Search Results

Search found 30894 results on 1236 pages for 'best practice'.

Page 373/1236 | < Previous Page | 369 370 371 372 373 374 375 376 377 378 379 380  | Next Page >

  • Recommended Practices for Managing httpd.conf for different environments

    - by James Kingsbery
    We have several different environments (developer dekstop, integration, QA, prod) which should have slightly different variants of the same httpd.conf file. As an example, the httpd.conf file configures that httpd should act as a reverse proxy and proxy certain URLs to Jetty, but the hostname of the Jetty instance is different in each environment. Is there a recommended practice for mangaging these kinds of differences? I looked around the apache documentation for the httpd.conf file and I didn't see anything that does what I need.

    Read the article

  • 20GB+ worth of emails in my /home what is a better solution for that?

    - by Skinkie
    My email storage requirements are outgrowing anything reasonable with respect to local mail storage. As we speak 99% of my home partition is filled with personal mail in Thunderbirds mail dirs. Needless to say, this is just painful, badly searchable and as history has proven me that backups work, but Thunderbird is capable of loosing a lot of mail very easily. Currently I have an remote IMAPS server (Dovecot) running for my daily mail, accessible from anywhere, which from my own practice works efficiently up to about 1000 emails. Then some archive directories should be used to move mail around. I have been looking into DBMail, but I wonder if I make my case worse or better which such solution. None of the supported database employ string deduplication or string compression out of the box, so is this going to help me with 20GB+ mail? What about falling back to a plain old IMAP server? A filesystem like ZFS would support stuff like GZIP transparently, which could help. Could someone share their thoughts? The 20GB mostly consists of mailinglists, and normal mail. Not things like attachments. To add some clarifications; As we speak, my mail is not server side indexed at all - only my new mail arrives at a remote IMAP server. It is all local storage from former POP3 accounts, local mirrored Gmail and IMAP accounts. In my perspective it is not Thunderbird that sucks, its fileformat that sucks. Regarding the 1000 mails. On the road I am using Alpine and MobileMail, quite happy with both of them, but some management is required to actually manage the mail. Sieve helps a lot with that, but browing through 10.000 e-mails is not fun, especially not on a mobile client. I am quite happy with Dovecot, never had any issues with it. I just wonder if this is the way to go. Or if there are any other better solutions. What my question is: what is the best practice solution that allows 20GB+ mails and is -on demand remotely accessible, easy to backup and archive worthy. It doesn't need to be available 24x7. The final approach I took was installing a local IMAP server (Dovecot), configured it for being my archive, using the following guide: http://en.gentoo-wiki.com/wiki/Dovecot/InstallThunderbird

    Read the article

  • Port-forwarding HTTPS web server

    - by James Moore
    I have port forwarded our front-facing IP to an internal HTTPS server. The browser does not connect. A wget command determines that the certificate is self-signed for the internal IP. Hence why the browser is refusing to display the page properly. What is the best-practice scenario for this sort of stuff? Thanks

    Read the article

  • Creating Test Sites

    - by Robert
    I have a website running off site. When we hire someone I would like to create a test site (a copy of live site) for the new employee to tinker with. I will need to take fresh copies of the Files and Database (basically a snapshot) and allow them to access these copied files and database so they could edit and upload them to see the changes they made as if it was the live site Basically what is the best practice for creating a copy of a website for testing? Server is running Linux, PHP, mySQL

    Read the article

  • Other roles on Hyper-V Server

    - by Puneet Arora
    Microsoft offers the standalone Hyper-V server for free. I'm wondering if I can install roles other than the Hyper-V role on this? I know installing other roles alongside Hyper-V is a bad practice, but what I'm trying to ask is if the Hyper-V Server edition of Windows Server allows installation of other roles, like DNS server, File Server etc. Infact I'm not interested in running Hyper-V, just looking for a free windows server to install some roles on. Thanks

    Read the article

  • Any hardware/software routers that support Full Cone NAT?

    - by Ian Boyd
    i'm trying to get Teredo to function on my machine. Most routers, it seems, refuse to forward packets from any host other than the one i specifically connected to first. Teredo requires full Cone NAT in order to function. Does any router, hardware or software, allow full cone NAT? Is this an oversight by the designers of Teredo that nobody, in practice, can use it? i've tried m0n0wall pfsense D-Link Linksys SMC

    Read the article

  • Cheap web hosting that supports php/mysql

    - by Cortopasta
    Does anyone know where I can find web hosting that supports php/mysql? I'm just using it to practice updating/changing live web sites, and to run code in an environment other than my XAMP stack on my thumb drive. It doesn't need to be fast or able to use a lot of bandwith, just somewhere I can play with code to sharpen my skill set

    Read the article

  • Oracle Virtualbox on statically compiled kernel

    - by aking1012
    I can't seem to find any documentation on the subject. I'm working on putting together a linux install for a fairly "dirty" environment. Best practice there would be a statically compiled kernel with no module support. I can already do the customizations to strip out unnecessary drivers/etc to get the performance and disable module support. Does anyone have a link or any ideas on how to get the Oracle Virtualbox module (not the OSE one, I need USB passthrough) compiled in?

    Read the article

  • SQL Connection String to access localhost\SQLEXPRESS

    - by user34683
    I've installed SQL Express on my PC hoping to do some practice creating tables and then modifying them. I coded a webpage in Visual Studio to, basically, SELECT * from a table in the SQLEXPRESS, but I can never get the connection string to work. Please help My connection string "Data Source=localhost\SQLEXPRESS;Initial Catalog=test;User Id=xaa9-PC\xaa9;Password=abcd;" Error Message: Query is select * from tblCustomers where username='johndoe' error is Login failed for user 'xaa9-PC\xaa9'.

    Read the article

  • How to use Git over multiple similar systems

    - by Spidfire
    I have a system I need to duplicate over several systems and make minor changes like change less/css variables and configuration files. Is there a best practice for these kind of problems? I currently do: git clone repo cp ../default/config.js config.js ... for several files or should I create different branches of the same repo or should I create an repo for the changes? It is currently doable but it will get annoying if I get more than 5 similar systems.

    Read the article

  • how to change zone of a extented webapplication-SharePoint?

    - by Ryan
    I have extended a webapplication and set its zone to Intranet but now we decided to make that site anonymous I made all the settings in authentication provider and site collection settings but its still showing its zone as Intranet . I read that its best practice to keep Internet as the zone for anonymous access.. How can I change it now and does it affect leaving it as Intranet?

    Read the article

  • How many megabytes per second may I expect from a gigabit USB 2.0 network card under linux?

