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  • Text tagging/analysis tool for Mac

    - by Mark Porter
    I'm a doctoral student doing research in the humanities. As part of my research I have gathered together a lot of interview text. To analyse this data I want to be able to easily tag sections of text with keywords (the tags need to be able to overlap, and perhaps be organised hierarchically) and later be able to collate those sections from across multiple files. I need to be able to do this on a Mac. It feels like a simple task but I can't find any software for doing it that isn't either horribly clunky or a massive overkill worth hundreds of pounds. Is there any good software for doing this, or are there any good ways of doing it with other software?

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  • Forensic Analysis of the OOM-Killer

    - by Oddthinking
    Ubuntu's Out-Of-Memory Killer wreaked havoc on my server, quietly assassinating my applications, sendmail, apache and others. I've managed to learn what the OOM Killer is, and about its "badness" rules. While my machine is small, my applications are even smaller, and typically only half of my physical memory is in use, let alone swap-space, so I was surprised. I am trying to work out the culprit, but I don't know how to read the OOM-Killer logs. Can anyone please point me to a tutorial on how to read the data in the logs (what are ve, free and gen?), or help me parse these logs? Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 1, exc 2326 0 goal 2326 0... Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 1 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 1, exc 2326 0 red 61795 745 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 2, exc 122 0 goal 383 0... Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 1 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 2, exc 383 0 red 61795 745 Apr 20 20:03:27 EL135 kernel: kill_signal(13516.0): task ebb0c6f0, thg d33a1b00, sig 2 Apr 20 20:03:27 EL135 kernel: OOM killed process watchdog (pid=14490, ve=13516) exited, free=43104 gen=24501. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=4457, ve=13516) exited, free=43104 gen=24502. Apr 20 20:03:27 EL135 kernel: OOM killed process ntpd (pid=10816, ve=13516) exited, free=43104 gen=24503. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=27401, ve=13516) exited, free=43104 gen=24504. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=29009, ve=13516) exited, free=43104 gen=24505. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=10557, ve=13516) exited, free=49552 gen=24506. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=24983, ve=13516) exited, free=53117 gen=24507. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=29129, ve=13516) exited, free=68493 gen=24508. Apr 20 20:03:27 EL135 kernel: OOM killed process sendmail-mta (pid=941, ve=13516) exited, free=68803 gen=24509. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=12418, ve=13516) exited, free=69330 gen=24510. Apr 20 20:03:27 EL135 kernel: OOM killed process python (pid=22953, ve=13516) exited, free=72275 gen=24511. Apr 20 20:03:27 EL135 kernel: OOM killed process apache2 (pid=6624, ve=13516) exited, free=76398 gen=24512. Apr 20 20:03:27 EL135 kernel: OOM killed process python (pid=23317, ve=13516) exited, free=94285 gen=24513. Apr 20 20:03:27 EL135 kernel: OOM killed process tail (pid=29030, ve=13516) exited, free=95339 gen=24514. Apr 20 20:03:28 EL135 kernel: OOM killed process apache2 (pid=20583, ve=13516) exited, free=101663 gen=24515. Apr 20 20:03:28 EL135 kernel: OOM killed process logger (pid=12894, ve=13516) exited, free=101694 gen=24516. Apr 20 20:03:28 EL135 kernel: OOM killed process bash (pid=21119, ve=13516) exited, free=101849 gen=24517. Apr 20 20:03:28 EL135 kernel: OOM killed process atd (pid=991, ve=13516) exited, free=101880 gen=24518. Apr 20 20:03:28 EL135 kernel: OOM killed process apache2 (pid=14649, ve=13516) exited, free=102748 gen=24519. Apr 20 20:03:28 EL135 kernel: OOM killed process grep (pid=21375, ve=13516) exited, free=132167 gen=24520. Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 4, exc 4215 0 goal 4826 0... Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): task ede29370, thg df98b880, sig 1 Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 4, exc 4826 0 red 189481 331 Apr 20 20:03:57 EL135 kernel: kill_signal(13516.0): task ede29370, thg df98b880, sig 2 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 5, exc 3564 0 goal 3564 0... Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): task c6c90110, thg cdb1a100, sig 1 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 5, exc 3564 0 red 189481 331 Apr 20 20:04:53 EL135 kernel: kill_signal(13516.0): task c6c90110, thg cdb1a100, sig 2 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): selecting to kill, queued 0, seq 6, exc 8071 0 goal 8071 0... Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): task d7294050, thg c03f42c0, sig 1 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): selected 1, signalled 1, queued 1, seq 6, exc 8071 0 red 189481 331 Apr 20 20:07:14 EL135 kernel: kill_signal(13516.0): task d7294050, thg c03f42c0, sig 2 Watchdog is a watchdog task, that was idle; nothing in the logs to suggest it had done anything for days. Its job is to restart one of the applications if it dies, so a bit ironic that it is the first to get killed. Tail was monitoring a few logs files. Unlikely to be consuming memory madly. The apache web-server only serves pages to a little old lady who only uses it to get to church on Sundays a couple of developers who were in bed asleep, and hadn't visited a page on the site for a few weeks. The only traffic it might have had is from the port-scanners; all the content is password-protected and not linked from anywhere, so no spiders are interested. Python is running two separate custom applications. Nothing in the logs to suggest they weren't humming along as normal. One of them was a relatively recent implementation, which makes suspect #1. It doesn't have any data-structures of any significance, and normally uses only about 8% of the total physical RAW. It hasn't misbehaved since. The grep is suspect #2, and the one I want to be guilty, because it was a once-off command. The command (which piped the output of a grep -r to another grep) had been started at least 30 minutes earlier, and the fact it was still running is suspicious. However, I wouldn't have thought grep would ever use a significant amount of memory. It took a while for the OOM killer to get to it, which suggests it wasn't going mad, but the OOM killer stopped once it was killed, suggesting it may have been a memory-hog that finally satisfied the OOM killer's blood-lust.

