Search Results

Search found 105 results on 5 pages for 'harsh maurya'.

Page 5/5 | < Previous Page | 1 2 3 4 5 

  • Hard crash when drawing content for CALayer using quartz

    - by Lukasz
    I am trying to figure out why iOS crash my application in the harsh way (no crash logs, immediate shudown with black screen of death with spinner shown for a while). It happens when I render content for CALayer using Quartz. I suspected the memory issue (happens only when testing on the device), but memory logs, as well as instruments allocation logs looks quite OK. Let me past in the fatal function: - (void)renderTiles{ if (rendering) { //NSLog(@"====== RENDERING TILES SKIP ======="); return; } rendering = YES; CGRect b = tileLayer.bounds; CGSize s = b.size; CGFloat imageScale = [[UIScreen mainScreen] scale]; s.height *= imageScale; s.width *= imageScale; dispatch_async(queue, ^{ NSLog(@""); NSLog(@"====== RENDERING TILES START ======="); NSLog(@"1. Before creating context"); report_memory(); CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB(); NSLog(@"2. After creating color space"); report_memory(); NSLog(@"3. About to create context with size: %@", NSStringFromCGSize(s)); CGContextRef ctx = CGBitmapContextCreate(NULL, s.width, s.height, 8, 0, colorSpace, kCGImageAlphaPremultipliedLast); NSLog(@"4. After creating context"); report_memory(); CGAffineTransform flipTransform = CGAffineTransformMake(1.0, 0.0, 0.0, -1.0, 0.0, s.height); CGContextConcatCTM(ctx, flipTransform); CGRect tileRect = CGRectMake(0, 0, tileImageScaledSize.width, tileImageScaledSize.height); CGContextDrawTiledImage(ctx, tileRect, tileCGImageScaled); NSLog(@"5. Before creating cgimage from context"); report_memory(); CGImageRef cgImage = CGBitmapContextCreateImage(ctx); NSLog(@"6. After creating cgimage from context"); report_memory(); dispatch_sync(dispatch_get_main_queue(), ^{ tileLayer.contents = (id)cgImage; }); NSLog(@"7. After asgning tile layer contents = cgimage"); report_memory(); CGColorSpaceRelease(colorSpace); CGContextRelease(ctx); CGImageRelease(cgImage); NSLog(@"8. After releasing image and context context"); report_memory(); NSLog(@"====== RENDERING TILES END ======="); NSLog(@""); rendering = NO; }); } Here are the logs: ====== RENDERING TILES START ======= 1. Before creating context Memory in use (in bytes): 28340224 / 519442432 (5.5%) 2. After creating color space Memory in use (in bytes): 28340224 / 519442432 (5.5%) 3. About to create context with size: {6324, 5208} 4. After creating context Memory in use (in bytes): 28344320 / 651268096 (4.4%) 5. Before creating cgimage from context Memory in use (in bytes): 153649152 / 651333632 (23.6%) 6. After creating cgimage from context Memory in use (in bytes): 153649152 / 783159296 (19.6%) 7. After asgning tile layer contents = cgimage Memory in use (in bytes): 153653248 / 783253504 (19.6%) 8. After releasing image and context context Memory in use (in bytes): 21688320 / 651288576 (3.3%) ====== RENDERING TILES END ======= Application crashes in random places. Sometimes when reaching en of the function and sometime in random step. Which direction should I look for a solution? Is is possible that GDC is causing the problem? Or maybe the context size or some Core Animation underlying references?