    - by Nakedible
    I'm interested in the actual real-word throughput attainable with an external 1000BaseT USB 2.0 network card under Linux. I have been able to attain 90 megabytes per second on a PCI-E interface, but the USB 2.0 bus has a theoretical limit of 480Mbit/s, and in practice less than 40 megabytes per second. Is the actual throughput attainable with such a card under linux 40, 30, 20, or even as low as 10 megabytes per second, eg. no better than a normal 100BaseT network card?

    Read the article

  • Virtual Memory and SSD

    - by Zombian
    While studying for the A+ Exam I was reading about SSD's and I thought to myself that if you had a mobo with a low RAM limit you could use a dedicated SSD purely for Virtual RAM. I looked up some info on line and the info I found said that this was a poor practice but didn't explain why. Why shouldn't SSD's be used for Virtual Memory and what are your thoughts on a dedicated Virtual Memory drive? Thank you!

    Read the article

  • When and how often to start connection to database in php?

    - by AndHeiberg
    When and how often is it good practice to start the connection to your database in php? I'm new to databases, and I'm wondering when I should start by database connection. I'm creating a api with an index, controllers and model. Should I start the connection in the index and then pass it to all the other files, start the connection at the top of all files and call it as a global in functions as needed or start and end the connection in every function?

    Read the article

  • Avoiding QoS degradation for video streaming clients

    - by aarege31
    Suppose I have two routers connected via a 1Gbit connection. A client behind router 1 streams to a client behind router 2 while other clients behind router 1 transmit data to other clients behind router 2. Are there any best practice policing, scheduling or queue management algorithms available that help a beginner understand what is necessary to prevent QoS degration in simple cases as above as well as in real world environments?

    Read the article

  • Time sync in data center

    - by ak
    We currently have setting to sync time when spread is more than 5 mins, but it's getting to a point where some applications don't accept it. What is best practice out there to sync time for all windows and unix boxes to sync with time server or domain controller. Windows time service is not made for high accuracy less then 10 secs. What are alternatives ?

    Read the article

  • Response code for Chinese spiders? [closed]

    - by pt2ph8
    My server is being "attacked" by Chinese spiders that don't respect the rules in my robots.txt. They are being very aggressive and using a lot of resources, so I'm going to set up some rules in nginx to block them by user agent. Question: which response code should I return, 403, 444 (empty response in nginx) or something else? I'm wondering how the spiders will react to different status codes. What's the best practice?

    Read the article

  • Git push from post-receive

    - by meka
    I have two servers, let's call them first and second. First one is where the real development is done, and second one should be the replica. What I would like to do is put "git push" in post-receive, but there is one problem. Post-receive is executed as the user doing git push to first server, so I can't chmod 600 ssh key with no pass. What is the best practice for this? Thanx!

