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  • How do I get VDPAU working with Ubuntu 9.10?

    - by Brad Robertson
    What do I need to do to get MKV HD videos playing with VDPAU and also Blu-ray discs? Lots of people say you need to compile the latest MPlayer (which I haven't had luck doing) for VDPAU. I found an mplayer ppa that says it has VDPAU compiled into it so I'd like to use that. What packages do I need for playing MKV files and Blu-ray with the video decoding offloaded to my GPU? So far I haven't had any luck with any of the tutorials I've found. I'm just looking for a quick synopsis that will tell me what I'm looking for as I'm kind of shooting in the dark. (I didn't know what VDPAU was until a few days ago.)

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  • Creating hard drive backup images efficiently

    - by Arrieta
    We are in the process of pruning our directories to recuperate some disk space. The 'algorithm' for the pruning/backup process consists of a list of directories and, for each one of them, a set of rules, e.g. 'compress *.bin', 'move *.blah', 'delete *.crap', 'leave *.important'; these rules change from directory to directory but are well known. The compressed and moved files are stored in a temporary file system, burned onto a blue ray, tested within the blue ray, and, finally, deleted from their original locations. I am doing this in Python (basically a walk statement with a dictionary with the rules for each extension in each folder). Do you recommend a better methodology for pruning file systems? How do you do it? We run on Linux.

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  • Online betting system design [closed]

    - by Rafal
    I am a Computer Science student, preparing for my exam in software engineering. I am strugging with answering one of the sample questions to the scenario below. My understanding is that the system design approach should probably be a mixture of agile and plan driven elements but - since I've no practical experience - it's hard for me to decide on the balance and tolls that should be used. I will appreciate any hints from experienced business analysts who were involved in similar kind of projects. Ray Sing is the owner of “Last Betz", a bookmakers with 7 outlets across Louth and Meath. With the advent of smartphones Ray would now like to allow his clients to place their bets online using their mobile devices. Clients would register for an account and password and would log their credit card details via the Last Betz website. To begin using the facility customers must 'load' their accounts with 100 euros. Any winnings, minus commission, will be placed in the account whilst any losses will be automatically deducted from the account. Assuming you have been selected to develop the above system: How would you approach the design of this system? Discuss the design methods and models you would use.

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  • What's the difference between "Flash Drive" and "Flash Memory"?

    - by Clive D
    I have a problem with a Blu ray disk I bought. I talked to a Sony technician who advised me to plug a "USB Flash Memory Stick" into the Blu-ray player. Is this something specific? Is there a difference between the following two? "USB Flash Drive" "USB Flash Memory" When I go to Curry's or other sites that sell USB Sticks, they only talk about "USB Flash Drives". I've been in computing for many years and know the basics, but "memory" and "drive" are different things to me.

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  • Handling Indirection and keeping layers of method calls, objects, and even xml files straight

    - by Cervo
    How do you keep everything straight as you trace deeply into a piece of software through multiple method calls, object constructors, object factories, and even spring wiring. I find that 4 or 5 method calls are easy to keep in my head, but once you are going to 8 or 9 calls deep it gets hard to keep track of everything. Are there strategies for keeping everything straight? In particular, I might be looking for how to do task x, but then as I trace down (or up) I lose track of that goal, or I find multiple layers need changes, but then I lose track of which changes as I trace all the way down. Or I have tentative plans that I find out are not valid but then during the tracing I forget that the plan is invalid and try to consider the same plan all over again killing time.... Is there software that might be able to help out? grep and even eclipse can help me to do the actual tracing from a call to the definition but I'm more worried about keeping track of everything including the de-facto plan for what has to change (which might vary as you go down/up and realize the prior plan was poor). In the past I have dealt with a few big methods that you trace and pretty much can figure out what is going on within a few calls. But now there are dozens of really tiny methods, many just a single call to another method/constructor and it is hard to keep track of them all.