    Read the article

  • Of transactions and Mongo

    - by Nuri Halperin
    Originally posted on: http://geekswithblogs.net/nuri/archive/2014/05/20/of-transactions-and-mongo-again.aspxWhat's the first thing you hear about NoSQL databases? That they lose your data? That there's no transactions? No joins? No hope for "real" applications? Well, you *should* be wondering whether a certain of database is the right one for your job. But if you do so, you should be wondering that about "traditional" databases as well! In the spirit of exploration let's take a look at a common challenge: You are a bank. You have customers with accounts. Customer A wants to pay B. You want to allow that only if A can cover the amount being transferred. Let's looks at the problem without any context of any database engine in mind. What would you do? How would you ensure that the amount transfer is done "properly"? Would you prevent a "transaction" from taking place unless A can cover the amount? There are several options: Prevent any change to A's account while the transfer is taking place. That boils down to locking. Apply the change, and allow A's balance to go below zero. Charge person A some interest on the negative balance. Not friendly, but certainly a choice. Don't do either. Options 1 and 2 are difficult to attain in the NoSQL world. Mongo won't save you headaches here either. Option 3 looks a bit harsh. But here's where this can go: ledger. See, and account doesn't need to be represented by a single row in a table of all accounts with only the current balance on it. More often than not, accounting systems use ledgers. And entries in ledgers - as it turns out – don't actually get updated. Once a ledger entry is written, it is not removed or altered. A transaction is represented by an entry in the ledger stating and amount withdrawn from A's account and an entry in the ledger stating an addition of said amount to B's account. For sake of space-saving, that entry in the ledger can happen using one entry. Think {Timestamp, FromAccountId, ToAccountId, Amount}. The implication of the original question – "how do you enforce non-negative balance rule" then boils down to: Insert entry in ledger Run validation of recent entries Insert reverse entry to roll back transaction if validation failed. What is validation? Sum up the transactions that A's account has (all deposits and debits), and ensure the balance is positive. For sake of efficiency, one can roll up transactions and "close the book" on transactions with a pseudo entry stating balance as of midnight or something. This lets you avoid doing math on the fly on too many transactions. You simply run from the latest "approved balance" marker to date. But that's an optimization, and premature optimizations are the root of (some? most?) evil.. Back to some nagging questions though: "But mongo is only eventually consistent!" Well, yes, kind of. It's not actually true that Mongo has not transactions. It would be more descriptive to say that Mongo's transaction scope is a single document in a single collection. A write to a Mongo document happens completely or not at all. So although it is true that you can't update more than one documents "at the same time" under a "transaction" umbrella as an atomic update, it is NOT true that there' is no isolation. So a competition between two concurrent updates is completely coherent and the writes will be serialized. They will not scribble on the same document at the same time. In our case - in choosing a ledger approach - we're not even trying to "update" a document, we're simply adding a document to a collection. So there goes the "no transaction" issue. Now let's turn our attention to consistency. What you should know about mongo is that at any given moment, only on member of a replica set is writable. This means that the writable instance in a set of replicated instances always has "the truth". There could be a replication lag such that a reader going to one of the replicas still sees "old" state of a collection or document. But in our ledger case, things fall nicely into place: Run your validation against the writable instance. It is guaranteed to have a ledger either with (after) or without (before) the ledger entry got written. No funky states. Again, the ledger writing *adds* a document, so there's no inconsistent document state to be had either way. Next, we might worry about data loss. Here, mongo offers several write-concerns. Write-concern in Mongo is a mode that marshals how uptight you want the db engine to be about actually persisting a document write to disk before it reports to the application that it is "done". The most volatile, is to say you don't care. In that case, mongo would just accept your write command and say back "thanks" with no guarantee of persistence. If the server loses power at the wrong moment, it may have said "ok" but actually no written the data to disk. That's kind of bad. Don't do that with data you care about. It may be good for votes on a pole regarding how cute a furry animal is, but not so good for