    Read the article

  • CLSF & CLK 2013 Trip Report by Jeff Liu

    - by jamesmorris
    This is a contributed post from Jeff Liu, lead XFS developer for the Oracle mainline Linux kernel team. Recently, I attended both the China Linux Storage and Filesystem workshop (CLSF), and the China Linux Kernel conference (CLK), which were held in Shanghai. Here are the highlights for both events. CLSF - 17th October XFS update (led by Jeff Liu) XFS keeps rapid progress with a lot of changes, especially focused on the infrastructure/performance improvements as well as  new feature development.  This can be reflected with a sample statistics among XFS/Ext4+JBD2/Btrfs via: # git diff --stat --minimal -C -M v3.7..v3.12-rc4 -- fs/xfs|fs/ext4+fs/jbd2|fs/btrfs XFS: 141 files changed, 27598 insertions(+), 19113 deletions(-) Ext4+JBD2: 39 files changed, 10487 insertions(+), 5454 deletions(-) Btrfs: 70 files changed, 19875 insertions(+), 8130 deletions(-) What made up those changes in XFS? Self-describing metadata(CRC32c). This is a new feature and it contributed about 70% code changes, it can be enabled via `mkfs.xfs -m crc=1 /dev/xxx` for v5 superblock. Transaction log space reservation improvements. With this change, we can calculate the log space reservation at mount time rather than runtime to reduce the the CPU overhead. User namespace support. So both XFS and USERNS can be enabled on kernel configuration begin from Linux 3.10. Thanks Dwight Engen's efforts for this thing. Split project/group quota inodes. Originally, project quota can not be enabled with group quota at the same time because they were share the same quota file inode, now it works but only for v5 super block. i.e, CRC enabled. CONFIG_XFS_WARN, an new lightweight runtime debugger which can be deployed in production environment. Readahead log object recovery, this change can speed up the log replay progress significantly. Speculative preallocation inode tracking, clearing and throttling. The main purpose is to deal with inodes with post-EOF space due to speculative preallocation, support improved quota management to free up a significant amount of unwritten space when at or near EDQUOT. It support backgroup scanning which occurs on a longish interval(5 mins by default, tunable), and on-demand scanning/trimming via ioctl(2). Bitter arguments ensued from this session, especially for the comparison between Ext4 and Btrfs in different areas, I have to spent a whole morning of the 1st day answering those questions. We basically agreed on XFS is the best choice in Linux nowadays because: Stable, XFS has a good record in stability in the past 10 years. Fengguang Wu who lead the 0-day kernel test project also said that he has observed less error than other filesystems in the past 1+ years, I own it to the XFS upstream code reviewer, they always performing serious code review as well as testing. Good performance for large/small files, XFS does not works very well for small files has already been an old story for years. Best choice (maybe) for distributed PB filesystems. e.g, Ceph recommends delopy OSD daemon on XFS because Ext4 has limited xattr size. Best choice for large storage (>16TB). Ext4 does not support a single file more than around 15.95TB. Scalability, any objection to XFS is best in this point? :) XFS is better to deal with transaction concurrency than Ext4, why? The maximum size of the log in XFS is 2038MB compare to 128MB in Ext4. Misc. Ext4 is widely used and it has been proved fast/stable in various loads and scenarios, XFS just need more customers, and Btrfs is still on the road to be a manhood. Ceph Introduction (Led by Li Wang) This a hot topic.  Li gave us a nice introduction about the design as well as their current works. Actually, Ceph client has been included in Linux kernel since 2.6.34 and supported by Openstack since Folsom but it seems that it has not yet been widely deployment in production environment. Their major work is focus on the inline data support to separate the metadata and data storage, reduce the file access time, i.e, a file access need communication twice, fetch the metadata from MDS and then get data from OSD, and also, the small file access is limited by the network latency. The solution is, for the small files they would like to store the data at metadata so that when accessing a small file, the metadata server can push both metadata and data to the client at the same time. In this way, they can reduce the overhead of calculating the data offset and save the communication to OSD. For this feature, they have only run some small scale testing but really saw noticeable improvements. Test environment: Intel 2 CPU 12 Core, 64GB RAM, Ubuntu 12.04, Ceph 0.56.6 with 200GB SATA disk, 15 OSD, 1 MDS, 1 MON. The sequence read performance for 1K size files improved about 50%. I have asked Li and Zheng Yan (the core developer of Ceph, who also worked on Btrfs) whether Ceph is really stable and can be deployed at production environment for large scale PB level storage, but they can not give a positive answer, looks Ceph even does not spread over Dreamhost (subject to confirmation). From Li, they only deployed Ceph for a small scale storage(32 nodes) although they'd like to try 6000 nodes in the future. Improve Linux swap for Flash storage (led by Shaohua Li) Because of high density, low power and low price, flash storage (SSD) is a good candidate to partially replace DRAM. A quick answer for this is using SSD as swap. But Linux swap is designed for slow hard disk storage, so there are a lot of challenges to efficiently use SSD for swap. SWAPOUT swap_map scan swap_map is the in-memory data structure to track swap disk usage, but it is a slow linear scan. It will become a bottleneck while finding many adjacent pages in the use of SSD. Shaohua Li have changed it to a cluster(128K) list, resulting in O(1) algorithm. However, this apporoach needs restrictive cluster alignment and only enabled for SSD. IO pattern In most cases, the swap io is in interleaved pattern because of mutiple reclaimers or a free cluster is shared by all reclaimers. Even though block layer can merge interleaved IO to some extent, but we cannot count on it completely. Hence the per-cpu cluster is added base on the previous change, it can help reclaimer do sequential IO and the block layer will be easier to merge IO. TLB flush: If we're reclaiming one active page, we should first move the page from active lru list to inactive lru list, and then reclaim the page from inactive lru to swap it out. During the process, we need to clear PTE twice: first is 'A'(ACCESS) bit, second is 'P'(PRESENT) bit. Processors need to send lots of ipi which make the TLB flush really expensive. Some works have been done to improve this, including rework smp_call_functiom_many() or remove the first TLB flush in x86, but there still have some arguments here and only parts of works have been pushed to mainline. SWAPIN: Page fault does iodepth=1 sync io, but it's a little waste if only issue a page size's IO. The obvious solution is doing swap readahead. But the current in-kernel swap readahead is arbitary(always 8 pages), and it always doesn't perform well for both random and sequential access workload. Shaohua introduced a new flag for madvise(MADV_WILLNEED) to do swap