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• CppUnit for unit-testing executable files?

  - by hagubear

  I am not sure if anyone has done it. I am trying to do something that is in general, uncommon i.e. unit-testing executable (Windows) or ELFs (Linux). I know that CppUnit provides a good unit testing facility, but I have never used it for unit-testing (used UnitTest++). I hear rumours that you can unit-test executables too. Does anyone have the experience in this? A relevant post regarding the philosophy of it was here

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• Scenario to illustrate how unit testing leads to better design

  - by Cocowalla

  For an internal training session, I'm trying to come up with a simple scenario that illustrates how unit testing leads to better design, by forcing you to think about things like coupling before you start coding. The idea is that I get the participants to code something first, without considering unit testing, then we do it again, but considering unit testing. Hopefully the code produced second time round should be more decoupled and maintainable. I'm struggling to come up with a scenario that can be coded quickly, yet can still demonstrate how unit testing can lead to better overall design.

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• What is the aim of software testing?

  - by user970696

  Having read many books, there is a basic contradiction: Some say, "the goal of testing is to find bugs" while other say "the goal of the testing is to equalize the quality of the product", meaning that bugs are its by-products. I would also agree that if testing would be aimed primarily on a bug hunt, who would do the actual verification and actually provided the information, that the software is ready? Even e.g. Kaner changed his original definiton of testing goal from bug hunting to quality assesement provision but I still cannot see the clear difference. I percieve both as equally important. I can verify software by its specification to make sure it works and in that case, bugs found are just by products. But also I perform tests just to brake things. Also what definition is more accurate?

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• Code testing practice

  - by Robin Castlin

  So now I have come to the conclusion like many others that having some way of constantly testing your code is good practice since it enables fewer people to be involved (colleges and customers alike) by simply knowing what's wrong before someone else finds out the hard way. I've heard and read some about Unit Testing and understand what it's supposed to do and all. The there are so many different types of bugs. It can be everything from web browser not being able not being able to send correct values, javascript failing, a global function messing up a piece of code somewhere to a change that looked good when testing it out but fails in some special case which was hard to anticipate. My simply finding these errors I learn to rarely repeat them again, but there seems to always be new bugs to be found and learnt from. I would guess maybe the best practice would be to run every page and it's functions a couple of times, witness the result and repeat this in Firefox, Chrome and Internet Explorer (and all smartphones apparently) to make sure it works as intended. However this would take quite some time to do consider I don't work with patches/versions and do little fixes here and there a couple of times per week. What I prefer would be some kind of page I can just load that tests as much things as possible to make sure the site works as intended. Basicly just run a lot of cURL's with POST-values and see if I get expected result. But how would I preferably not increase the IDs of every mysql rows if I delete these testing rows? It feels silly to be on ID 1000 with maybe 50 rows in total. If I could build a new project from scratch I would probably implement some kind of smooth way to return a "TRUE" on testing instead of the actual page. But this solution would for the moment being have to be passed on existing projects. My question What would you recommend to be the best way to test my site to make sure that existing functions does their job upon editing the code? Should I consider to implement a lot of edits first, then test manually the entire code to make sure it still works? Is there any nice way of testing codes without "hurting" the ID columns? Extra thoughs Would it be a good idea to associate all of my files to the different parts of my site which they affect? For instance if I edit home.php I will through documentation test if my homepage's start works as intended since it's the only part of my site it should affect.

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• EPM 11.1.2 - In WebLogic Server, Enable Native IO Performance Pack

  - by Ahmed Awan

  Performance can be improved by enabling native IO in production mode. WebLogic Server benchmarks show major performance improvements when native performance packs are used on machines that host Oracle WebLogic Server instances. Important Note:  Always enable native I/O, if available, and check for errors at startup to make sure it is being initialed properly. Tip: The use of NATIVE performance packs are enabled by default in the configuration shipped with your distribution. You can use the Administration Console to verify that performance packs are enabled by clicking on each managed server and click on Tuning tab.

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• Linux testing - CPU & disk

  - by JavaRocky

  I am a bit rusty lately. What is the standard way to test CPU and disk I/O these days?