business. There are several other write-concerns varying from flushing the write to the disk of the writable instance, flushing to disk on several members of the replica set, a majority of the replica set or all of the members of a replica set. The former choice is the quickest, as no network coordination is required besides the main writable instance. The others impose extra network and time cost. Depending on your tolerance for latency and read-lag, you will face a choice of what works for you. It's really important to understand that no data loss occurs once a document is flushed to an instance. The record is on disk at that point. From that point on, backup strategies and disaster recovery are your worry, not loss of power to the writable machine. This scenario is not different from a relational database at that point. Where does this leave us? Oh, yes. Eventual consistency. By now, we ensured that the "source of truth" instance has the correct data, persisted and coherent. But because of lag, the app may have gone to the writable instance, performed the update and then gone to a replica and looked at the ledger there before the transaction replicated. Here are 2 options to deal with this. Similar to write concerns, mongo support read preferences. An app may choose to read only from the writable instance. This is not an awesome choice to make for every ready, because it just burdens the one instance, and doesn't make use of the other read-only servers. But this choice can be made on a query by query basis. So for the app that our person A is using, we can have person A issue the transfer command to B, and then if that same app is going to immediately as "are we there yet?" we'll query that same writable instance. But B and anyone else in the world can just chill and read from the read-only instance. They have no basis to expect that the ledger has just been written to. So as far as they know, the transaction hasn't happened until they see it appear later. We can further relax the demand by creating application UI that reacts to a write command with "thank you, we will post it shortly" instead of "thank you, we just did everything and here's the new balance". This is a very powerful thing. UI design for highly scalable systems can't insist that the all databases be locked just to paint an "all done" on screen. People understand. They were trained by many online businesses already that your placing of an order does not mean that your product is already outside your door waiting (yes, I know, large retailers are working on it... but were' not there yet). The second thing we can do, is add some artificial delay to a transaction's visibility on the ledger. The way that works is simply adding some logic such that the query against the ledger never nets a transaction for customers newer than say 15 minutes and who's validation flag is not set. This buys us time 2 ways: Replication can catch up to all instances by then, and validation rules can run and determine if this transaction should be "negated" with a compensating transaction. In case we do need to "roll back" the transaction, the backend system can place the timestamp of the compensating transaction at the exact same time or 1ms after the original one. Effectively, once A or B visits their ledger, both transactions would be visible and the overall balance "as of now" would reflect no change.  The 2 transactions (attempted/ reverted) would be visible , since we do actually account for the attempt. Hold on a second. There's a hole in the story: what if several transfers from A to some accounts are registered, and 2 independent validators attempt to compute the balance concurrently? Is there a chance that both would conclude non-sufficient-funds even though rolling back transaction 100 would free up enough for transaction 117 (some random later transaction)? Yes. there is that chance. But the integrity of the business rule is not compromised, since the prime rule is don't dispense money you don't have. To minimize or eliminate this scenario, we can also assign a single validation process per origin account. This may seem non-scalable, but it can easily be done as a "sharded" distribution. Say we have 11 validation threads (or processing nodes etc.). We divide the account number space such that each validator is exclusively responsible for a certain range of account numbers. Sounds cunningly similar to Mongo's sharding strategy, doesn't it? Each validator then works in isolation. More capacity needed? Chop the account space into more chunks. So where  are we now with the nagging questions? "No joins": Huh? What are those for? "No transactions": You mean no cross-collection and no cross-document transactions? Granted - but don't always need them either. "No hope for real applications": well... There are more issues and edge cases to slog through, I'm sure. But hopefully this gives you some ideas of how to solve common problems without distributed locking and relational databases. But then again, you can choose relational databases if they suit your problem.