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  • Should static analysis warnings fail the CI build?

    - by Cara
    Our team is investigating various options for static analysis in our project, and have mixed opinions about whether we want our Continuous Integration build to fail because of warnings from static analysis. The argument against failing the build is that there are often exceptions to the rules, and attempting to work around them just to make the build succeed reduces productivity. A better approach would be to generate reports with the build, and regularly dedicate developer time to addressing the reported issues. The counter-argument is that it is easy for the technical debt to build up if the bugs are not addressed immediately. Also, if the build fails when a potential bug is introduced, the amount of time required to fix it is reduced. What are your thoughts?

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  • Configuring Team System Code Analysis via a FxCop rules file

    - by Ian G
    Is there anyway to configure the code analysis rules in Visual Studio Team System to match those in an FxCop configuration file and keep them in sync automatically? Not all the developers on the team have TS so keeping the rules we are currently running in an FxCop file is required so everyone can run the same set, but it would nice for those with to be able to run them in the IDE. We're introducing static analysis to an existing project so turning on everything now isn't a useful option. (We are not using Foundation Server for source control, if that makes any difference.)

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  • Static source code analysis with LLVM

    - by Phong
    I recently discover the LLVM (low level virtual machine) project, and from what I have heard It can be used to performed static analysis on a source code. I would like to know if it is possible to extract the different function call through function pointer (find the caller function and the callee function) in a program. I could find the kind of information in the website so it would be really helpful if you could tell me if such an library already exist in LLVM or can you point me to the good direction on how to build it myself (existing source code, reference, tutorial, example...). EDIT: With my analysis I actually want to extract caller/callee function call. In the case of a function pointer, I would like to return a set of possible callee. both caller and callee must be define in the source code (this does not include third party function in a library).