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• Load testing nginx inside AWS

  - by andy

  I'm trying to load test nginx running on AWS. I need to try to optimise it to handle 1Gbps of inbound traffic. Currently I've got it to peak at 85Mbit/s by running nginx on an m1.large with 4 other machines hitting it by using ab with -i (for head requests) -k (keepalives) -r (ignore failed requests) -n 500000 -c 20000. I'm struggling to generate more than 85 Mbit/s traffic from 4 machines, yet when I do scp a large file I get nearly 0.25Gbit/s of traffic going over the network. Are there any tools or approaches that I could use to load test nginx that might generate more load? I'm only interested in inbound traffic, so perhaps a DoS tool could help if it chucks away responses? I'm hitting a very small (40 byte) static asset, and have peaked at handling 50K concurrent connections and getting 25k reqs/s when just using a single load generator machine.

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• Testing Workflows &ndash; Test-After

  - by Timothy Klenke

  Originally posted on: http://geekswithblogs.net/TimothyK/archive/2014/05/30/testing-workflows-ndash-test-after.aspxIn this post I’m going to outline a few common methods that can be used to increase the coverage of of your test suite.  This won’t be yet another post on why you should be doing testing; there are plenty of those types of posts already out there.  Assuming you know you should be testing, then comes the problem of how do I actual fit that into my day job.  When the opportunity to automate testing comes do you take it, or do you even recognize it? There are a lot of ways (workflows) to go about creating automated tests, just like there are many workflows to writing a program.  When writing a program you can do it from a top-down approach where you write the main skeleton of the algorithm and call out to dummy stub functions, or a bottom-up approach where the low level functionality is fully implement before it is quickly wired together at the end.  Both approaches are perfectly valid under certain contexts. Each approach you are skilled at applying is another tool in your tool belt.  The more vectors of attack you have on a problem – the better.  So here is a short, incomplete list of some of the workflows that can be applied to increasing the amount of automation in your testing and level of quality in general.  Think of each workflow as an opportunity that is available for you to take. Test workflows basically fall into 2 categories:  test first or test after.  Test first is the best approach.  However, this post isn’t about the one and only best approach.  I want to focus more on the lesser known, less ideal approaches that still provide an opportunity for adding tests.  In this post I’ll enumerate some test-after workflows.  In my next post I’ll cover test-first. Bug Reporting When someone calls you up or forwards you a email with a vague description of a bug its usually standard procedure to create or verify a reproduction plan for the bug via manual testing and log that in a bug tracking system.  This can be problematic.  Often reproduction plans when written down might skip a step that seemed obvious to the tester at the time or they might be missing some crucial environment setting. Instead of data entry into a bug tracking system, try opening up the test project and adding a failing unit test to prove the bug.  The test project guarantees that all aspects of the environment are setup properly and no steps are missing.  The language in the test project is much more precise than the English that goes into a bug tracking system. This workflow can easily be extended for Enhancement Requests as well as Bug Reporting. Exploratory Testing Exploratory testing comes in when you aren’t sure how the system will behave in a new scenario.  The scenario wasn’t planned for in the initial system requirements and there isn’t an existing test for it.  By definition the system behaviour is “undefined”. So write a new unit test to define that behaviour.  Add assertions to the tests to confirm your assumptions.  The new test becomes part of the living system specification that is kept up to date with the test suite. Examples This workflow is especially good when developing APIs.  When you are finally done your production API then comes the job of writing documentation on how to consume the API.  Good documentation will also include code examples.  Don’t let these code examples merely exist in some accompanying manual; implement them in a test suite. Example tests and documentation do not have to be created after the production API is complete.  It is best to write the example code (tests) as you go just before the production code. Smoke Tests Every system has a typical use case.  This represents the basic, core functionality of the system.  If this fails after an upgrade the end users will be hosed and they will be scratching their heads as to how it could be possible that an update got released with this core functionality broken. The tests for this core functionality are referred to as “smoke tests”.  It is a good idea to have them automated and run with each build in order to avoid extreme embarrassment and angry customers. Coverage Analysis Code coverage analysis is a tool that reports how much of the production code base is exercised by the test suite.  In Visual Studio this can be found under the Test main menu item. The tool will report a total number for the code coverage, which can be anywhere between 0 and 100%.  Coverage Analysis shouldn’t be used strictly for numbers reporting.  Companies shouldn’t set minimum coverage targets that mandate that all projects must have at least 80% or 100% test coverage.  These arbitrary requirements just invite gaming of the coverage analysis, which makes the numbers useless. The analysis tool will break down the coverage by the various classes and methods in projects.  Instead of focusing on the total number, drill down into this view and see which classes have high or low coverage.  It you are surprised by a low number on a class this is an opportunity to add tests. When drilling through the classes there will be generally two types of reaction to a surprising low test coverage number.  The first reaction type is a recognition that there is low hanging fruit to be picked.  There may be some classes or methods that aren’t being tested, which could easy be.  The other reaction type is “OMG”.  This were you find a critical piece of code that isn’t under test.  In both cases, go and add the missing tests. Test Refactoring The general theme of this post up to this point has been how to add more and more tests to a test suite.  I’ll step back from that a bit and remind that every line of code is a liability.  Each line of code has to be read and maintained, which costs money.  This is true regardless whether the code is production code or test code. Remember that the primary goal of the test suite is that it be easy to read so that people can easily determine the specifications of the system.  Make sure that adding more and more tests doesn’t interfere with this primary goal. Perform code reviews on the test suite as often as on production code.  Hold the test code up to the same high readability standards as the production code.  If the tests are hard to read then change them.  Look to remove duplication.  Duplicate setup code between two or more test methods that can be moved to a shared function.  Entire test methods can be removed if it is found that the scenario it tests is covered by other tests.  Its OK to delete a test that isn’t pulling its own weight anymore. Remember to only start refactoring when all the test are green.  Don’t refactor the tests and the production code at the same time.  An automated test suite can be thought of as a double entry book keeping system.  The unchanging, passing production code serves as the tests for the test suite while refactoring the tests. As with all refactoring, it is best to fit this into your regular work rather than asking for time later to get it done.  Fit this into the standard red-green-refactor cycle.  The refactor step no only applies to production code but also the tests, but not at the same time.  Perhaps the cycle should be called red-green-refactor production-refactor tests (not quite as catchy).   That about covers most of the test-after workflows I can think of.  In my next post I’ll get into test-first workflows.