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  • Converting raw data type to enumerated type

    - by Jim Lahman
    There are times when an enumerated type is preferred over using the raw data type.  An example of using a scheme is when we need to check the health of x-ray gauges in use on a production line.  Rather than using a scheme like 0, 1 and 2, we can use an enumerated type: 1: /// <summary> 2: /// POR Healthy status indicator 3: /// </summary> 4: /// <remarks>The healthy status is for each POR x-ray gauge; each has its own status.</remarks> 5: [Flags] 6: public enum POR_HEALTH : short 7: { 8: /// <summary> 9: /// POR1 healthy status indicator 10: /// </summary> 11: POR1 = 0, 12: /// <summary> 13: /// POR2 healthy status indicator 14: /// </summary> 15: POR2 = 1, 16: /// <summary> 17: /// Both POR1 and POR2 healthy status indicator 18: /// </summary> 19: BOTH = 2 20: } By using the [Flags] attribute, we are treating the enumerated type as a bit mask.  We can then use bitwise operations such as AND, OR, NOT etc. . Now, when we want to check the health of a specific gauge, we would rather use the name of the gauge than the numeric identity; it makes for better reading and programming practice. To translate the numeric identity to the enumerated value, we use the Parse method of Enum class: POR_HEALTH GaugeHealth = (POR_HEALTH) Enum.Parse(typeof(POR_HEALTH), XrayMsg.Gauge_ID.ToString()); The Parse method creates an instance of the enumerated type.  Now, we can use the name of the gauge rather than the numeric identity: 1: if (GaugeHealth == POR_HEALTH.POR1 || GaugeHealth == POR_HEALTH.BOTH) 2: { 3: XrayHealthyTag.Name = Properties.Settings.Default.POR1XRayHealthyTag; 4: } 5: else if (GaugeHealth == POR_HEALTH.POR2) 6: { 7: XrayHealthyTag.Name = Properties.Settings.Default.POR2XRayHealthyTag; 8: }

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  • Assigning valid moves on board game

    - by Kunal4536
    I am making a board game in unity 4.3 2d similar to checkers. I have added an empty object to all the points where player can move and added a box collider to each empty object.I attached a click to move script to each player token. Now I want to assign valid moves. e.g. as shown in picture... Players can only move on vertex of each square.Player can only move to adjacent vertex.Thus it can only move from red spot to yellow and cannot move to blue spot.There is another condition which is : if there is the token of another player at the yellow spot then the player cannot move to that spot. Instead it will have to go from red to green spot. How can I find the valid moves of the player by scripting. I have another problem with click to move. When I click all the objects move to that position.But I only want to move a single token. So what can i add to script to select a specific object and then click to move the specific object.Here is my script for click to move. var obj:Transform; private var hitPoint : Vector3; private var move: boolean = false; private var startTime:float; var speed = 1; function Update () { if(Input.GetKeyDown(KeyCode.Mouse0)) { var hit : RaycastHit; // no point storing this really var ray = Camera.main.ScreenPointToRay (Input.mousePosition); if (Physics.Raycast (ray, hit, 10000)) { hitPoint = hit.point; move = true; startTime = Time.time; } } if(move) { obj.position = Vector3.Lerp(obj.position, hitPoint, Time.deltaTime * speed); if(obj.position == hitPoint) { move = false; } } }`

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  • OpenWorld 2011 Video Index

    - by Chris Kawalek
    We did quite a few virtualization videos this year at Oracle OpenWorld 2011. You can find all these and more on our YouTube channel. Virtualization Wrapup Adam Hawley discusses the Oracle virtualization presence at Oracle OpenWorld 2011. http://www.youtube.com/oraclevirtualization#p/f/2/53_SQYljqN4 Oracle Applications on iPad Brad Lackey shows how you can access Oracle Applications on iPad. http://www.youtube.com/oraclevirtualization#p/f/9/3Ug5km3uxEQ Thinkquest.org and Oracle VM Dan Herrup describes how Thinkquest.org is using Oracle VM to help kids learn how to solve real world problems with computer technology. http://www.youtube.com/oraclevirtualization#p/f/6/Bw-km5kqzEo Avaya and Oracle Virtualization See Oracle desktop virtualization in action at Avaya's booth. http://www.youtube.com/oraclevirtualization#p/f/4/xIHRIijEPkM Eco-Features of Sun Ray Clients Michael Dann shows off the Sun Ray 3 Plus and talks about the eco benefits of Oracle's extremely low power consumption client device for desktop virtualization. http://www.youtube.com/oraclevirtualization#p/f/3/ulArHGe1OmM Application and Desktop Access with Oracle Secure Global Desktop Watch Jeff Harvey do a quick demo of Oracle Secure Global Desktop accessing Oracle Applications. http://www.youtube.com/oraclevirtualization#p/f/5/g_ikA7dwh0g Oracle VM VirtualBox for VDI Andy Hall describes how enterprises leverage Oracle VM VirtualBox as part of their VDI deployments. http://www.youtube.com/oraclevirtualization#p/f/8/WmkeYlzgnZ8 TechCast Live: The Coolest Virtualization Products Interview with Andy Hall about the desktop virtualization portfolio. http://www.youtube.com/oraclevirtualization#p/f/7/VMkrAhZ83AA