    Read the article

  • Session Evaluations

    - by BuckWoody
    I do a lot of public speaking. I write, teach, present and communicate at many levels. I love to do those things. And I love to get better at them. And one of the ways you get better at something is to get feedback on how you did. That being said, I have to confess that I really despise the “evaluations” I get at most venues. From college to technical events to other locations, at Microsoft and points in between, I find these things to be just shy of damaging, and most certainly useless. And it’s not always your fault. Ouch. That seems harsh. But let me ask you one question – and be as honest as you can with the answer – think about it first: “What is the point of a session evaluation?” I’m not saying there isn’t one. In fact, I think there’s a really important reason for them. In my mind, it’s really this: To make the speaker / next session better. Now, if you look at that, you can see right away that most session evals don’t accomplish this goal – not even a little. No, the way that they are worded and the way you (and I) fill them out, it’s more like the implied goal is this: Tell us how you liked this speaker / session. The current ones are for you, not for the speaker or the next person. It’s a popularity contest. Don’t get me wrong. I want to you have a good time. I want you to learn. I want (desperately, oh, please oh please) for you to like me. But in fact, that’s probably not why you went to the session / took the class / read that post. No, you want to learn, and to learn for a particular reason. Remember, I’m talking about college classes, sessions and other class environments here, not a general public event. Most – OK, all – session evaluations make you answer the second goal, not the first. Let’s see how: First, they don’t ask you why you’re there. They don’t ask you if you’re even qualified to evaluate the session or speaker. They don’t ask you how to make it better or keep it great. They use odd numeric scales that are meaningless. For instance, can someone really tell me the difference between a 100-level session and a 200-level one? Between a 400-level and a 500? Is it “internals” (whatever that means) or detail, or length or code, or what? I once heard a great description: A 100-level session makes me say, “wow - I’m smart.” A 500-level session makes me say “wow – that presenter is smart.” And just what is the difference between a 6 and a 7 answer on this question: How well did the speaker know the material? 1  2  3  4  5  6  7  8  9  10 Oh. My. Gosh. How does that make the next session better, or the speaker? And what criteria did you use to answer? And is a “10” better than a “1” (not always clear, and various cultures answer this differently). When it’s all said and done, a speaker basically finds out one thing from the current session evals: “They liked me. They really really liked me.” Or, “Wow. I think I may need to schedule some counseling for the depression I’m about to go into.” You may not think that’s what the speaker hears, but trust me, they do. Those are the only two reactions to the current feedback sheets they get. Either they keep doing what they are doing, or they get their feelings hurt. They just can’t use the information provided to do better. Sorry, but there it is. Keep in mind I do want your feedback. I want to get better. I want you to get your money and time’s worth, probably as much as any speaker alive. But I want those evaluations to be accurate, specific and actionable. I want to know if you had a good time, sure, but I also want to know if I did the right things, and if not, if I can do something different or better. And so, for your consideration, here is the evaluation form I would LOVE for you to use. Feel free to copy it and mail it to me any time. I’m going to put some questions here, and then I’ll even include why they are there. Notice that the form asks you a subjective question right away, and then makes you explain why. That’s work on your part. Notice also that it separates the room and the coffee and the lights and the LiveMeeting from the presenter. So many presenters are faced with circumstances beyond their control, and yet are rated high or low personally on those things. This form helps tease those apart. It’s not numeric. Numbers are easier for the scoring committees but are useless for you and me. So I don’t have any numbers. We’re actually going to have to read these things, not put them in a machine. Hey, if you put in the work to write stuff down, the least we could do is take the time to read it. It’s not anonymous. If you’ve got something to say, say it, and own up to it. People are not “more honest” when they are anonymous, they are less honest. So put your name on it. In fact – this is radical – I posit that these evaluations should be publicly available. Forever. Just like replies to a blog post. Hey, if I’m an organizer, I would LOVE to be able to have access to specific, actionable information on the attendees and the speakers. So if you want mine to be public, go for it. I’ll take the good and the bad. Enjoy. ------------------------------------------------------------------------------------------------------------------------------------------- Session Evaluation – Date, Time, Location, Topic Thanks for giving us your time today. We know that’s valuable, and we hope you learned something you can use from the session. If you can answer these questions as completely as you can, it will help the next person who attends a session here. Your Name: What you do for a living: (We Need your background to evaluate your evaluation) How long you have been doing that: (Again, we need your background to evaluate your evaluation) Paste Session Description Here: (This is what I said I would talk about) Did you like the session?                     No        Meh        Yes (General subjective question – overall “feeling”. You’ll tell us why in a minute.)  Tell us about the venue. Temperature, lights, coffee, or the online sound, performance, anything other than the speaker and the material. (Helps the logistics to be better or as good for the next person) 1. What did you expect to learn in this session? (How did you interpret that extract – did you have expectations that I should work towards for the next person?) 2. Did you learn what you expected to learn? Why? Be very specific. (This is the most important question there is. It tells us how to make the session better for someone like you.) 3. If you were giving this presentation, would you have done anything differently? What? (Helps us to gauge you, the listener, and might give us a great idea on how to do something better. Thanks!) 4. What will you do with the information you got? (Every presenter wants you to learn, and learn something useful. This will help us do that as well or better)  