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  • android spectrum analysis of streaming input

    - by TheBeeKeeper
    for a school project I am trying to make an android application that, once started, will perform a spectrum analysis of live audio received from the microphone or a bluetooth headset. I know I should be using FFT, and have been looking at moonblink's open source audio analyzer ( http://code.google.com/p/moonblink/wiki/Audalyzer ) but am not familiar with android development, and his code is turning out to be too difficult for me to work with. So I suppose my questions are, are there any easier java based, or open source android apps that do spectrum analysis I can reference? Or is there any helpful information that can be given, such as; steps that need be taken to get the microphone input, put it into an fft algorithm, then display a graph of frequency and pitch over time from its output? Any help would be appreciated, thanks.

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  • SQLAuthority News – Download Whitepaper – SQL Server Analysis Services to Hive

    - by pinaldave
    The SQL Server Analysis Service is a very interesting subject and I always have enjoyed learning about it. You can read my earlier article over here. Big Data is my new interest and I have been exploring it recently. During this weekend this blog post caught my attention and I enjoyed reading it. Big Data is the next big thing. The growth is predicted to be 60% per year till 2016. There is no single solution to the growing need of the big data available in the market right now as well there is no one solution in the business intelligence eco-system available as well. However, the need of the solution is ever increasing. I am personally Klout user. You can see my Klout profile over. I do understand what Klout is trying to achieve – a single place to measure the influence of the person. However, it works a bit mysteriously. There are plenty of social media available currently in the internet world. The biggest problem all the social media faces is that everybody opens an account but hardly people logs back in. To overcome this issue and have returned visitors Klout has come up with the system where visitors can give 5/10 K+ to other users in a particular area. Looking at all the activities Klout is doing it is indeed big consumer of the Big Data as well it is early adopter of the big data and Hadoop based system.  Klout has to 1 trillion rows of data to be analyzed as well have nearly thousand terabyte warehouse. Hive the language used for Big Data supports Ad-Hoc Queries using HiveQL there are always better solutions. The alternate solution would be using SQL Server Analysis Services (SSAS) along with HiveQL. As there is no direct method to achieve there are few common workarounds already in place. A new ODBC driver from Klout has broken through the limitation and SQL Server Relation Engine can be used as an intermediate stage before SSAS. In this white paper the same solutions have been discussed in the depth. The white paper discusses following important concepts. The Klout Big Data solution Big Data Analytics based on Analysis Services Hadoop/Hive and Analysis Services integration Limitations of direct connectivity Pass-through queries to linked servers Best practices and lessons learned This white paper discussed all the important concepts which have enabled Klout to go go to the next level with all the offerings as well helped efficiency by offering a few out of the box solutions. I personally enjoy reading this white paper and I encourage all of you to do so. SQL Server Analysis Services to Hive Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, T SQL, Technology

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  • Rawr Code Clone Analysis&ndash;Part 0

    - by Dylan Smith
    Code Clone Analysis is a cool new feature in Visual Studio 11 (vNext).  It analyzes all the code in your solution and attempts to identify blocks of code that are similar, and thus candidates for refactoring to eliminate the duplication.  The power lies in the fact that the blocks of code don't need to be identical for Code Clone to identify them, it will report Exact, Strong, Medium and Weak matches indicating how similar the blocks of code in question are.   People that know me know that I'm anal enthusiastic about both writing clean code, and taking old crappy code and making it suck less. So the possibilities for this feature have me pretty excited if it works well - and thats a big if that I'm hoping to explore over the next few blog posts. I'm going to grab the Rawr source code from CodePlex (a World Of Warcraft gear calculator engine program), run Code Clone Analysis against it, then go through the results one-by-one and refactor where appropriate blogging along the way.  My goals with this blog series are twofold: Evaluate and demonstrate Code Clone Analysis Provide some concrete examples of refactoring code to eliminate duplication and improve the code-base Here are the initial results:   Code Clone Analysis has found: 129 Exact Matches 201 Strong Matches 300 Medium Matches 193 Weak Matches Also indicated is that there was a total of 45,181 potentially duplicated lines of code that could be eliminated through refactoring.  Considering the entire solution only has 109,763 lines of code, if true, the duplicates lines of code number is pretty significant. In the next post we’ll start examining some of the individual results and determine if they really do indicate a potential refactoring.