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• How to collect the performance data of a server during an unreachable/down period using Nagios?

  - by gsc-frank

  Some time services and host stop responding due to a poor server performance. I mean, if for some reason (could be lot of concurrency services access, a expensive backup execution on the server or whatever that consume tons of server resources) a server performance is very degraded, that could lead that the server isn't capable to establish any "normal network communication" (without trigger whatever standards timeouts defined for such communication). Knowing host's performance data (cpu, memory, ...) in case of available during that period (host is not down and despite of its performance degradation still allow plugins collect performance data) could be very useful for sysadmin to try to determine what cause the problem, or at least, if the host performance was good and don't interfered at all in the host/service down. This problem could be solved using remote active (NRPE) or remote passive (NSCA) if such remote solutions could store (buffered) perf data to be send to central Nagios server when host performance or network outage allow it. I read the doc of both solutions and can't find any reference to such buffer mechanism neither what happened in case that NSCA can't reach Nagios server. Any idea of how solve this lack of info? so useful for forensic analysis. EDIT: My questions isn about which tools I can use to debug perf problems or gather perf data to analysis, but is about how collect (using Nagios) host perf data even during a network outage for its posterior analysis (kind of forensic analysis). The idea is integrate such data to Nagios graphers like pnp4nagios and NagiosGrapther. I know that I could install tools like Cacti in each of my host, and have a kind of performance data collection redundancy, but I really want avoid that and try to solve all perf analysis requirements with one tools: Nagios

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• How fast are my services? Comparing basicHttpBinding and ws2007HttpBinding using the SO-Aware Test Workbench

  - by gsusx

  When working on real world WCF solutions, we become pretty aware of the performance implications of the binding and behavior configuration of WCF services. However, whether it’s a known fact the different binding and behavior configurations have direct reflections on the performance of WCF services, developers often struggle to figure out the real performance behavior of the services. We can attribute this to the lack of tools for correctly testing the performance characteristics of WCF services...(read more)

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• Cloud Based Load Testing Using TF Service &amp; VS 2013

  - by Tarun Arora [Microsoft MVP]