    Read the article

  • The Product Owner

    - by Robert May
    In a previous post, I outlined the rules of Scrum.  This post details one of those rules. Picking a most important part of Scrum is difficult.  All of the rules are required, but if there were one rule that is “more” required that every other rule, its having a good Product Owner.  Simply put, the Product Owner can make or break the project. Duties of the Product Owner A Product Owner has many duties and responsibilities.  I’ll talk about each of these duties in detail below. A Product Owner: Discovers and records stories for the backlog. Prioritizes stories in the Product Backlog, Release Backlog and Iteration Backlog. Determines Release dates and Iteration Dates. Develops story details and helps the team understand those details. Helps QA to develop acceptance tests. Interact with the Customer to make sure that the product is meeting the customer’s needs. Discovers and Records Stories for the Backlog When I do Scrum, I always use User Stories as the means for capturing functionality that’s required in the system.  Some people will use Use Cases, but the same rule applies.  The Product Owner has the ultimate responsibility for figuring out what functionality will be in the system.  Many different mechanisms for capturing this input can be used.  User interviews are great, but all sources should be considered, including talking with Customer Support types.  Often, they hear what users are struggling with the most and are a great source for stories that can make the application easier to use. Care should be taken when soliciting user stories from technical types such as programmers and the people that manage them.  They will almost always give stories that are very technical in nature and may not have a direct benefit for the end user.  Stories are about adding value to the company.  If the stories don’t have direct benefit to the end user, the Product Owner should question whether or not the story should be implemented.  In general, technical stories should be included as tasks in User Stories.  Technical stories are often needed, but the ultimate value to the user is in user based functionality, so technical stories should be considered nothing more than overhead in providing that user functionality. Until the iteration prior to development, stories should be nothing more than short, one line placeholders. An exercise called Story Planning can be used to brainstorm and come up with stories.  I’ll save the description of this activity for another blog post. For more information on User Stories, please read the book User Stories Applied by Mike Cohn. Prioritizes Stories in the Product Backlog, Release Backlog and Iteration Backlog Prioritization of stories is one of the most difficult tasks that a Product Owner must do.  A key concept of Scrum done right is the need to have the team working from a single set of prioritized stories.  If the team does not have a single set of prioritized stories, Scrum will likely fail at your organization.  The Product Owner is the ONLY person who has the responsibility to prioritize that list.  The Product Owner must be very diplomatic and sincerely listen to the people around him so that he can get the priorities correct. Just listening will still not yield the proper priorities.  Care must also be taken to ensure that Return on Investment is also considered.  Ultimately, determining which stories give the most value to the company for the least cost is the most important factor in determining priorities.  Product Owners should be willing to look at cold, hard numbers to determine the order for stories.  Even when many people want a feature, if that features is costly to develop, it may not have as high of a return on investment as features that are cheaper, but not as popular. The act of prioritization often causes conflict in an environment.  Customer Service thinks that feature X is the most important, because it will stop people from calling.  Operations thinks that feature Y is the most important, because it will stop servers from crashing.  Developers think that feature Z is most important because it will make writing software much easier for them.  All of these are useful goals, but the team can have only one list of items, and each item must have a priority that is different from all other stories.  The Product Owner will determine which feature gives the best return on investment and the other features will have to wait their turn, which means that someone will not have their top priority feature implemented first. A weak Product Owner will refuse to do prioritization.  I’ve heard from multiple Product Owners the following phrase, “Well, it’s all got to be done, so what does it matter what order we do it in?”  If your product owner is using this phrase, you need a new Product Owner.  Order is VERY important.  In Scrum, every release is potentially shippable.  If the wrong priority items are developed, then the value added in each release isn’t what it should be.  Additionally, the Product Owner with this mindset doesn’t understand Agile.  A product is NEVER finished, until the company has decided that it is no longer a going concern and they are no longer going to sell the product.  Therefore, prioritization isn’t an event, its something that continues every day.  The logical extension of the phrase “It’s all got to be done” is that you will never ship your product, since a product is never “done.”  Once stories have been prioritized, assigning them to the Release Backlog and the Iteration Backlog becomes relatively simple.  The top priority items are copied into the respective backlogs in order and the task is complete.  The team does have the right to shuffle things around a little in the iteration backlog.  For example, they may determine that working on story C with story A is appropriate because they’re related, even though story B is technically a higher priority than story C.  Or they may decide that story B is too big to complete in the time available after Story A has tasks created, so they’ll work on Story C since it’s smaller.  They can’t, however, go deep into the backlog to pick stories to implement.  The team and the Product Owner should work together to determine what’s best for the company. Prioritization is time consuming, but its one of the most important things a Product Owner does. Determines Release Dates and Iteration Dates Product owners are responsible for determining release dates for a product.  A common misconception that Product Owners have is that every “release” needs to correspond with an actual release to customers.  This is not the case.  In general, releases should be no more than 3 months long.  You  may decide to release the product to the customers, and many companies do release the product to customers, but it may also be an internal release. If a release date is too far away, developers will fall into the trap of not feeling a sense of urgency.  The date is far enough away that they don’t need to give the release their full attention.  Additionally, important tasks, such as performance tuning, regression testing, user documentation, and release preparation, will not happen regularly, making them much more difficult and time consuming to do.  The more frequently you do these tasks, the easier they are to accomplish. The Product Owner will be a key participant in determining whether or not a release should be sent out to the customers.  