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  • The Sensemaking Spectrum for Business Analytics: Translating from Data to Business Through Analysis

    - by Joe Lamantia
    One of the most compelling outcomes of our strategic research efforts over the past several years is a growing vocabulary that articulates our cumulative understanding of the deep structure of the domains of discovery and business analytics. Modes are one example of the deep structure we’ve found.  After looking at discovery activities across a very wide range of industries, question types, business needs, and problem solving approaches, we've identified distinct and recurring kinds of sensemaking activity, independent of context.  We label these activities Modes: Explore, compare, and comprehend are three of the nine recognizable modes.  Modes describe *how* people go about realizing insights.  (Read more about the programmatic research and formal academic grounding and discussion of the modes here: https://www.researchgate.net/publication/235971352_A_Taxonomy_of_Enterprise_Search_and_Discovery) By analogy to languages, modes are the 'verbs' of discovery activity.  When applied to the practical questions of product strategy and development, the modes of discovery allow one to identify what kinds of analytical activity a product, platform, or solution needs to support across a spread of usage scenarios, and then make concrete and well-informed decisions about every aspect of the solution, from high-level capabilities, to which specific types of information visualizations better enable these scenarios for the types of data users will analyze. The modes are a powerful generative tool for product making, but if you've spent time with young children, or had a really bad hangover (or both at the same time...), you understand the difficult of communicating using only verbs.  So I'm happy to share that we've found traction on another facet of the deep structure of discovery and business analytics.  Continuing the language analogy, we've identified some of the ‘nouns’ in the language of discovery: specifically, the consistently recurring aspects of a business that people are looking for insight into.  We call these discovery Subjects, since they identify *what* people focus on during discovery efforts, rather than *how* they go about discovery as with the Modes. Defining the collection of Subjects people repeatedly focus on allows us to understand and articulate sense making needs and activity in more specific, consistent, and complete fashion.  In combination with the Modes, we can use Subjects to concretely identify and define scenarios that describe people’s analytical needs and goals.  For example, a scenario such as ‘Explore [a Mode] the attrition rates [a Measure, one type of Subject] of our largest customers [Entities, another type of Subject] clearly captures the nature of the activity — exploration of trends vs. deep analysis of underlying factors — and the central focus — attrition rates for customers above a certain set of size criteria — from which follow many of the specifics needed to address this scenario in terms of data, analytical tools, and methods. We can also use Subjects to translate effectively between the different perspectives that shape discovery efforts, reducing ambiguity and increasing impact on both sides the perspective divide.  For example, from the language of business, which often motivates analytical work by asking questions in business terms, to the perspective of analysis.  The question posed to a Data Scientist or analyst may be something like “Why are sales of our new kinds of potato chips to our largest customers fluctuating unexpectedly this year?” or “Where can innovate, by expanding our product portfolio to meet unmet needs?”.  Analysts translate questions and beliefs like these into one or more empirical discovery efforts that more formally and granularly indicate the plan, methods, tools, and desired outcomes of analysis.  From the perspective of analysis this second question might become, “Which customer needs of type ‘A', identified and measured in terms of ‘B’, that are not directly or indirectly addressed by any of our current products, offer 'X' potential for ‘Y' positive return on the investment ‘Z' required to launch a new offering, in time frame ‘W’?  And how do these compare to each other?”.  Translation also happens from the perspective of analysis to the perspective of data; in terms of availability, quality, completeness, format, volume, etc. By implication, we are proposing that most working organizations — small and large, for profit and non-profit, domestic and international, and in the majority of industries — can be described for analytical purposes using this collection of Subjects.  This is a bold claim, but simplified articulation of complexity is one of the primary goals of sensemaking frameworks such as this one.  (And, yes, this is in fact a framework for making sense of sensemaking as a category of activity - but we’re not considering the recursive aspects of this exercise at the moment.) Compellingly, we can place the collection of subjects on a single continuum — we call it the Sensemaking Spectrum — that simply and coherently illustrates some of the most important relationships between the different types of Subjects, and also illuminates several of the fundamental dynamics shaping business analytics as a domain.  As a corollary, the Sensemaking Spectrum also suggests innovation opportunities for products and services related to business analytics. The first illustration below shows Subjects arrayed along the Sensemaking Spectrum; the second illustration presents examples of each kind of Subject.  Subjects appear in colors ranging from blue to reddish-orange, reflecting their place along the Spectrum, which indicates whether a Subject addresses more the viewpoint of systems and data (Data centric and blue), or people (User centric and orange).  This axis is shown explicitly above the Spectrum.  Annotations suggest how Subjects align with the three significant perspectives of Data, Analysis, and Business that shape business analytics activity.  This rendering makes explicit the translation and bridging function of Analysts as a role, and analysis as an activity. Subjects are best understood as fuzzy categories [http://georgelakoff.files.wordpress.com/2011/01/hedges-a-study-in-meaning-criteria-and-the-logic-of-fuzzy-concepts-journal-of-philosophical-logic-2-lakoff-19731.pdf], rather than tightly defined buckets.  For each Subject, we suggest some of the most common examples: Entities may be physical things such as named products, or locations (a building, or a city); they could be Concepts, such as satisfaction; or they could be Relationships between entities, such as the variety of possible connections that define linkage in social networks.  Likewise, Events may indicate a time and place in the dictionary sense; or they may be Transactions involving named entities; or take the form of Signals, such as ‘some Measure had some value at some time’ - what many enterprises understand as alerts.   The central story of the Spectrum is that though consumers of analytical insights (represented here by the Business perspective) need to work in terms of Subjects that are directly meaningful to their perspective — such as Themes, Plans, and Goals — the working realities of data (condition, structure, availability, completeness, cost) and the changing nature of most discovery efforts make direct engagement with source data in this fashion impossible.  Accordingly, business analytics as a domain is structured around the fundamental assumption that sense making depends on analytical transformation of data.  Analytical activity incrementally synthesizes more complex and larger scope Subjects from data in its starting condition, accumulating insight (and value) by moving through a progression of stages in which increasingly meaningful Subjects are iteratively synthesized from the data, and recombined with other Subjects.  The end goal of  ‘laddering’ successive transformations is to enable sense making from the business perspective, rather than the analytical perspective.Synthesis through laddering is typically accomplished by specialized Analysts using dedicated tools and methods. Beginning with some motivating question such as seeking opportunities to increase the efficiency (a Theme) of fulfillment processes to reach some level of profitability by the end of the year (Plan), Analysts will iteratively wrangle and transform source data Records, Values and Attributes into recognizable Entities, such as Products, that can be combined with Measures or other data into the Events (shipment of orders) that indicate the workings of the business.  More complex Subjects (to the right of the Spectrum) are composed of or make reference to less complex Subjects: a business Process such as Fulfillment will include Activities such as confirming, packing, and then shipping orders.  These Activities occur within or are conducted by organizational units such as teams of staff or partner firms (Networks), composed of Entities which are structured via Relationships, such as supplier and buyer.  The fulfillment process will involve other types of Entities, such as the products or services the business provides.  The success of the fulfillment process overall may be judged according to a sophisticated operating efficiency Model, which includes tiered Measures of business activity and health for the transactions and activities included.  All of this may be interpreted through an understanding of the operational domain of the businesses supply chain (a Domain).   We'll discuss the Spectrum in more depth in succeeding posts.