prefetch, so the changes happen in userspace API and leave the in-kernel readahead unchanged(but I think some improvement can also be done here). SWAP discard As we know, discard is important for SSD write throughout, but the current swap discard implementation is synchronous. He changed it to async discard which allow discard and write run in the same time. Meanwhile, the unit of discard is also optimized to cluster. Misc: lock contention For many concurrent swapout and swapin , the lock contention such as anon_vma or swap_lock is high, so he changed the swap_lock to a per-swap lock. But there still have some lock contention in very high speed SSD because of swapcache address_space lock. Zproject (led by Bob Liu) Bob gave us a very nice introduction about the current memory compression status. Now there are 3 projects(zswap/zram/zcache) which all aim at smooth swap IO storm and promote performance, but they all have their own pros and cons. ZSWAP It is implemented based on frontswap API and it uses a dynamic allocater named Zbud to allocate free pages. Zbud means pairs of zpages are "buddied" and it can only store at most two compressed pages in one page frame, so the max compress ratio is 50%. Each page frame is lru-linked and can do shink in memory pressure. If the compressed memory pool reach its limitation, shink or reclaim happens. It decompress the page frame into two new allocated pages and then write them to real swap device, but it can fail when allocating the two pages. ZRAM Acts as a compressed ramdisk and used as swap device, and it use zsmalloc as its allocator which has high density but may have fragmentation issues. Besides, page reclaim is hard since it will need more pages to uncompress and free just one page. ZRAM is preferred by embedded system which may not have any real swap device. Now both ZRAM and ZSWAP are in driver/staging tree, and in the mm community there are some disscussions of merging ZRAM into ZSWAP or viceversa, but no agreement yet. ZCACHE Handles file page compression but it is removed out of staging recently. From industry (led by Tang Jie, LSI) An LSI engineer introduced several new produces to us. The first is raid5/6 cards that it use full stripe writes to improve performance. The 2nd one he introduced is SandForce flash controller, who can understand data file types (data entropy) to reduce write amplification (WA) for nearly all writes. It's called DuraWrite and typical WA is 0.5. What's more, if enable its Dynamic Logical Capacity function module, the controller can do data compression which is transparent to upper layer. LSI testing shows that with this virtual capacity enables 1x TB drive can support up to 2x TB capacity, but the application must monitor free flash space to maintain optimal performance and to guard against free flash space exhaustion. He said the most useful application is for datebase. Another thing I think it's worth to mention is that a NV-DRAM memory in NMR/Raptor which is directly exposed to host system. Applications can directly access the NV-DRAM via a memory address - using standard system call mmap(). He said that it is very useful for database logging now. This kind of NVM produces are beginning to appear in recent years, and it is said that Samsung is building a research center in China for related produces. IMHO, NVM will bring an effect to current os layer especially on file system, e.g. its journaling may need to redesign to fully utilize these nonvolatile memory. OCFS2 (led by Canquan Shen) Without a doubt, HuaWei is the biggest contributor to OCFS2 in the past two years. They have posted 46 upstream patches and 39 patches have been merged. Their current project is based on 32/64 nodes cluster, but they also tried 128 nodes at the experimental stage. The major work they are working is to support ATS (atomic test and set), it can be works with DLM at the same time. Looks this idea is inspired by the vmware VMFS locking, i.e, http://blogs.vmware.com/vsphere/2012/05/vmfs-locking-uncovered.html CLK - 18th October 2013 Improving Linux Development with Better Tools (Andi Kleen) This talk focused on how to find/solve bugs along with the Linux complexity growing. Generally, we can do this with the following kind of tools: Static code checkers tools. e.g, sparse, smatch, coccinelle, clang checker, checkpatch, gcc -W/LTO, stanse. This can help check a lot of things, simple mistakes, complex problems, but the challenges are: some are very slow, false positives, may need a concentrated effort to get false positives down. Especially, no static checker I found can follow indirect calls (“OO in C”, common in kernel): struct foo_ops { int (*do_foo)(struct foo *obj); } foo->do_foo(foo); Dynamic runtime checkers, e.g, thread checkers, kmemcheck, lockdep. Ideally all kernel code would come with a test suite, then someone could run all the dynamic checkers. Fuzzers/test suites. e.g, Trinity is a great tool, it finds many bugs, but needs manual model for each syscall. Modern fuzzers around using automatic feedback, but notfor kernel yet: http://taviso.decsystem.org/making_software_dumber.pdf Debuggers/Tracers to understand code, e.g, ftrace, can dump on events/oops/custom triggers, but still too much overhead in many cases to run always during debug. Tools to read/understand source, e.g, grep/cscope work great for many cases, but do not understand indirect pointers (OO in C model used in kernel), give us all “do_foo” instances: struct foo_ops { int (*do_foo)(struct foo *obj); } = { .do_foo = my_foo }; foo>do_foo(foo); That would be great to have a cscope like tool that understands this based on types/initializers XFS: The High Performance Enterprise File System (Jeff Liu) [slides] I gave a talk for introducing the disk layout, unique features, as well as the recent changes.   The slides include some charts to reflect the performances between XFS/Btrfs/Ext4 for small files. About a dozen users raised their hands when I asking who has experienced with XFS. I remembered that when I asked the same question in LinuxCon/Japan, only 3 people raised their hands, but they are Chris Mason, Ric Wheeler, and another attendee. The attendee questions were mainly focused on stability, and comparison with other file systems. Linux Containers (Feng Gao) The speaker introduced us that the purpose for those kind of namespaces, include mount/UTS/IPC/Network/Pid/User, as well as the system API/ABI. For the userspace tools, He mainly focus on the Libvirt LXC rather than us(LXC). Libvirt LXC is another userspace container management tool, implemented as one type of libvirt driver, it can manage containers, create namespace, create private filesystem layout for container, Create devices for container and setup resources controller via cgroup. In this talk, Feng also mentioned another two possible new namespaces in the future, the 1st is the audit, but not sure if it should be assigned to user namespace or not. Another is about syslog, but the question is do we really need it? In-memory Compression (Bob Liu) Same as CLSF, a nice introduction that I have already mentioned above. Misc There were some other talks related to ACPI based memory hotplug, smart wake-affinity in scheduler etc., but my head is not big enough to record all those things. -- Jeff Liu