The determination should be made on whether or not the features contained in the release are valuable enough  and complete enough that the customers will see real value in the release.  Often, some features will take more than three months to get them to a state where they qualify for a release or need additional supporting features to be released.  The product owner has the right to make this determination. In addition to release dates, the Product Owner also will help determine iteration dates.  In general, an iteration length should be chosen and the team should follow that iteration length for an extended period of time.  If the iteration length is changed every iteration, you’re not doing Scrum.  Iteration lengths help the team and company get into a rhythm of developing quality software.  Iterations should be somewhere between 2 and 4 weeks in length.  Any shorter, and significant software will likely not be developed.  Any longer, and the team won’t feel urgency and planning will become very difficult. Iterations may not be extended during the iteration.  Companies where Scrum isn’t really followed will often use this as a strategy to complete all stories.  They don’t want to face the harsh reality of what their true performance is, and looking good is more important than seeking visibility and improving the process and team.  Companies like this typically don’t allow failure.  This is unhealthy.  Failure is part of life and unless we learn from it, we can’t improve.  I would much rather see a team push out stories to the next iteration and then have healthy discussions about why they failed rather than extend the iteration and not deal with the core problems. If iteration length varies, retrospectives become more difficult.  For example, evaluating the performance of the team’s estimation efforts becomes much more difficult if the iteration length varies.  Also, the team must have a velocity measurement.  If the iteration length varies, measuring velocity becomes impossible and upper management no longer will have the ability to evaluate the teams performance.  People external to the team will no longer have the ability to determine when key features are likely to be developed.  Variable iterations cause the entire company to fail and likely cause Scrum to fail at an organization. Develops Story Details and Helps the Team Understand Those Details A key concept in Scrum is that the stories are nothing more than a placeholder for a conversation.  Stories should be nothing more than short, one line statements about the functionality.  The team will then converse with the Product Owner about the details about that story.  The product owner needs to have a very good idea about what the details of the story are and needs to be able to help the team understand those details. Too often, we see this requirement as being translated into the need for comprehensive documentation about the story, including old fashioned requirements documentation.  The team should only develop the documentation that is required and should not develop documentation that is only created because their is a process to do so. In general, what we see that works best is the iteration before a team starts development work on a story, the Product Owner, with other appropriate business analysts, will develop the details of that story.  They’ll figure out what business rules are required, potentially make paper prototypes or other light weight mock-ups, and they seek to understand the story and what is implied.  Note that the time allowed for this task is deliberately short.  The Product Owner only has a single iteration to develop all of the stories for the next iteration. If more than one iteration is used, I’ve found that teams will end up with Big Design Up Front and traditional requirements documents.  This is a waste of time, since the team will need to then have discussions with the Product Owner to figure out what the requirements document says.  Instead of this, skip making the pretty pictures and detailing the nuances of the requirements and build only what is minimally needed by the team to do development.  If something comes up during development, you can address it at that time and figure out what you want to do.  The goal is to keep things as light weight as possible so that everyone can move as quickly as possible. Helps QA to Develop Acceptance Tests In Scrum, no story can be counted until it is accepted by QA.  Because of this, acceptance tests are very important to the team.  In general, acceptance tests need to be developed prior to the iteration or at the very beginning of the iteration so that the team can make sure that the tasks that they develop will fulfill the acceptance criteria. The Product Owner will help the team, including QA, understand what will make the story acceptable.  Note that the Product Owner needs to be careful about specifying that the feature will work “Perfectly” at the end of the iteration.  In general, features are developed a little bit at a time, so only the bit that is being developed should be considered as necessary for acceptance. A weak Product Owner will make statements like “Do it right the first time.”  Not only are these statements damaging to the team (like they would try to do it WRONG the first time . . .), they’re also ignoring the iterative nature of Scrum.  Additionally, a weak product owner will seek to add scope in the acceptance testing.  For example, they will refuse to determine acceptance at the beginning of the iteration, and then, after the team has planned and committed to the iteration, they will expand scope by defining acceptance.  This often causes the team to miss the iteration because scope that wasn’t planned on is included.  There are ways that the team can mitigate this problem.  For example, include extra “Product Owner” time to deal with the uncertainty that you know will be introduced by the Product Owner.  This will slow the perceived velocity of the team and is not ideal, since they’ll be doing more work than they get credit for. Interact with the Customer to Make Sure that the Product is Meeting the Customer’s Needs Once development is complete, what the team has worked on should be put in front of real live people to see if it meets the needs of the customer.  One of the great things about Agile is that if something doesn’t work, we can revisit it in a future iteration!  This frees up the team to make the best decision now and know that if that decision proves to be incorrect, the team can revisit it and change that decision. Features are about adding value to the customer, so if the customer doesn’t find them useful, then having the team make tweaks is valuable.  In general, most software will be 80 to 90 percent “right” after the initial round and only minor tweaks are required.  If proper coding standards are followed, these tweaks are usually minor and easy to accomplish.  Product Owners that are doing a good job will encourage real users to see and use the software, since they know that they are trying to add value to the customer. Poor product owners will think that they know the answers already, that their customers are silly and do stupid things and that they don’t need customer input.  If you have a product owner that is afraid to show the team’s work to real customers, you probably need a different product owner. Up Next, “Who Makes a Good Product Owner.” Followed by, “Messing with the Team.” Technorati Tags: Scrum,Product Owner

