand what I am saying

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  • How to shorten brain context switch delay when need to use new technology\framework?

    - by gasan
    The problem is when I have to deal with a new framework\library\language it completely slows my work process, at first it's kind of shock, you're sitting on your place about a day doing nothing surfing the net, because you simply can't do anything even read docs, then, on the second day I realize that I definitely should do something and starting read about it, then I realize that I don't understand it, then I'm reading until I got feeling that I should show some results immediately and then I'm writing the code quite fast and the job doesn't seem to be difficult. Then job is done and I won't probably return to that technology\framework for a month or a year or never at all. And I will almost certainly forget almost everything about it after a month. To illustrate by checkpoints I experience: shock, long studying times, work with the new tech briefly, never use it afterwards, then I completely forget it. So what would be the solution here?

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  • Static GitHub powered blog engine

    - by Daniel Cazzulino
    Blog engines were the new &quot;cool thing to write&quot; after the fever of writing a new DI framework was over. It was kinda like the new &quot;hello world++&quot; example. Almost every single engine uses a database of some sort to keep posts and comments. Almost every one is not leveraging the web as a consequence ;) I was intrigued by the possibilities that a flexible and general-purpose hosting solution like Github could offer for a static blog engine: basically keeping plain markdown/HTML/razor/WLW/whatever files that through a publish/build time process generate static files that pass for a &quot;blog engine&quot;. GitHub even supports custom domain names, so why not? Such an &quot;engine&quot; would have a number of benefits: Plain CSS styling Arbitrary JavaScript Leverage the web infrastructure (caching, CDNs, etc.) ...Read full article

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  • Nokia Bluetooth headset Bh 503 not recognized

    - by euDennis
    I bought an Nokia Bluetooth Phone Bh 503. It works just fine with my Android phone, but with Ubuntu it even get recognized. I already paired the Ubuntu with my Android, but with the bluetooth phone it even find it. What can be the problem? Already search in Google for answers, but almost always the problem is with bluetooth that doesn't work, but in my case it works, but not with the headset. Already install almost all packages about bluetooth, like blueman, bluez, gnome-bluetooth, bluetooth, etc.

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  • best way to "introduce" OOP/OOD to team of experienced C++ engineers

    - by DXM
    I am looking for an efficient way, that also doesn't come off as an insult, to introduce OOP concepts to existing team members? My teammates are not new to OO languages. We've been doing C++/C# for a long time so technology itself is familiar. However, I look around and without major infusion of effort (mostly in the form of code reviews), it seems what we are producing is C code that happens to be inside classes. There's almost no use of single responsibility principle, abstractions or attempts to minimize coupling, just to name a few. I've seen classes that don't have a constructor but get memset to 0 every time they are instantiated. But every time I bring up OOP, everyone always nods and makes it seem like they know exactly what I'm talking about. Knowing the concepts is good, but we (some more than others) seem to have very hard time applying them when it comes to delivering actual work. Code reviews have been very helpful but the problem with code reviews is that they only occur after the fact so to some it seems we end up rewriting (it's mostly refactoring, but still takes lots of time) code that was just written. Also code reviews only give feedback to an individual engineer, not the entire team. I am toying with the idea of doing a presentation (or a series) and try to bring up OOP again along with some examples of existing code that could've been written better and could be refactored. I could use some really old projects that no one owns anymore so at least that part shouldn't be a sensitive issue. However, will this work? As I said most people have done C++ for a long time so my guess is that a) they'll sit there thinking why I'm telling them stuff they already know or b) they might actually take it as an insult because I'm telling them they don't know how to do the job they've been doing for years if not decades. Is there another approach which would reach broader audience than a code review would, but at the same time wouldn't feel like a punishment lecture? I'm not a fresh kid out of college who has utopian ideals of perfectly designed code and I don't expect that from anyone. The reason I'm writing this is because I just did a review of a person who actually had decent high-level design on paper. However if you picture classes: A - B - C - D, in the code B, C and D all implement almost the same public interface and B/C have one liner functions so that top-most class A is doing absolutely all the work (down to memory management, string parsing, setup negotiations...) primarily in 4 mongo methods and, for all intents and purposes, calls almost directly into D. Update: I'm a tech lead(6 months in this role) and do have full support of the group manager. We are working on a very mature product and maintenance costs are definitely letting themselves be known.