    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

  • C#/.NET Fundamentals: Choosing the Right Collection Class

    - by James Michael Hare
    The .NET Base Class Library (BCL) has a wide array of collection classes at your disposal which make it easy to manage collections of objects. While it's great to have so many classes available, it can be daunting to choose the right collection to use for any given situation. As hard as it may be, choosing the right collection can be absolutely key to the performance and maintainability of your application! This post will look at breaking down any confusion between each collection and the situations in which they excel. We will be spending most of our time looking at the System.Collections.Generic namespace, which is the recommended set of collections. The Generic Collections: System.Collections.Generic namespace The generic collections were introduced in .NET 2.0 in the System.Collections.Generic namespace. This is the main body of collections you should tend to focus on first, as they will tend to suit 99% of your needs right up front. It is important to note that the generic collections are unsynchronized. This decision was made for performance reasons because depending on how you are using the collections its completely possible that synchronization may not be required or may be needed on a higher level than simple method-level synchronization. Furthermore, concurrent read access (all writes done at beginning and never again) is always safe, but for concurrent mixed access you should either synchronize the collection or use one of the concurrent collections. So let's look at each of the collections in turn and its various pros and cons, at the end we'll summarize with a table to help make it easier to compare and contrast the different collections. The Associative Collection Classes Associative collections store a value in the collection by providing a key that is used to add/remove/lookup the item. Hence, the container associates the value with the key. These collections are most useful when you need to lookup/manipulate a collection using a key value. For example, if you wanted to look up an order in a collection of orders by an order id, you might have an associative collection where they key is the order id and the value is the order. The Dictionary<TKey,TVale> is probably the most used associative container class. The Dictionary<TKey,TValue> is the fastest class for associative lookups/inserts/deletes because it uses a hash table under the covers. Because the keys are hashed, the key type should correctly implement GetHashCode() and Equals() appropriately or you should provide an external IEqualityComparer to the dictionary on construction. The insert/delete/lookup time of items in the dictionary is amortized constant time - O(1) - which means no matter how big the dictionary gets, the time it takes to find something remains relatively constant. This is highly desirable for high-speed lookups. The only downside is that the dictionary, by nature of using a hash table, is unordered, so you cannot easily traverse the items in a Dictionary in order. The SortedDictionary<TKey,TValue> is similar to the Dictionary<TKey,TValue> in usage but very different in implementation. The SortedDictionary<TKey,TValye> uses a binary tree under the covers to maintain the items in order by the key. As a consequence of sorting, the type used for the key must correctly implement IComparable<TKey> so that the keys can be correctly sorted. The sorted dictionary trades a little bit of lookup time for the ability to maintain the items in order, thus insert/delete/lookup times in a sorted dictionary are logarithmic - O(log n). Generally speaking, with logarithmic time, you can double the size of the collection and it only has to perform one extra comparison to find the item. Use the SortedDictionary<TKey,TValue> when you want fast lookups but also want to be able to maintain the collection in order by the key. The SortedList<TKey,TValue> is the other ordered associative container class in the generic containers. Once again SortedList<TKey,TValue>, like SortedDictionary<TKey,TValue>, uses a key to sort key-value pairs. Unlike SortedDictionary, however, items in a SortedList are stored as an ordered array of items. This means that insertions and deletions are linear - O(n) - because deleting or adding an item may involve shifting all items up or down in the list. Lookup time, however is O(log n) because the SortedList can use a binary search to find any item in the list by its key. So why would you ever want to do this? Well, the answer is that if you are going to load the SortedList up-front, the insertions will be slower, but because array indexing is faster than following object links, lookups are marginally faster than a SortedDictionary. Once again I'd use this in situations where you want fast lookups and want to maintain the collection in order by the key, and where insertions and deletions are rare. The Non-Associative Containers The other container classes are non-associative. They don't use keys to manipulate the collection but rely on the object itself being stored or some other means (such as index) to manipulate the collection. The List<T> is a basic contiguous storage container. Some people may call this a vector or dynamic array. Essentially it is an array of items that grow once its current capacity is exceeded. Because the items are stored contiguously as an array, you can access items in the List<T> by index very quickly. However inserting and removing in the beginning or middle of the List<T> are very costly because you must shift all the items up or down as you delete or insert respectively. However, adding and removing at the end of a List<T> is an amortized constant operation - O(1). Typically List<T> is the standard go-to collection when you don't have any other constraints, and typically we favor a List<T> even over arrays unless we are sure the size will remain absolutely fixed. The LinkedList<T> is a basic implementation of a doubly-linked list. This means that you can add or remove items in the middle of a linked list very quickly (because there's no items to move up or down in contiguous memory), but you also lose the ability to index items by position quickly. Most of the time we tend to favor List<T> over LinkedList<T> unless you are doing a lot of adding and removing from the collection, in which case a LinkedList<T> may make more sense. The HashSet<T> is an unordered collection of unique items. This means that the collection cannot have duplicates and no order is maintained. Logically, this is very similar to having a Dictionary<TKey,TValue> where the TKey and TValue both refer to the same object. This collection is very useful for maintaining a collection of items you wish to check membership against. For example, if you receive an order for a given vendor code, you may want to check to make sure the vendor code belongs to the set of vendor codes you handle. In these cases a HashSet<T> is useful for super-quick lookups where order is not important. Once again, like in Dictionary, the type T should have a valid implementation of GetHashCode() and Equals(), or you should provide an appropriate IEqualityComparer<T> to the HashSet<T> on construction. The SortedSet<T> is to HashSet<T> what the SortedDictionary<TKey,TValue> is to Dictionary<TKey,TValue>. That is, the SortedSet<T> is a binary tree where the key and value are the same object. This once again means that adding/removing/lookups are logarithmic - O(log n) - but you gain the ability to iterate over the items in order. For this collection to be effective, type T must implement IComparable<T> or you need to supply an external IComparer<T>. Finally, the Stack<T> and Queue<T> are two very specific collections that allow you to handle a sequential collection of objects in very specific ways. The Stack<T> is a last-in-first-out (LIFO) container where items are added and removed from the top of the stack. Typically this is useful in situations where you want to stack actions and then be able to undo those actions in reverse order as needed. The Queue<T> on the other hand is a first-in-first-out container which adds items at the end of the queue and removes items from the front. This is useful for situations where you need to process items in the order in which they came, such as a print spooler or waiting lines. So that's the basic collections. Let's summarize what we've learned in a quick reference table.  Collection Ordered? Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes Dictionary No Yes Via Key Key: O(1) O(1) Best for high performance lookups. SortedDictionary Yes No Via Key Key: O(log n) O(log n) Compromise of Dictionary speed and ordering, uses binary search tree. SortedList Yes Yes Via Key Key: O(log n) O(n) Very similar to SortedDictionary, except tree is implemented in an array, so has faster lookup on preloaded data, but slower loads. List No Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no ordering. LinkedList No No No Value: O(n) O(1) Best for lists where inserting/deleting in middle is common and no direct access required. HashSet No Yes Via Key Key: O(1) O(1) Unique unordered collection, like a Dictionary except key and value are same object. SortedSet Yes No Via Key Key: O(log n) O(log n) Unique ordered collection, like SortedDictionary except key and value are same object. Stack No Yes Only Top Top: O(1) O(1)* Essentially same as List<T> except only process as LIFO Queue No Yes Only Front Front: O(1) O(1) Essentially same as List<T> except only process as FIFO   The Original Collections: System.Collections namespace The original collection classes are largely considered deprecated by developers and by Microsoft itself. In fact they indicate that for the most part you should always favor the generic or concurrent collections, and only use the original collections when you are dealing with legacy .NET code. Because these collections are out of vogue, let's just briefly mention the original collection and their generic equivalents: ArrayList A dynamic, contiguous collection of objects. Favor the generic collection List<T> instead. Hashtable Associative, unordered collection of key-value pairs of objects. Favor the generic collection Dictionary<TKey,TValue> instead. Queue First-in-first-out (FIFO) collection of objects. Favor the generic collection Queue<T> instead. SortedList Associative, ordered collection of key-value pairs of objects. Favor the generic collection SortedList<T> instead. Stack Last-in-first-out (LIFO) collection of objects. Favor the generic collection Stack<T> instead. In general, the older collections are non-type-safe and in some cases less performant than their generic counterparts. Once again, the only reason you should fall back on these older collections is for backward compatibility with legacy code and libraries only. The Concurrent Collections: System.Collections.Concurrent namespace The concurrent collections are new as of .NET 4.0 and are included in the System.Collections.Concurrent namespace. These collections are optimized for use in situations where multi-threaded read and write access of a collection is desired. The concurrent queue, stack, and dictionary work much as you'd expect. The bag and blocking collection are more unique. Below is the summary of each with a link to a blog post I did on each of them. ConcurrentQueue Thread-safe version of a queue (FIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentStack Thread-safe version of a stack (LIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentBag Thread-safe unordered collection of objects. Optimized for situations where a thread may be bother reader and writer. For more information see: C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection ConcurrentDictionary Thread-safe version of a dictionary. Optimized for multiple readers (allows multiple readers under same lock). For more information see C#/.NET Little Wonders: The ConcurrentDictionary BlockingCollection Wrapper collection that implement producers & consumers paradigm. Readers can block until items are available to read. Writers can block until space is available to write (if bounded). For more information see C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection Summary The .NET BCL has lots of collections built in to help you store and manipulate collections of data. Understanding how these collections work and knowing in which situations each container is best is one of the key skills necessary to build more performant code. Choosing the wrong collection for the job can make your code much slower or even harder to maintain if you choose one that doesn’t perform as well or otherwise doesn’t exactly fit the situation. Remember to avoid the original collections and stick with the generic collections.  If you need concurrent access, you can use the generic collections if the data is read-only, or consider the concurrent collections for mixed-access if you are running on .NET 4.0 or higher.   Tweet Technorati Tags: C#,.NET,Collecitons,Generic,Concurrent,Dictionary,List,Stack,Queue,SortedList,SortedDictionary,HashSet,SortedSet

    Read the article

  • VS 2012 Code Review &ndash; Before Check In OR After Check In?