  Originally posted on: http://geekswithblogs.net/TarunArora/archive/2013/06/30/cloud-based-load-testing-using-tf-service-amp-vs-2013.aspx One of the new features announced as part of the Visual Studio 2013 Ultimate Preview is ‘Cloud Based Load Testing’. In this blog post I’ll walk you through, What is Cloud Based Load Testing? How have I been using this feature? – Success story! Where can you find more resources on this feature? What is Cloud Based Load Testing? It goes without saying that performance testing your application not only gives you the confidence that the application will work under heavy levels of stress but also gives you the ability to test how scalable the architecture of your application is. It is important to know how much is too much for your application! Working with various clients in the industry I have realized that the biggest barriers in Load Testing & Performance Testing adoption are, High infrastructure and administration cost that comes with this phase of testing Time taken to procure & set up the test infrastructure Finding use for this infrastructure investment after completion of testing Is cloud the answer? 100% Visual Studio Compatible Scalable and Realistic Start testing in < 2 minutes Intuitive Pay only for what you need Use existing on premise tests on cloud There are a lot of vendors out there offering Cloud Based Load Testing, to name a few, Load Storm Soasta Blaze Meter Blitz And others… The question you may want to ask is, why should you go with Microsoft’s Cloud based Load Test offering. If you are a Microsoft shop or already have investments in Microsoft technologies, you’ll see great benefit in the natural integration this offers with existing Microsoft products such as Visual Studio and Windows Azure. For example, your existing Web tests authored in Visual Studio 2010 or Visual Studio 2012 will run on the cloud without requiring any modifications what so ever. Microsoft’s cloud test rig also supports API based testing, for example, if you are building a WPF application which consumes WCF services, you can write unit tests to invoke the WCF service, these tests can be run on the cloud test rig and loaded with ‘N’ concurrent users for performance testing. If you have your assets already hosted in the Azure and possibly in the same data centre as the Cloud test rig, your Azure app will not incur a usage cost because of the generated traffic since the traffic is coming from the same data centre. The licensing or pricing information on Microsoft’s cloud based Load test service is yet to be announced, but I would expect this to be priced attractively to match the market competition.   The only additional configuration required for running load tests on Microsoft Cloud based Load Tests service is to select the Test run location as Run tests using Visual Studio Team Foundation Service, How have I been using Microsoft’s Cloud based Load Test Service? I have been part of the Microsoft Cloud Based Load Test Service advisory council for the last 7 months. This gave the opportunity to see the product shape up from concept to working solution. I was also the first person outside of Microsoft to try this offering out. This gave me the opportunity to test real world application at various clients using the Microsoft Load Test Service and provide real world feedback to the Microsoft product team. One of the most recent systems I tested using the Load Test Service has been an insurance quote generation engine. This insurance quote generation engine is,   hosted in Windows Azure expected to get quote requests from across the globe expected to handle 5 Million quote requests in a day (not clear how this load will be distributed across the day) There was no way, I could simulate such kind of load from on premise without standing up additional hardware. But Microsoft’s Cloud based Load Test service allowed me to test my key performance testing scenarios, i.e. Simulate expected Load, Endurance Testing, Threshold Testing and Testing for Latency. Simulating expected load: approach to devising a load pattern My approach to devising a load test pattern has been to run the test scenario with 1 user to figure out the response time. Then work out how many users are required to reach the target load. So, for example, to invoke 1 quote from the quote engine software takes 0.5 seconds. Now if you do the math,   1 quote request by 1 user = 0.5 seconds   quotes generated by 1 user in 24 hour = 1 * (((2 * 60) * 60) * 24) = 172,800   quotes generated by 30 users in 24 hours = 172,800 * 30 =  5,184,000 This was a very simple example, if your application requires more concurrent users to test scenario’s such as caching, etc then you can devise your own load pattern, some examples of load test patterns can be found here.  Endurance Testing To test for endurance, I loaded the quote generation engine with an expected fixed user load and ran the test for very long duration such as over 48 hours and observed the affect of the long running test on the Azure infrastructure. Currently Microsoft Load Test service does not support metrics from the machine under test. I used Azure diagnostics to begin with, but later started using Cerebrata Azure Diagnostics Manager to capture the metrics of the machine under test. Threshold Testing To figure out how much user load the application could cope with before falling on its belly, I opted to step load the quote generation engine by incrementing user load with different variations of incremental user load per minute till the application crashed out and forced an IIS reset. Testing for Latency Currently the Microsoft Load Test service does not support generating geographically distributed load, I however, deployed the insurance quote generation engine in different Azure data centres and ran the same set of performance tests to measure for latency. Because I could compare load test results from different runs by exporting the results to excel (this feature is provided out of the box right from Visual Studio 2010) I could see the different in response times. More resources on Microsoft Cloud based Load Test Service A few important links to get you started, Download Visual Studio Ultimate 2013 Preview Getting started guide for load testing using Team Foundation Service Troubleshooting guide for FAQs and known issues Team Foundation Service forum for questions and support Detailed demo and presentation (link to Tech-Ed session recording) Detailed demo and presentation (link to Build session recording) There a few limits on the usage of Microsoft Cloud based Load Test service that you can read about here. If you have any feedback on Microsoft Cloud based Load Test service, feel free to share it with the product team via the Visual Studio User Voice forum. I hope you found this useful. Thank you for taking the time out and reading this blog post. If you enjoyed the post, remember to subscribe to http://feeds.feedburner.com/TarunArora. Stay tuned!