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  • OpenWorld 2011 Video Index

    - by Chris Kawalek
    We did quite a few virtualization videos this year at Oracle OpenWorld 2011. You can find all these and more on our YouTube channel. Virtualization Wrapup Adam Hawley discusses the Oracle virtualization presence at Oracle OpenWorld 2011. http://www.youtube.com/oraclevirtualization#p/f/2/53_SQYljqN4 Oracle Applications on iPad Brad Lackey shows how you can access Oracle Applications on iPad. http://www.youtube.com/oraclevirtualization#p/f/9/3Ug5km3uxEQ Thinkquest.org and Oracle VM Dan Herrup describes how Thinkquest.org is using Oracle VM to help kids learn how to solve real world problems with computer technology. http://www.youtube.com/oraclevirtualization#p/f/6/Bw-km5kqzEo Avaya and Oracle Virtualization See Oracle desktop virtualization in action at Avaya's booth. http://www.youtube.com/oraclevirtualization#p/f/4/xIHRIijEPkM Eco-Features of Sun Ray Clients Michael Dann shows off the Sun Ray 3 Plus and talks about the eco benefits of Oracle's extremely low power consumption client device for desktop virtualization. http://www.youtube.com/oraclevirtualization#p/f/3/ulArHGe1OmM Application and Desktop Access with Oracle Secure Global Desktop Watch Jeff Harvey do a quick demo of Oracle Secure Global Desktop accessing Oracle Applications. http://www.youtube.com/oraclevirtualization#p/f/5/g_ikA7dwh0g Oracle VM VirtualBox for VDI Andy Hall describes how enterprises leverage Oracle VM VirtualBox as part of their VDI deployments. http://www.youtube.com/oraclevirtualization#p/f/8/WmkeYlzgnZ8 TechCast Live: The Coolest Virtualization Products Interview with Andy Hall about the desktop virtualization portfolio. http://www.youtube.com/oraclevirtualization#p/f/7/VMkrAhZ83AA

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  • 3D physics engine for accurate collision handling on desktop/laptop computers (non-console)

    - by Georges Oates Larsen
    What are your suggestions for a physics engine that satisfies the following criteria? Capable of calculating collisions between multiple concave mesh-based colliders Handles many collisions going on at once (for instance one mesh being wedged between two others, which themselves may be wedged between two meshes) Does not allow for collider passthrough, even at high speeds. For instance, if I am applying force to a programmatically hinged object that makes it spin, I do not want it to pass through another rigidbody that it collides with while spinning. I have this problem using PhysX As implied before, reacts well to hinged objects, preferably has its own implementation of a hinge, but I am willing to program my own. The important part is that it has some sort of interface that guarantees accurate collision tracking even when dealing with these things Platform independent -- runs on mac as well as PC, also not tied down to specific graphics cards I think that's the best way to explain what I am looking for. Basically, I need SUPER reliable collisions. Something that can't be accomplished with a simple ray casting approach that sends a ray from the last position of the object to the current position (as this object may be potentially large and colliding with small objects via rotation) Bonus points for also including an OPEN SOURCE engine.