    - by Tarun Arora
    “Is Code Review Important and Effective?” There is a consensus across the industry that code review is an effective and practical way to collar code inconsistency and possible defects early in the software development life cycle. Among others some of the advantages of code reviews are, Bugs are found faster Forces developers to write readable code (code that can be read without explanation or introduction!) Optimization methods/tricks/productive programs spread faster Programmers as specialists "evolve" faster It's fun “Code review is systematic examination (often known as peer review) of computer source code. It is intended to find and fix mistakes overlooked in the initial development phase, improving both the overall quality of software and the developers' skills. Reviews are done in various forms such as pair programming, informal walkthroughs, and formal inspections.” Wikipedia No where does the definition mention whether its better to review code before the code has been committed to version control or after the commit has been performed. No matter which side you favour, Visual Studio 2012 allows you to request for a code review both before check in and also request for a review after check in. Let’s weigh the pros and cons of the approaches independently. Code Review Before Check In or Code Review After Check In? Approach 1 – Code Review before Check in Developer completes the code and feels the code quality is appropriate for check in to TFS. The developer raises a code review request to have a second pair of eyes validate if the code abides to the recommended best practices, will not result in any defects due to common coding mistakes and whether any optimizations can be made to improve the code quality.                                             Image 1 – code review before check in Pros Everything that gets committed to source control is reviewed. Minimizes the chances of smelly code making its way into the code base. Decreases the cost of fixing bugs, remember, the earlier you find them, the lesser the pain in fixing them. Cons Development Code Freeze – Since the changes aren’t in the source control yet. Further development can only be done off-line. The changes have not been through a CI build, hard to say whether the code abides to all build quality standards. Inconsistent! Cumbersome to track the actual code review process.  Not every change to the code base is worth reviewing, a lot of effort is invested for very little gain. Approach 2 – Code Review after Check in Developer checks in, random code reviews are performed on the checked in code.                                                      Image 2 – Code review after check in Pros The code has already passed the CI build and run through any code analysis plug ins you may have running on the build server. Instruct the developer to ensure ZERO fx cop, style cop and static code analysis before check in. Code is cleaner and smell free even before the code review. No Offline development, developers can continue to develop against the source control. Cons Bad code can easily make its way into the code base. Since the review take place much later in the cycle, the cost of fixing issues can prove to be much higher. Approach 3 – Hybrid Approach The community advocates a more hybrid approach, a blend of tooling and human accountability quotient.                                                               Image 3 – Hybrid Approach 1. Code review high impact check ins. It is not possible to review everything, by setting up code review check in policies you can end up slowing your team. More over, the code that you are reviewing before check in hasn't even been through a green CI build either. 2. Tooling. Let the tooling work for you. By running static analysis, fx cop, style cop and other plug ins on the build agent, you can identify the real issues that in my opinion can't possibly be identified using human reviews. Configure the tooling to report back top 10 issues every day. Mandate the manual code review of individuals who keep making it to this list of shame more often. 3. During Merge. I would prefer eliminating some of the other code issues during merge from Main branch to the release branch. In a scrum project this is still easier because cheery picking the merges is a possibility and the size of code being reviewed is still limited. Let the tooling work for you, if some one breaks the CI build often, put them on a gated check in build course until you see improvement. If some one appears on the top 10 list of shame generated via the build then ensure that all their code is reviewed till you see improvement. At the end of the day, the goal is to ensure that the code being delivered is top quality. By enforcing a code review before any check in, you force the developer to work offline or stay put till the review is complete. What do the experts say? So I asked a few expects what they thought of “Code Review quality gate before Checking in code?" Terje Sandstrom | Microsoft ALM MVP You mean a review quality gate BEFORE checking in code????? That would mean a lot of code staying either local or in shelvesets, and not even been through a CI build, and a green CI build being the main criteria for going further, f.e. to the review state. I would not like code laying around with no checkin’s. Having a requirement that code is checked in small pieces, 4-8 hours work max, and AT LEAST daily checkins, a manual code review comes second down the lane. I would expect review quality gates to happen before merging back to main, or before merging to release.  But that would all be on checked-in code.  Branching is absolutely one way to ease the pain.   Another way we are using is automatic quality builds, running metrics, coverage, static code analysis.  Unfortunately it takes some time, would be great to be on CI’s – but…., so it’s done scheduled every night. Based on this we get, among other stuff,  top 10 lists of suspicious code, which is then subjected to reviews.  If a person seems to be very popular on these top 10 lists, we subject every check in from that person to a review for a period. That normally helps.   None of the clients I have can afford to have every checkin reviewed, so we need to find ways around it. I don’t disagree with the nicety of having all the code reviewed, but I find it hard to find those resources in today’s enterprises. David V. Corbin | Visual Studio ALM Ranger I tend to agree with both sides. I hate having code that is not checked in, but at the same time hate having “bad” code in the repository. I have found that branching is one approach to solving this dilemma. Code is checked into the private/feature branch before the review, but is not merged over to the “official” branch until after the review. I advocate both, depending on circumstance (especially team dynamics)   - The “pre-checkin” is usually for elements that may impact the project as a whole. Think of it as another “gate” along with passing unit tests. - The “post-checkin” may very well not be at the changeset level, but correlates to a review at the “user story” level.   Again, this depends on team dynamics in play…. Robert MacLean | Microsoft ALM MVP I do not think there is no right answer for the industry as a whole. In short the question is why do you do reviews? Your question implies risk mitigation, so in low risk areas you can get away with it after check in while in high risk you need to do it before check in. An example is those new to a team or juniors need it much earlier (maybe that is before checkin, maybe that is soon after) than seniors who have shipped twenty sprints on the team. Abhimanyu Singhal | Visual Studio ALM Ranger Depends on per scenario basis. We recommend post check-in reviews when: 1. We don't want to block other checks and processes on manual code reviews. Manual reviews take time, and some pieces may not require manual reviews at all. 2. We need to trace all changes and track history. 