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  • Which tool can list writing access to a specific variable in C?

    - by Lichtblitz
    Unfortunately I'm not even sure how this sort of static analysis is called. It's not really control flow analysis because I'm not looking for function calls and I don't really need data flow analysis because I don't care about the actual values. I just need a tool that lists the locations (file, function) where writing access to a specific variable takes place. I don't even care if that list contained lines that are unreachable. I could imagine that writing a simple parser could suffice for this task but I'm certain that there must be a tool out there that does this simple analysis. As a poor student I would appreciate free or better yet open source tools and if someone could tell me how this type of static analysis is actually called, I would be equally grateful! EDIT: I forgot to mention there's no pointer arithmetic in the code base.

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  • Static code analysis for VB6 and classic ASP

    - by Ryan
    I'm looking for a static code analysis tool that will determine if I have orphaned functions in my VB6 code. The problem I'm running into is we make calls to the VB6 code from classic asp. Is there a tool that will look at both the classic asp and VB6 and determine if there are any orphaned functions?

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  • Static code analysis tools for VB6

    - by Maksym Markov
    Right now we are maintaining some old project written in VB6 we are planning to implement continues integration sefver for it. We would like to implement some code analysis as well to track that maintanability at least not getting worse. Basically there is only one requirement - the tool should be command line so we can call it from constinues integration server and it should work with VB6 projects. I will really a;preciate any recommendations regards tools to try. Thank you, Maksym

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  • Code Analysis - Treat as Error

    - by Brian Schmitt
    Looking to enable the "Enable code Analysis on Build" feature in Visual Studio. Obviously the Rules are a best practice, and I am working with an existing code base that currently fails many of the rules. I am looking for input as to which rules are the most egregious and should be treated as an Error.

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  • Javascript source code analysis ( specifically duplication checking )

    - by David
    Partial duplicate of this Notes: I already use JSLint extensively via a tool I wrote that scans in intervals my current project directory for recently updated/created .js files. It's drastically improved productivity for me and I doubt there is anything as good as JSLint for the price (it's free). That said, is there any analysis tool out there that can find repetitive or near-duplicate code blocks, the goal being to make it easier to find opportunities to consolidate large files or small/medium sized projects?

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  • Glassfish log files analysis

    - by Cem
    Can I get some recommendations for good log analysis software for Glassfish log files? Since it will not vary from application server to application server dramatically, I guess that there is a common solution for all servers. Thanks

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  • .Net Analysis tools [closed]

    - by TWith2Sugars
    Possible Duplicate: What static analysis tools are available for C#? At work we tend to use two tools for analysing our projects, FxCop to analyse our managed code and StyleCop to have consistent code layout. I found these tools pretty much by accident and it has led me to wonder what other tools are available that I might of missed?

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  • Oracle Solaris Crash Analysis Tool 5.3 now available