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  • Make Gameobject Stand On Surface Facing Certain Direction

    - by Julian
    I want to make a biped character stand on any surface I click on. Surfaces have up vectors of any of positive or negative X,Y,Z. So imagine a cube with each face being a gameobject whose up vector pointing directly away from the cube. If my character is facing "forward" and I click on a surface which is to the left or right of me ( left or right walls), I want my character to now be standing on that surface but still be facing in the direction he initially was. If I click on a wall which is in the forward path of my character i want him to now be standing on that surface and his forward to now be what was once "up" relative to my character. Here is the code I am working with now. void Update() { if (Input.GetMouseButtonUp (0)) { RaycastHit hit; var ray = Camera.main.ScreenPointToRay(Input.mousePosition); if (Physics.Raycast(ray, out hit)) { Vector3 upVectBefore = transform.up; Vector3 forwardVectBefore = transform.forward; Quaternion rotationVectBefore = transform.rotation; Vector3 hitPosition = hit.transform.position; transform.position = hitPosition; float lookDifference = Vector3.Distance(hit.transform.up, forwardVectBefore); if(Vector3.Distance(hit.transform.up, upVectBefore) < .23) //Same normal { transform.rotation = rotationVectBefore; } else if(lookDifference > 1.412 && lookDifference <= 1.70607) //side wall { transform.up = hit.transform.up; transform.forward = forwardVectBefore; } else //head on wall { transform.up = hit.transform.up; transform.forward = upVectBefore; } } } } The first case "Same normal" works fine, however the other two do not work as I would like them to. Sometimes my character is laying down on the surface or on the wrong side of the surface. Does anyone know nice way of solving this problem?

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  • Partition tool with console UI (as in server installation)?

    - by lepe
    Back in 2006, Ray (3DLover) posted the same question in: http://ubuntuforums.org/showthread.php?t=309680 but none of the answers were really useful. Now with a little help from AskUbuntu community, I would like to repeat his question again to see if this time it can be answered correctly. So this is the question (and what I wish too): I'm looking for a UI tool for managing partitions in a console. I have installed Ubuntu Server, so I don't have X Windows at all. fdisk and sfdisk are entirely command line. parted is slightly better, but it's not really a UI. cfdisk has somewhat of a UI, but it only works on one disk at a time, and there's no advanced options like configuring LVM or RAID. Just partitioning. I love the partition tool that is available during the OS install procedure. You can partition, configure RAID's and LMV sets. It can format the partitions with several different file systems, it can set labels, mount options and it can insert your volumes into your fstab. Is this tool available as a stand-alone program? I can't find it anywhere. I think it's called parted_server, but I can't find much information about where to get it. In the past, I have run the Ubuntu install procedure just to use the partition manager that comes with it. (canceling the install after making my partition edits) Anyone help me on this? Thanks -Ray Thanks in advance.

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  • LLBLGen Pro v3.5 has been released!