3. We have a code promotion strategy/process in place. For risk mitigation, post checkin code can be promoted to Accepted branches. Or can be rejected. Pre Checkin Reviews are used when 1. There is a high risk factor associated 2. Reviewers are generally (most of times) have immediate availability. 3. Team does not have strict tracking needs. Simply speaking, no single process fits all scenarios. You need to select what works best for your team/project. Thomas Schissler | Visual Studio ALM Ranger This is an interesting discussion, I’m right now discussing details about executing code reviews with my teams. I see and understand the aspects you brought in, but there is another side as well, I’d like to point out. 1.) If you do reviews per check in this is not very practical as a hard rule because this will disturb the flow of the team very often or it will lead to reduce the checkin frequency of the devs which I would not accept. 2.) If you do later reviews, for example if you review PBIs, it is not easy to find out which code you should review. Either you review all changesets associate with the PBI, but then you might review code which has been changed with a later checkin and the dev maybe has already fixed the issue. Or you review the diff of the latest changeset of the PBI with the first but then you might also review changes of other PBIs. Jakob Leander | Sr. Director, Avanade In my experience, manual code review: 1. Does not get done and at the very least does not get redone after changes (regardless of intentions at start of project) 2. When a project actually do it, they often do not do it right away = errors pile up 3. Requires a lot of time discussing/defining the standard and for the team to learn it However code review is very important since e.g. even small memory leaks in a high volume web solution have big consequences In the last years I have advocated following approach for code review - Architects up front do “at least one best practice example” of each type of component and tell the team. Copy from this one. This should include error handling, logging, security etc. - Dev lead on project continuously browse code to validate that the best practices are used. Especially that patterns etc. are not broken. You can do this formally after each sprint/iteration if you want. Once this is validated it is unlikely to “go bad” even during later code changes Agree with customer to rely on static code analysis from Visual Studio as the one and only coding standard. This has HUUGE benefits - You can easily tweak to reach the level you desire together with customer - It is easy to measure for both developers/management - It is 100% consistent across code base - It gets validated all the time so you never end up getting hammered by a customer review in the end - It is easy to tell the developer that you do not want code back unless it has zero errors = minimize communication You need to track this at least during nightly builds and make sure team sees total # issues. Do not allow #issues it to grow uncontrolled. On the project I run I require code analysis to have run on code before checkin (checkin rule). This means -  You have to have clean compile (or CA wont run) so this is extra benefit = very few broken builds - You can change a few of the rules to compile as errors instead of warnings. I often do this for “missing dispose” issues which you REALLY do not want in your app Tip: Place your custom CA rules files as part of solution. That  way it works when you do branching etc. (path to CA file is relative in VS) Some may argue that CA is not as good as manual inspection. But since manual inspection in reality suffers from the 3 issues in start it is IMO a MUCH better (and much cheaper) approach from helicopter perspective Tirthankar Dutta | Director, Avanade I think code review should be run both before and after check ins. There are some code metrics that are meant to be run on the entire codebase … Also, especially on multi-site projects, one should strive to architect in a way that lets men manage the framework while boys write the repetitive code… scales very well with the need to review less by containment and imposing architectural restrictions to emphasise the design. Bruno Capuano | Microsoft ALM MVP For code reviews (means peer reviews) in distributed team I use http://www.vsanywhere.com/default.aspx  David Jobling | Global Sr. Director, Avanade Peer review is the only way to scale and its a great practice for all in the team to learn to perform and accept. In my experience you soon learn who's code to watch more than others and tune the attention. Mikkel Toudal Kristiansen | Manager, Avanade If you have several branches in your code base, you will need to merge often. This requires manual merging, when a file has been changed in both branches. It offers a good opportunity to actually review to changed code. So my advice is: Merging between branches should be done as often as possible, it should be done by a senior developer, and he/she should perform a full code review of the code being merged. As for detecting architectural smells and code smells creeping into the code base, one really good third party tools exist: Ndepend (http://www.ndepend.com/, for static code analysis of the current state of the code base). You could also consider adding StyleCop to the solution. Jesse Houwing | Visual Studio ALM Ranger I gave a presentation on this subject on the TechDays conference in NL last year. See my presentation and slides here (talk in Dutch, but English presentation): http://blog.jessehouwing.nl/2012/03/did-you-miss-my-techdaysnl-talk-on-code.html  I’d like to add a few more points: - Before/After checking is mostly a trust issue. If you have a team that does diligent peer reviews and regularly talk/sit together or peer review, there’s no need to enforce a before-checkin policy. The peer peer-programming and regular feedback during development can take care of most of the review requirements as long as the team isn’t under stress. - Under stress, enforce pre-checkin reviews, it might sound strange, if you’re already under time or budgetary constraints, but it is under such conditions most real issues start to be created or pile up. - Use tools to catch most common errors, Code Analysis/FxCop was already mentioned. HP Fortify, Resharper, Coderush etc can help you there. There are also a lot of 3rd party rules you can add to Code Analysis. I’ve written a few myself (http://fccopcontrib.codeplex.com) and various teams from Microsoft have added their own rules (MSOCAF for SharePoint, WSSF for WCF). For common errors that keep cropping up, see if you can define a rule. It’s much easier. But more importantly make sure you have a good help page explaining *WHY* it's wrong. If you have small feature or developer branches/shelvesets, you might want to review pre-merge. It’s still better to do peer reviews and peer programming, but the most important thing is that bad quality code doesn’t make it into the important branch. So my philosophy: - Use tooling as much as possible. - Make sure the team understands the tooling and the importance of the things it flags. It’s too easy to just click suppress all to ignore the warnings. - Under stress, tighten process, it’s under stress that the problems of late reviews will really surface - Most importantly if you do reviews do them as early as possible, but never later than needed. In other words, pre-checkin/post checking doesn’t really matter, as long as the review is done before the code is released. It’ll just be much more expensive to fix any review outcomes the later you find them. --- I would love to hear what you think!