    Read the article

  • Marshalling to a native library in C#

    - by Daniel Baulig
    I'm having trouble calling functions of a native library from within managed C# code. I am developing for the 3.5 compact framework (Windows Mobile 6.x) just in case this would make any difference. I am working with the waveIn* functions from coredll.dll (these are in winmm.dll in regular Windows I believe). This is what I came up with: // namespace winmm; class winmm [StructLayout(LayoutKind.Sequential)] public struct WAVEFORMAT { public ushort wFormatTag; public ushort nChannels; public uint nSamplesPerSec; public uint nAvgBytesPerSec; public ushort nBlockAlign; public ushort wBitsPerSample; public ushort cbSize; } [StructLayout(LayoutKind.Sequential)] public struct WAVEHDR { public IntPtr lpData; public uint dwBufferLength; public uint dwBytesRecorded; public IntPtr dwUser; public uint dwFlags; public uint dwLoops; public IntPtr lpNext; public IntPtr reserved; } public delegate void AudioRecordingDelegate(IntPtr deviceHandle, uint message, IntPtr instance, ref WAVEHDR wavehdr, IntPtr reserved2); [DllImport("coredll.dll")] public static extern int waveInAddBuffer(IntPtr hWaveIn, ref WAVEHDR lpWaveHdr, uint cWaveHdrSize); [DllImport("coredll.dll")] public static extern int waveInPrepareHeader(IntPtr hWaveIn, ref WAVEHDR lpWaveHdr, uint Size); [DllImport("coredll.dll")] public static extern int waveInStart(IntPtr hWaveIn); // some other class private WinMM.WinMM.AudioRecordingDelegate waveIn; private IntPtr handle; private uint bufferLength; private void setupBuffer() { byte[] buffer = new byte[bufferLength]; GCHandle bufferPin = GCHandle.Alloc(buffer, GCHandleType.Pinned); WinMM.WinMM.WAVEHDR hdr = new WinMM.WinMM.WAVEHDR(); hdr.lpData = bufferPin.AddrOfPinnedObject(); hdr.dwBufferLength = this.bufferLength; hdr.dwFlags = 0; int i = WinMM.WinMM.waveInPrepareHeader(this.handle, ref hdr, Convert.ToUInt32(Marshal.SizeOf(hdr))); if (i != WinMM.WinMM.MMSYSERR_NOERROR) { this.Text = "Error: waveInPrepare"; return; } i = WinMM.WinMM.waveInAddBuffer(this.handle, ref hdr, Convert.ToUInt32(Marshal.SizeOf(hdr))); if (i != WinMM.WinMM.MMSYSERR_NOERROR) { this.Text = "Error: waveInAddrBuffer"; return; } } private void setupWaveIn() { WinMM.WinMM.WAVEFORMAT format = new WinMM.WinMM.WAVEFORMAT(); format.wFormatTag = WinMM.WinMM.WAVE_FORMAT_PCM; format.nChannels = 1; format.nSamplesPerSec = 8000; format.wBitsPerSample = 8; format.nBlockAlign = Convert.ToUInt16(format.nChannels * format.wBitsPerSample); format.nAvgBytesPerSec = format.nSamplesPerSec * format.nBlockAlign; this.bufferLength = format.nAvgBytesPerSec; format.cbSize = 0; int i = WinMM.WinMM.waveInOpen(out this.handle, WinMM.WinMM.WAVE_MAPPER, ref format, Marshal.GetFunctionPointerForDelegate(waveIn), 0, WinMM.WinMM.CALLBACK_FUNCTION); if (i != WinMM.WinMM.MMSYSERR_NOERROR) { this.Text = "Error: waveInOpen"; return; } setupBuffer(); WinMM.WinMM.waveInStart(this.handle); } I read alot about marshalling the last few days, nevertheless I do not get this