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• Postfix performance

  - by Brian G

  Running postfix on ubuntu, sending alot of mail ( ~ 1 million messages ) per day. loads are extremly high but not much in terms of cpu and memory load. Anyone in a similiar situation and know how to remove the bottleneck? All mail on this server is outbound. I would have to assume the bottleneck is disk. Just an update, here is what iostat looks like: avg-cpu: %user %nice %system %iowait %steal %idle 0.00 0.00 0.12 99.88 0.00 0.00 Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s avgrq-sz avgqu-sz await svctm %util sda 0.00 12.38 0.00 2.48 0.00 118.81 48.00 0.00 0.00 0.00 0.00 sdb 1.49 22.28 72.28 42.57 629.70 1041.58 14.55 135.56 834.31 8.71 100.00 Are these numbers in line with the performance you would expect from a single disk? sdb is dedicated to postfix. I think it is queue shuffling, from incoming-active-deferred More details from questions: Server: Quad core Xeon(R) CPU E5405 @ 2.00GH with 4 GB ram Load average: 464.88, 489.11, 483.91, 4 cores. but the memory utilization and cpu is minimal Postfix instances between 16 - 32

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• Increase application performance on Amazon AWS

  - by Honus Wagner

  I've got a client with an MVC v1 (.NET) application running on a micro instance. On this instance, I've got .NET, IIS 7.5, and MS SQL Server 2008 running to handle the application. The client has reported that it is taking nearly 10 seconds to process each request. Even loading the initial login page takes about that long, then logging in takes that long, etc etc. The currently running instance specs are as follows: 615 MB RAM Intel Xenon CPU E5430 @ 2.66GHz 2.78 GHz 64-Bit Is the memory availability the issue? or is it the processing power? I forsee two options: Change to a larget instance Set up a 2-tier architecture with two micro instances Which of these will give the application better performance? Thanks in advance.

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• Application Performance: The Best of the Web