    Read the article

  • How to Visualize your Audit Data with BI Publisher?

    - by kanichiro.nishida
      Do you know how many reports on your BI Publisher server are accessed yesterday ? Or, how many users accessed to the reports yesterday, or what are the average number of the users accessed to the reports during the week vs. weekend or morning vs. afternoon ? With BI Publisher 11G, now you can audit your user’s reports access and understand the state of the reporting environment at your server, each user, or each report level. At the previous post I’ve talked about what the BI Publisher’s auditing functionality and how to enable it so that BI Publisher can start collecting such data. (How to Audit and Monitor BI Publisher Reports Access?)Now, how can you visualize such auditing data to have a better understanding and gain more insights? With Fusion Middleware Audit Framework you have an option to store the auditing data into a database instead of a log file, which is the default option. Once you enable the database storage option, that means you have your auditing data (or, user report access data) in your database tables, now no brainer, you can start visualize the data, create reports, analyze, and share with BI Publisher. So, first, let’s take a look on how to enable the database storage option for the auditing data. How to Feed the Auditing Data into Database First you need to create a database schema for Fusion Middleware Audit Framework with RCU (Repository Creation Utility). If you have already installed BI Publisher 11G you should be familiar with this RCU. It creates any database schema necessary to run any Fusion Middleware products including BI stuff. And you can use the same RCU that you used for your BI or BI Publisher installation to create this Audit schema. Create Audit Schema with RCU Here are the steps: Go to $RCU_HOME/bin and execute the ‘rcu’ command Choose Create at the starting screen and click Next. Enter your database details and click Next. Choose the option to create a new prefix, for example ‘BIP’, ‘KAN’, etc. Select 'Audit Services' from the list of schemas. Click Next and accept the tablespace creation. Click Finish to start the process. After this, there should be following three Audit related schema created in your database. <prefix>_IAU (e.g. KAN_IAU) <prefix>_IAU_APPEND (e.g. KAN_IAU_APPEND) <prefix>_IAU_VIEWER (e.g. KAN_IAU_VIEWER) Setup Datasource at WebLogic After you create a database schema for your auditing data, now you need to create a JDBC connection on your WebLogic Server so the Audit Framework can access to the database schema that was created with the RCU with the previous step. Connect to the Oracle WebLogic Server administration console: http://hostname:port/console (e.g. http://report.oracle.com:7001/console) Under Services, click the Data Sources link. Click ‘Lock & Edit’ so that you can make changes Click New –> ‘Generic Datasource’ to create a new data source. Enter the following details for the new data source:  Name: Enter a name such as Audit Data Source-0.  JNDI Name: jdbc/AuditDB  Database Type: Oracle  Click Next and select ‘Oracle's Driver (Thin XA) Versions: 9.0.1 or later’ as Database Driver (if you’re using Oracle database), and click Next. The Connection Properties page appears. Enter the following information: Database Name: Enter the name of the database (SID) to which you will connect. Host Name: Enter the hostname of the database.  Port: Enter the database port.  Database User Name: This is the name of the audit schema that you created in RCU. The suffix is always IAU for the audit schema. For example, if you gave the prefix as ‘BIP’, then the schema name would be ‘KAN_IAU’.  Password: This is the password for the audit schema that you created in RCU.   Click Next. Accept the defaults, and click Test Configuration to verify the connection. Click Next Check listed servers where you want to make this JDBC connection available. Click ‘Finish’ ! After that, make sure you click ‘Activate Changes’ at the left hand side top to take the new JDBC connection in effect. Register your Audit Data Storing Database to your Domain Finally, you can register the JNDI/JDBC datasource as your Auditing data storage with Fusion Middleware Control (EM). Here are the steps: 1. Login to Fusion Middleware Control 2. Navigate to Weblogic Domain, right click on ‘bifoundation…..’, select Security, then Audit Store. 3. Click the searchlight icon next to the Datasource JNDI Name field. 4.Select the Audit JNDI/JDBC datasource you created in the previous step in the pop-up window and click OK. 5. Click Apply to continue. 6. Restart the whole WebLogic Servers in the domain. After this, now the BI Publisher should start feeding all the auditing data into the database table called ‘IAU_BASE’. Try login to BI Publisher and open a couple of reports, you should see the activity audited in the ‘IAU_BASE’ table. If not working, you might want to check the log file, which is located at $BI_HOME/user_projects/domains/bifoundation_domain/servers/AdminServer/logs/AdminServer-diagnostic.log to see if there is any error. Once you have the data in the database table, now, it’s time to visualize with BI Publisher reports! Create a First BI Publisher Auditing Report Register Auditing Datasource as JNDI datasource First thing you need to do is to register the audit datasource (JNDI/JDBC connection) you created in the previous step as JNDI data source at BI Publisher. It is a JDBC connection registered as JNDI, that means you don’t need to create a new JDBC connection by typing the connection URL, username/password, etc. You can just register it using the JNDI name. (e.g. jdbc/AuditDB) Login to BI Publisher as Administrator (e.g. weblogic) Go to Administration Page Click ‘JNDI Connection’ under Data Sources and Click ‘New’ Type Data Source Name and JNDI Name. The JNDI Name is the one you created in the WebLogic Console as the auditing datasource. (e.g. jdbc/AuditDB) Click ‘Test Connection’ to make sure the datasource connection works. Provide appropriate roles so that the report developers or viewers can share this data source to view reports. Click ‘Apply’ to save. Create Data Model Select Data Model from the tool bar menu ‘New’ Set ‘Default Data Source’ to the audit JNDI data source you have created in the previous step. Select ‘SQL Query’ for your data set Use Query Builder to build a query or just type a sql query. Either way, the table you want to report against is ‘IAU_BASE’. This IAU_BASE table contains all the auditing data for other products running on the WebLogic Server such as JPS, OID, etc. So, if you care only specific to BI Publisher then you want to filter by using  ‘IAU_COMPONENTTYPE’ column which contains the product name (e.g. ’xmlpserver’ for BI Publisher). Here is my sample sql query. select     "IAU_BASE"."IAU_COMPONENTTYPE" as "IAU_COMPONENTTYPE",      "IAU_BASE"."IAU_EVENTTYPE" as "IAU_EVENTTYPE",      "IAU_BASE"."IAU_EVENTCATEGORY" as "IAU_EVENTCATEGORY",      "IAU_BASE"."IAU_TSTZORIGINATING" as "IAU_TSTZORIGINATING",    to_char("IAU_TSTZORIGINATING", 'YYYY-MM-DD') IAU_DATE,    to_char("IAU_TSTZORIGINATING", 'DAY') as IAU_DAY,    to_char("IAU_TSTZORIGINATING", 'HH24') as IAU_HH24,    to_char("IAU_TSTZORIGINATING", 'WW') as IAU_WEEK_OF_YEAR,      "IAU_BASE"."IAU_INITIATOR" as "IAU_INITIATOR",      "IAU_BASE"."IAU_RESOURCE" as "IAU_RESOURCE",      "IAU_BASE"."IAU_TARGET" as "IAU_TARGET",      "IAU_BASE"."IAU_MESSAGETEXT" as "IAU_MESSAGETEXT",      "IAU_BASE"."IAU_FAILURECODE" as "IAU_FAILURECODE",      "IAU_BASE"."IAU_REMOTEIP" as "IAU_REMOTEIP" from    "KAN3_IAU"."IAU_BASE" "IAU_BASE" where "IAU_BASE"."IAU_COMPONENTTYPE" = 'xmlpserver' Once you saved a sample XML for this data model, now you can create a report with this data model. Create Report Now you can use one of the BI Publisher’s layout options to design the report layout and visualize the auditing data. I’m a big fan of Online Layout Editor, it’s just so easy and simple to create reports, and on top of that, all the reports created with Online Layout Editor has the Interactive View with automatic data linking and filtering feature without any setting or coding. If you haven’t checked the Interactive View or Online Layout Editor you might want to check these previous blog posts. (Interactive Reporting with BI Publisher 11G, Interactive Master Detail Report Just A Few Clicks Away!) But of course, you can use other layout design option such as RTF template. Here are some sample screenshots of my report design with Online Layout Editor.     Visualize and Gain More Insights about your Customers (Users) ! Now you can visualize your auditing data to have better understanding and gain more insights about your reporting environment you manage. It’s been actually helping me personally to answer the  questios like below.  How many reports are accessed or opened yesterday, today, last week ? Who is accessing which report at what time ? What are the time windows when the most of the reports access happening ? What are the most viewed reports ? Who are the active users ? What are the # of reports access or user access trend for the last month, last 6 months, last 12 months, etc ? I was talking with one of the best concierge in the world at this hotel the other day, and he was telling me that the best concierge knows about their customers inside-out therefore they can provide a very private service that is customized to each customer to meet each customer’s specific needs. Well, this is true when it comes to how to administrate and manage your reporting environment, right ? The best way to serve your customers (report users, including both viewers and developers) is to understand how they use, what they use, when they use. Auditing is not just about compliance, but it’s the way to improve the customer service. The BI Publisher 11G Auditing feature enables just that to help you understand your customers better. Happy customer service, be the best reporting concierge! p.s. please share with us on what other information would be helpful for you for the auditing! Always, any feedback is a great value and inspiration for us!  

    Read the article

< Previous Page | 369 370 371 372 373 374 375 376 377 378 379 380  | Next Page >