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  • Google ranking - Modal views - google analytics events [duplicate]

    - by minchiya
    This question already has an answer here: How to diagnose a search engine ranking drop? 5 answers I modified a site recently : - I added many google analytics events, to better understand user behaviour. - I added also two buttons on almost all the pages of the site. Those buttons show modal-views (I am using bootstrap) with questions about user opinion. This modals views are on almost all pages of the site. After this modification the ranking of the site decreased on google search from the second place to the seconde page :( Is it the events-collected or the model-views added ? If the model-views are the reason, then how to better do similar surveys ? Did you have please similar experience, or explanation to this ? Perhaps it is the effect of panda4 update. In this cas, what can I look for to improve the site. How to debug the problem/reasons ?

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  • Why are most websites optimized for viewing in portrait mode?

    - by NVM
    I simply cannot figure this out. Almost all monitors have an aspect ratio where width is much bigger than the height and yet almost all websites are designed exactly for the other way round? I am not really a web developer and am just experimenting stuff at the moment but this madness baffles me!!! Edit: The point is not that I would like to limit the height of a website. The point is that I'd wat it to somehow fill all available space when I have my 1920x1080 in landscape mode. Edit 2: See this to understand what I am saying

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  • Why is JavaScript not used for classical application development (compiled software)?

    - by Jose Faeti
    During my years of web development with JavaScript, I come to the conclusion that it's an incredible powerful language, and you can do amazing things with it. It offers a rich set of features, like: Dynamic typing First-class functions Nested functions Closures Functions as methods Functions as Object constructors Prototype-based Objects-based (almost everything is an object) Regex Array and Object literals It seems to me that almost everything can be achieved with this kind of language, you can also emulate OO programming, since it provides great freedom and many different coding styles. With more software-oriented custom functionalities (I/O, FileSystem, Input devices, etc.) I think it will be great to develop applications with. Though, as far as I know, it's only used in web development or in existing softwares as a scripting language only. Only recently, maybe thanks to the V8 Engine, it's been used more for other kind of tasks (see node.js for example). Why until now it's only be relegated only to web development? What is keeping it away from software development?

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  • Is it practical to have perfect validation score on HTML?

    - by Truth
    I was in a heated discussion the other day, about whether or not it's practical to have a perfect validation score on any HTML document. By practical I mean: Does not take a ridiculous amount of time compared to it's almost-perfect counterpart. Can be made to look good on older browsers and to be usable on very old browsers. Justifies the effort it may take to do so (does it come with some kind of reward on SEO/Usability/Accessibility that cannot be achieved in a simpler way with almost-perfect validation) So basically, is perfect validation score practical on any HTML document?

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  • Manual memory allocation and purity

    - by Eonil
    Language like Haskell have concept of purity. In pure function, I can't mutate any state globally. Anyway Haskell fully abstracts memory management, so memory allocation is not a problem here. But if languages can handle memory directly like C++, it's very ambiguous to me. In these languages, memory allocation makes visible mutation. But if I treat making new object as impure action, actually, almost nothing can be pure. So purity concept becomes almost useless. How should I handle purity in languages have memory as visible global object?

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  • When to use C over C++, and C++ over C?