  - by Michaela Murray

  Wisdom A deep understanding and realization […] resulting in the ability to apply perceptions, judgements and actions. It is also the comprehension of what is true coupled with optimum judgment as to action. - Wikipedia We’re writing a book for ASP.NET developers, and we want you to be a part of it. We know that there’s a huge amount of web developer wisdom that never gets shared, and we want to find those golden nuggets of knowledge and experience, and make sure everyone can learn from them. Right now, we want to find out about your top tips, hard-won lessons, and sage advice for avoiding, finding, and fixing application performance problems. If you work with .NET and SQL, even better – a lot of application performance relies on the interaction with the database, so we want to hear from you! “How Do You Want Me To Be Involved?” Right! Details! We want you, our most excellent readers, to email us with the Best Advice you would give to other developers for getting the best performance out of their applications. It doesn’t matter if your advice is for newbies or veterans, .NET or SQL – so long as it’s about application performance, we want to hear from you. (And if you think that there’s developer wisdom out there that “everyone knows”, a) I’m willing to bet you could find someone who doesn’t know about it, and b) it probably bears repeating anyway!) “I’m Interested. What Can You Do For Me?” Excellent question. For starters, there’s a chance to win a Microsoft Surface (the tablet, not the table-top). Once all the ASP.NET Wisdom has been collected, tallied, and labelled, it will then be weighed and measured by a team of expert judges (whose identities are still a closely-guarded secret).  The top tip in both SQL & .NET categories will each win their author their very own MS Surface. But that’s not all! We can also give you… immortality! More details? Ok. We’ll be collecting all of the tips sent in by our readers (and we can’t wait to learn from you all,) and with the help of our Simple-Talk editors, we will publish and distribute your combined and documented knowledge as a free, community-created, professionally typeset eBook. You will naturally be credited by name / pseudonym / twitter handle / GitHub username / StackOverflow profile / Whatever, as the clearly ingenious author of hot performance tips. The Not-Very-Fine Print Here’s the breakdown: We want to bring together the best application performance knowledge from ASP.NET developers. Closing date for submissions will be 9am GMT, December 4th. Submissions should be made by email – [email protected] Submissions will be judged by a panel of expert judges (who will be revealed soon). The top submission in both the SQL & .NET categories will each win a Microsoft Surface. ALL the tips which make it through the judging process will be polished by Simple-Talk editors, and turned into a professionally typeset eBook, which will be freely available, and promoted alongside the ANTS Performance Profiler tool. Anyone whose entry makes it into the book will be clearly and profusely credited in the method of their choice (or can remain anonymous.) The really REALLY short version Share what you know about ASP.NET application performance for a chance to win a Microsoft Surface, and then get your name credited in a slick eBook with top-notch production values. For more details, see above. We can’t wait to learn from you!

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• How to manage test fixtures for end-to-end testing?

  - by Peter Becker

  Having just set up a test framework for a new web application, I realized I missed one of the big questions: "How do I make tests independent from each other?" Years ago I have set up some complicated Ant scripting to do full cycles of deleting all database tables, creating the schema again, adding test data, starting the application, running one test and then stopping the application. That was a pain to maintain and restricted us to nightly tests due to the time it took to run the full suite. It was still worth it, but I wonder if there is an easier way. Are there alternatives to this approach? The main criterion is that each test should not be affected by any other test in the suite, no matter if it failed or succeeded.

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• How to do integration testing?

  - by StackUnderflow

  There is so much written about unit testing but I have hardly found any books/blogs about integration testing? Could you please suggest me something to read on this topic? What tests to write when doing integration testing? what makes a good integration test? etc etc Thanks

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• tools for testing vim plugins

  - by intuited

  I'm looking for some tools for testing vim scripts. Either vim scripts that do unit/functional testing, or classes for some other library (eg Python's unittest module) that make it convenient to run vim with parameters that cause it to do some tests on its environment, and determine from the output whether or not a given test passed. I'm aware of a couple of vim scripts that do unit testing, but they're sort of vaguely documented and may or may not actually be useful: vim-unit: purports "To provide vim scripts with a simple unit testing framework and tools" first and only version (v0.1) was released in 2004 documentation doesn't mention whether or not it works reliably, other than to state that it is "fare [sic] from finished". unit-test.vim: This one also seems pretty experimental, and may not be particularly reliable. May have been abandoned or back-shelved: last commit was in 2009-11 ( 6 months ago) No tagged revisions have been created (ie no releases) So information from people who are using one of those two existent modules, and/or links to other, more clearly usable, options, are very welcome.

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• Why not speed up testing by using function dependency graph?

  - by Maltrap

  It seems logical to me that if you have a dependency graph of your source code (tree showing call stack of all functions in your code base) you should be able to save a tremendous amount of time doing functional and integration tests after each release. Essentially you will be able to tell the testers exactly what functionality to test as the rest of the features remain unchanged from a source code point of view. If for instance you change a spelling mistake in once piece of the code, there is no reason to run through your whole test script again "just in case" you introduced a critical bug. My question, why are dependency trees not used in software engineering and if you use them, how do you maintain them? What tools are available that generate these trees for C# .NET, C++ and C source code?