code working. When my callback function is called (waveIn) when the buffer is full, the hdr structure passed back in wavehdr is obviously corrupted. Here is an examlpe of how the structure looks like at that point: - wavehdr {WinMM.WinMM.WAVEHDR} WinMM.WinMM.WAVEHDR dwBufferLength 0x19904c00 uint dwBytesRecorded 0x0000fa00 uint dwFlags 0x00000003 uint dwLoops 0x1990f6a4 uint + dwUser 0x00000000 System.IntPtr + lpData 0x00000000 System.IntPtr + lpNext 0x00000000 System.IntPtr + reserved 0x7c07c9a0 System.IntPtr This obiously is not what I expected to get passed. I am clearly concerned about the order of the fields in the view. I do not know if Visual Studio .NET cares about actual memory order when displaying the record in the "local"-view, but they are obviously not displayed in the order I speciefied in the struct. Then theres no data pointer and the bufferLength field is far to high. Interestingly the bytesRecorded field is exactly 64000 - bufferLength and bytesRecorded I'd expect both to be 64000 though. I do not know what exactly is going wrong, maybe someone can help me out on this. I'm an absolute noob to managed code programming and marshalling so please don't be too harsh to me for all the stupid things I've propably done. Oh here's the C code definition for WAVEHDR which I found here, I believe I might have done something wrong in the C# struct definition: /* wave data block header */ typedef struct wavehdr_tag { LPSTR lpData; /* pointer to locked data buffer */ DWORD dwBufferLength; /* length of data buffer */ DWORD dwBytesRecorded; /* used for input only */ DWORD_PTR dwUser; /* for client's use */ DWORD dwFlags; /* assorted flags (see defines) */ DWORD dwLoops; /* loop control counter */ struct wavehdr_tag FAR *lpNext; /* reserved for driver */ DWORD_PTR reserved; /* reserved for driver */ } WAVEHDR, *PWAVEHDR, NEAR *NPWAVEHDR, FAR *LPWAVEHDR; If you are used to work with all those low level tools like pointer-arithmetic, casts, etc starting writing managed code is a pain in the ass. It's like trying to learn how to swim with your hands tied on your back. Some things I tried (to no effect): .NET compact framework does not seem to support the Pack = 2^x directive in [StructLayout]. I tried [StructLayout(LayoutKind.Explicit)] and used 4 bytes and 8 bytes alignment. 4 bytes alignmentgave me the same result as the above code and 8 bytes alignment only made things worse - but that's what I expected. Interestingly if I move the code from setupBuffer into the setupWaveIn and do not declare the GCHandle in the context of the class but in a local context of setupWaveIn the struct returned by the callback function does not seem to be corrupted. I am not sure however why this is the case and how I can use this knowledge to fix my code. I'd really appreciate any good links on marshalling, calling unmanaged code from C#, etc. Then I'd be very happy if someone could point out my mistakes. What am I doing wrong? Why do I not get what I'd expect.

    Read the article

< Previous Page | 1 2 3 4 5