    - by Dark Templar
    I've been introduced to Computer Science for a little over a year now, and from my experience it seems that C and C++ are both considered one of the "ultrafast" languages out there, whereas others such as Python and such scripting languages are usually deemed somewhat slower. But I've also seen many cases where a software project or even a small one would interleave files where a certain number n of those files would be written in C, and a certain number m of those files would be written in C++. (I also noticed that C++ files almost always have corresponding headers, while C files not so much). But my main point of inquiry is to get a general sense of intuition on when it is appropriate to use C over C++, and when it is better to use C++ over C. Other than the facts that (1) C++ is object-oriented whereas C is not, and (2) the syntaxes are very similar, and C++ was intentionally created to resemble C in many ways, I am not sure what their differences are. It seems to me that they are (almost) perfectly interchangeable in many domains. So it would be appreciated if someone could clear up the situation! Thanks

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  • High temperature on my laptop with Radeon Mobility HD4670

    - by Lorthirk
    As almost everyone here, I guess, in these days I downloaded Quantal Quetzal to give it a try. However I noticed that my laptop runs fairly hot with cooling fans almost always on, even sitting in the desktop doing nothing. I downloaded XSensor to read temperature sensors, and I saw that while CPU stays on about 65°C, so quiet normal I guess, the GPU sits at 75°C. In comparison my actual Windows 7 installation, which dual boots witb Quantal, stays at 59°C CPU and 65°C. So I went reading and learned that AMD dropped support for my video card from fglrx package, and that fglrx-legacy won't support 1.13 Xorg, so I'm basically stuck with OSS drivers. So I was guessing if there's anything I can try, and if it's possible that the OSS drivers could be the cause of the high temperature?

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  • Backups, What Are They Good For?

    We've heard the confessional story from Pixar that Toy Story 2 was almost lost due to a bad backup, but sometimes there is no 'almost'. Grant Fritchey casts a sympathetic eye over some catastrophic data losses, and gives advice on how to avoid what he has termed an RGE (résumé generating event). New! SQL Monitor 3.0 Red Gate's multi-server performance monitoring and alerting tool gets results from Day One.Simple to install and easy to use – download a free trial today.

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  • How to avoid being an API programmer only?

    - by anything
    I have almost six years of experience in java. I have developed many projects which used frameworks like Struts, Spring, Hibernate, JQuery , DWR, Ajax etc. I have used these technologies in almost all the projects I have worked on. Projects were very simple mostly with crud based apps. My everyday tasks involves creating few screens, writing queries, testing etc. After all these years I feel like I have turned into an API programmer who just uses these above mentioned frameworks which is not giving me any satisfaction of being a programmer. Is this normal or is it just me who is feeling like this?

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  • Using packages (gems, eggs, etc.) to create decoupled architectures

    - by Juan Carlos Coto
    The main issue Seeing the good support most modern programming platforms have for package management (think gem, npm, pip, etc), does it make sense to design an application or system be composed of internally developed packages, so as to promote and create a loosely coupled architecture? Example An example of this would be to create packages for database access, as well as for authentication and other components of the system. These, of course, use external packages as well. Then, your system imports and uses these packages - instead of including their code within its own code base. Considerations To me, it seems that this would promote code decoupling and help maintainability, almost in a Web-based-vs.-desktop-application kind of way (updates are applied almost automatically, single code base for single functionality, etc.). Does this seem like a rational and sane design concept? Is this actually used as a standard way of structuring applications today? Thanks very much!

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  • Designing a single look up entity

    - by altsyset
    In almost every application you have this look up entity that provides a dynamic references. This are things like type, category, etc. These entities will always have id, name, desc So at first I designed different entities for each look up. Like education_type, education_level, degree_type.... But on a second thought I decided to have on entity for each of these kinds of entities. But when I am done with the design and check the relation this entity will be referenced by almost all entities in the system and I don't believe that is appropriate. So What is your take on this? Can you give me some clear pros and cons?

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  • Already 3,333 tweets...

    Almost everything is about numbers, and this short blog entry includes the number of tweets written so far. ;) Quite frankly, I joined the Twitter bandwagon late... February 2010 or so. And within those 4.5 years I just came across an interesting milestone: 3,333 tweets 3,333 tweets since February 2010 Compared to some of my fellows here from Mauritius that's almost nothing... Anyways, Cheers and for the next 3,333 tweets. This time faster, hopefully.

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