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• Server Performance

  - by sb12

  I know very little about performance tuning of servers etc... so i thought i'd put this up here as i start some research on it, just to get some direction. I am in the process of migrating from my old server to a new one - both are 64 bit machines. One is a few years old, the other brand new (PowerEdge R410). The old server spec is: 2 cpus, 3.4GHz Pentiums, 8G of RAM, Fedora 11 currently installed The new server spec is: 16 cpus, 3.2 GHz Xeon, 16G of RAM, CentOS 6.2 installed. Also RAID10 is on the new server - no RAID on the old one. Both servers currently have the same database (MySQL) with the same data migrated. I wrote a Perl script that simply steps through each row of a table in the database (about 18000 rows) and updates a value in that row. Every row in the table is updated. Out of curiosity i ran this perl script on both machines, just to see how the new server would perform vs. the old one, and it produced interesting results: The old server was twice as fast as the new one to complete. Looking at the database, both are configured exactly the same (the new one being a dump of the old one...)... Anyone any ideas why this would be given the hardware gap between both? As i said i'm about to start some digging, but thought i'd put this up here to maybe get some good direction.... Many thanks in advance..

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• Analysing and measuring the performance of a .NET application (survey results)

  - by Laila

  Back in December last year, I asked myself: could it be that .NET developers think that you need three days and a PhD to do performance profiling on their code? What if developers are shunning profilers because they perceive them as too complex to use? If so, then what method do they use to measure and analyse the performance of their .NET applications? Do they even care about performance? So, a few weeks ago, I decided to get a 1-minute survey up and running in the hopes that some good, hard data would clear the matter up once and for all. I posted the survey on Simple Talk and got help from a few people to promote it. The survey consisted of 3 simple questions: Amazingly, 533 developers took the time to respond - which means I had enough data to get representative results! So before I go any further, I would like to thank all of you who contributed, because I now have some pretty good answers to the troubling questions I was asking myself. To thank you properly, I thought I would share some of the results with you. First of all, application performance is indeed important to most of you. In fact, performance is an intrinsic part of the development cycle for a good 40% of you, which is much higher than I had anticipated, I have to admit. (I know, "Have a little faith Laila!") When asked what tool you use to measure and analyse application performance, I found that nearly half of the respondents use logging statements, a third use performance counters, and 70% of respondents use a profiler of some sort (a 3rd party performance profilers, the CLR profiler or the Visual Studio profiler). The importance attributed to logging statements did surprise me a little. I am still not sure why somebody would go to the trouble of manually instrumenting code in order to measure its performance, instead of just using a profiler. I personally find the process of annotating code, calculating times from log files, and relating it all back to your source terrifyingly laborious. Not to mention that you then need to remember to turn it all off later! Even when you have logging in place throughout all your code anyway, you still have a fair amount of potentially error-prone calculation to sift through the results; in addition, you'll only get method-level rather than line-level timings, and you won't get timings from any framework or library methods you don't have source for. To top it all, we all know that bottlenecks are rarely where you would expect them to be, so you could be wasting time looking for a performance problem in the wrong place. On the other hand, profilers do all the work for you: they automatically collect the CPU and wall-clock timings, and present the results from method timing all the way down to individual lines of code. Maybe I'm missing a trick. I would love to know about the types of scenarios where you actively prefer to use logging statements. Finally, while a third of the respondents didn't have a strong opinion about code performance profilers, those who had an opinion thought that they were mainly complex to use and time consuming. Three respondents in particular summarised this perfectly: "sometimes, they are rather complex to use, adding an additional time-sink to the process of trying to resolve the existing problem". "they are simple to use, but the results are hard to understand" "Complex to find the more advanced things, easy to find some low hanging fruit". These results confirmed my suspicions: Profilers are seen to be designed for more advanced users who can use them effectively and make sense of the results. I found yet more interesting information when I started comparing samples of "developers for whom performance is an important part of the dev cycle", with those "to whom performance is only looked at in times of crisis", and "developers to whom performance is not important, as long as the app works". See the three graphs below. Sample of developers to whom performance is an important part of the dev cycle: Sample of developers to whom performance is important only in times of crisis: Sample of developers to whom performance is not important, as long as the app works: As you can see, there is a strong correlation between the usage of a profiler and the importance attributed to performance: indeed, the more important performance is to a development team, the more likely they are to use a profiler. In addition, developers to whom performance is an important part of the dev cycle have a higher tendency to use a much wider range of methods for performance measurement and analysis. And, unsurprisingly, the less important performance is, the less varied the methods of measurement are. So all in all, to come back to my random questions: .NET developers do care about performance. Those who care the most use a wider range of performance measurement methods than those who care less. But overall, logging statements, performance counters and third party performance profilers are the performance measurement methods of choice for most developers. Finally, although most of you find code profilers complex to use, those of you who care the most about performance tend to use profilers more than those of you to whom performance is not so important.