    - by user12609056
    Oracle Solaris Crash Analysis Tool 5.3 The Oracle Solaris Crash Analysis Tool Team is happy to announce the availability of release 5.3.  This release addresses bugs discovered since the release of 5.2 plus enhancements to support Oracle Solaris 11 and updates to Oracle Solaris versions 7 through 10. The packages are available on My Oracle Support - simply search for Patch 13365310 to find the downloadable packages. Release Notes General blast support The blast GUI has been removed and is no longer supported. Oracle Solaris 2.6 Support As of Oracle Solaris Crash Analysis Tool 5.3, support for Oracle Solaris 2.6 has been dropped. If you have systems running Solaris 2.6, you will need to use Oracle Solaris Crash Analysis Tool 5.2 or earlier to read its crash dumps. New Commands Sanity Command Though one can re-run the sanity checks that are run at tool start-up using the coreinfo command, many users were unaware that they were. Though these checks can still be run using that command, a new command, namely sanity, can now be used to re-run the checks at any time. Interface Changes scat_explore -r and -t option The -r option has ben added to scat_explore so that a base directory can be specified and the -t op[tion was added to enable color taggging of the output. The scat_explore sub-command now accepts new options. Usage is: scat --scat_explore [-atv] [-r base_dir] [-d dest] [unix.N] [vmcore.]N Where: -v Verbose Mode: The command will print messages highlighting what it's doing. -a Auto Mode: The command does not prompt for input from the user as it runs. -d dest Instructs scat_explore to save it's output in the directory dest instead of the present working directory. -r base_dir Instructs scat_explore to save it's under the directory base_dir instead of the present working directory. If it is not specified using the -d option, scat_explore names it's output file as "scat_explore_system_name_hostid_lbolt_value_corefile_name." -t Enable color tags. When enabled, scat_explore tags important text with colors that match the level of importance. These colors correspond to the color normally printed when running Oracle Solaris Crash Analysis Tool in interactive mode. Tag Name Definition FATAL An extremely important message which should be investigated. WARNING A warning that may or may not have anything to do with the crash. ERROR An error, usually printer with a suggested command ALERT Used to indicate something the tool discovered. INFO Purely informational message INFO2 A follow-up to an INFO tagged message REDZONE Usually used when prnting memory info showing something is in the kernel's REDZONE. N The number of the crash dump. Specifying unix.N vmcore.N is optional and not required. Example: $ scat --scat_explore -a -v -r /tmp vmcore.0 #Output directory: /tmp/scat_explore_oomph_833a2959_0x28800_vmcore.0 #Tar filename: scat_explore_oomph_833a2959_0x28800_vmcore.0.tar #Extracting crash data... #Gathering standard crash data collections... #Panic string indicates a possible hang... #Gathering Hang Related data... #Creating tar file... #Compressing tar file... #Successful extraction SCAT_EXPLORE_DATA_DIR=/tmp/scat_explore_oomph_833a2959_0x28800_vmcore.0 Sending scat_explore results The .tar.gz file that results from a scat_explore run may be sent using Oracle Secure File Transfer. The Oracle Secure File Transfer User Guide describes how to use it to send a file. The send_scat_explore script now has a -t option for specifying a to address for sending the results. This option is mandatory. Known Issues There are a couple known issues that we are addressing in release 5.4, which you should expect to see soon: Display of timestamps in threads and clock information is incorrect in some cases. There are alignment issues with some of the tables produced by the tool.

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  • Implementing User-Defined Hierarchies in SQL Server Analysis Services

    To be able to drill into multidimensional cube data at several levels, you must implement all of the hierarchies on the database dimensions. Then you'll create the attribute relationships necessary to optimize performance. Analysis Services hierarchies offer plenty of possibilities for displaying the data that your business requires. Rob Sheldon continues his series on SQL Server Analysis Services 2008.

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  • Implementing User-Defined Hierarchies in SQL Server Analysis Services

    To be able to drill into multidimensional cube data at several levels, you must implement all of the hierarchies on the database dimensions. Then you'll create the attribute relationships necessary to optimize performance. Analysis Services hierarchies offer plenty of possibilities for displaying the data that your business requires. Rob Sheldon continues his series on SQL Server Analysis Services 2008.

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  • How to Do Competition Analysis

    One of the most important aspects of SEO is the work you put in before you even touch the website or build a single back link. This analysis work involves keyword research and competition analysis. Choose the wrong keywords and you could be wasting all your efforts in the onsite and offsite optimization. Choose keywords which have too much competition and you'll be taking on an uphill battle.

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  • A new Excel 2010 book for Data Analysis

    - by Marco Russo (SQLBI)
    Microsoft Press just announced the printing of Microsoft Excel 2010: Data Analysis and Business Modeling , which is the third edition of the book written by Wayne L. Winston covering many data analysis and modeling techniques using a very clear problem-solution approach, including a good statistical explanation whenever it is necessary. I suggest this book as a good complement to our Microsoft PowerPivot for Excel 2010: Give Your Data Meaning !...(read more)

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  • REAL PRACTICES: Performance Scaling Microsoft SQL Server 2008 Analysis Services at Microsoft adCenter

    This white paper explains how Microsoft® adCenter implemented a Microsoft SQL Server® 2008 Analysis Services Scalable Shared Database on EMC® Symmetrix VMAX™ storage. Leveraging TimeFinder® clones and Enterprise Flash Drives with the read-only feature of SQL Server 2008 Analysis Services allowed adCenter to dramatically scale out OLAP while maintaining SLAs and decreasing system outages.

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