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• BUILD 2013 Session&ndash;Testing Your C# Base Windows Store Apps

  - by Tim Murphy

  Originally posted on: http://geekswithblogs.net/tmurphy/archive/2013/06/27/build-2013-sessionndashtesting-your-c-base-windows-store-apps.aspx Testing an application is not what most people consider fun and the number of situation that need to be tested seems to grow exponentially when building mobile apps.  That is why I found the topic of this session interesting.  When I found out that the speaker, Francis Cheung, was from the Patterns and Practices group I knew I was in the right place.  I have admired that team since I first met Ron Jacobs around 2001.  So what did Francis have to offer? He started off in a rather confusing who’s on first fashion.  It seems that one of his tester was originally supposed to give the talk, but then it was decided that it would be better to have someone who does development present a testing topic.  This didn’t hinder the content of the talk in the least.  He broke the process down in a logical manner that would be straight forward to understand if not implement. Francis hit the main areas we usually think of such as tombstoning, network connectivity and asynchronous code, but he approached them with tools they we may not have thought of until now.  He relied heavily on Fiddler to intercept and change the behavior of network requests. Then there are the areas you might not normal think to check.  This includes localization, accessibility and updating client code to a new version.  These are important aspects of your app that can severely impact how customers feel about your app.  Take the time to view this session and get a new appreciation for testing and where it fits in your development lifecycle. del.icio.us Tags: BUILD 2013,Testing,C#,Windows Store Apps,Fiddler

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• Term for unit testing that separates test logic from test result data

  - by mario

  So I'm not doing any unit testing. But I've had an idea to make it more appropriate for my field of use. Yet it's not clear if something like this exists, and if, how it would possibly be called. Ordinary unit tests combine the test logic and the expected outcome. In essence the testing framework only checks for booleans (did this match, did the expected result result). To generalize, the test code itself references the audited functions, and also explicites the result values like so: unit::assert( test_me() == 17 ) What I'm looking for is a separation of concerns. The test itself should only contain the tested logic. The outcome and result data should be handled by the unit testing or assertion framework. As example: unit::probe( test_me() ) Here the probe actually doubles as collector in the first run, and afterwards as verification method. The expected 17 is not mentioned in the test code, but stored or managed elsewhere. How is this scheme called? Or how would you call it? I hope I can find some actual implementations with the proper terminology. Obviously such a pattern is unfit for TDD. It's strictly for regression testing. Also obviously, it cannot be used for all cases. Only the simpler test subjects can be analyzed that way, for anything else the ordinary unit test setup and assertion steps are required. And yes, this could be manually accomplished by crafting a ResultWhateverObject, but that would still require hardwiring that to the test logic. Also keep in mind that I'm inquiring for use with scripting languages, and not about Java. I'm aware that the xUnit pattern originates there, and why it's hence as elaborate as it is. Btw, I've discovered one test execution framework which allows for shortening simple test notations to: test_me(); // 17 While thus the result data is no longer coded in (it's a comment), that's still not a complete separation and of course would work only for scalar results.

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• C# Performance Pitfall – Interop Scenarios Change the Rules

  - by Reed

  C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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• How to save a perfmon Performance Counter as a textfile (Reliability and Performance Monitor Version

  - by Lieven Cardoen

  Now the file gets saved as blg, but I would like a txt versin to import in Excel.

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• How often is software speed evident in the eyes of customers?

  - by rwong

  In theory, customers should be able to feel the software performance improvements from first-hand experience. In practice, sometimes the improvements are not noticible enough, such that in order to monetize from the improvements, it is necessary to use quotable performance figures in marketing in order to attract customers. We already know the difference between perceived performance (GUI latency, etc) and server-side performance (machines, networks, infrastructure, etc). How often is it that programmers need to go the extra length to "write up" performance analyses for which the audience is not fellow programmers, but managers and customers?

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