    - by FransBouma
    Last weekend we released LLBLGen Pro v3.5! Below the list of what's new in this release. Of course, not everything is on this list, like the large amount of work we put in refactoring the runtime framework. The refactoring was necessary because our framework has two paradigms which are added to the framework at a different time, and from a design perspective in the wrong order (the paradigm we added first, SelfServicing, should have been built on top of Adapter, the other paradigm, which was added more than a year after the first released version). The refactoring made sure the framework re-uses more code across the two paradigms (they already shared a lot of code) and is better prepared for the future. We're not done yet, but refactoring a massive framework like ours without breaking interfaces and existing applications is ... a bit of a challenge ;) To celebrate the release of v3.5, we give every customer a 30% discount! Use the coupon code NR1ORM with your order :) The full list of what's new: Designer Rule based .NET Attribute definitions. It's now possible to specify a rule using fine-grained expressions with an attribute definition to define which elements of a given type will receive the attribute definition. Rules can be assigned to attribute definitions on the project level, to make it even easier to define attribute definitions in bulk for many elements in the project. More information... Revamped Project Settings dialog. Multiple project related properties and settings dialogs have been merged into a single dialog called Project Settings, which makes it easier to configure the various settings related to project elements. It also makes it easier to find features previously not used  by many (e.g. type conversions) More information... Home tab with Quick Start Guides. To make new users feel right at home, we added a home tab with quick start guides which guide you through four main use cases of the designer. System Type Converters. Many common conversions have been implemented by default in system type converters so users don't have to develop their own type converters anymore for these type conversions. Bulk Element Setting Manipulator. To change setting values for multiple project elements, it was a little cumbersome to do that without a lot of clicking and opening various editors. This dialog makes changing settings for multiple elements very easy. EDMX Importer. It's now possible to import entity model data information from an existing Entity Framework EDMX file. Other changes and fixes See for the full list of changes and fixes the online documentation. LLBLGen Pro Runtime Framework WCF Data Services (OData) support has been added. It's now possible to use your LLBLGen Pro runtime framework powered domain layer in a WCF Data Services application using the VS.NET tools for WCF Data Services. WCF Data Services is a Microsoft technology for .NET 4 to expose your domain model using OData. More information... New query specification and execution API: QuerySpec. QuerySpec is our new query specification and execution API as an alternative to Linq and our more low-level API. It's build, like our Linq provider, on top of our lower-level API. More information... SQL Server 2012 support. The SQL Server DQE allows paging using the new SQL Server 2012 style. More information... System Type converters. For a common set of types the LLBLGen Pro runtime framework contains built-in type conversions so you don't need to write your own type converters anymore. Public/NonPublic property support. It's now possible to mark a field / navigator as non-public which is reflected in the runtime framework as an internal/friend property instead of a public property. This way you can hide properties from the public interface of a generated class and still access it through code added to the generated code base. FULL JOIN support. It's now possible to perform FULL JOIN joins using the native query api and QuerySpec. It's left to the developer to check whether the used target database supports FULL (OUTER) JOINs. Using a FULL JOIN with entity fetches is not recommended, and should only be used when both participants in the join aren't the target of the fetch. Dependency Injection Tracing. It's now possible to enable tracing on dependency injection. Enable tracing at level '4' on the traceswitch 'ORMGeneral'. This will emit trace information about which instance of which type got an instance of type T injected into property P. Entity Instances in projections in Linq. It's now possible to return an entity instance in a custom Linq projection. It's now also possible to pass this instance to a method inside the query projection. Inheritance fully supported in this construct. Entity Framework support The Entity Framework has been updated in the recent year with code-first support and a new simpler context api: DbContext (with DbSet). The amount of code to generate is smaller and the context simpler. LLBLGen Pro v3.5 comes with support for DbContext and DbSet and generates code which utilizes these new classes. NHibernate support NHibernate v3.2+ built-in proxy factory factory support. By default the built-in ProxyFactoryFactory is selected. FluentNHibernate Session Manager uses 1.2 syntax. Fluent NHibernate mappings generate a SessionManager which uses the v1.2 syntax for the ProxyFactoryFactory location Optionally emit schema / catalog name in mappings Two settings have been added which allow the user to control whether the catalog name and/or schema name as known in the project in the designer is emitted into the mappings.

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  • Atmospheric Scattering

    - by Lawrence Kok
    I'm trying to implement atmospheric scattering based on Sean O`Neil algorithm that was published in GPU Gems 2. But I have some trouble getting the shader to work. My latest attempts resulted in: http://img253.imageshack.us/g/scattering01.png/ I've downloaded sample code of O`Neil from: http://http.download.nvidia.com/developer/GPU_Gems_2/CD/Index.html. Made minor adjustments to the shader 'SkyFromAtmosphere' that would allow it to run in AMD RenderMonkey. In the images it is see-able a form of banding occurs, getting an blueish tone. However it is only applied to one half of the sphere, the other half is completely black. Also the banding appears to occur at Zenith instead of Horizon, and for a reason I managed to get pac-man shape. I would appreciate it if somebody could show me what I'm doing wrong. Vertex Shader: uniform mat4 matView; uniform vec4 view_position; uniform vec3 v3LightPos; const int nSamples = 3; const float fSamples = 3.0; const vec3 Wavelength = vec3(0.650,0.570,0.475); const vec3 v3InvWavelength = 1.0f / vec3( Wavelength.x * Wavelength.x * Wavelength.x * Wavelength.x, Wavelength.y * Wavelength.y * Wavelength.y * Wavelength.y, Wavelength.z * Wavelength.z * Wavelength.z * Wavelength.z); const float fInnerRadius = 10; const float fOuterRadius = fInnerRadius * 1.025; const float fInnerRadius2 = fInnerRadius * fInnerRadius; const float fOuterRadius2 = fOuterRadius * fOuterRadius; const float fScale = 1.0 / (fOuterRadius - fInnerRadius); const float fScaleDepth = 0.25; const float fScaleOverScaleDepth = fScale / fScaleDepth; const vec3 v3CameraPos = vec3(0.0, fInnerRadius * 1.015, 0.0); const float fCameraHeight = length(v3CameraPos); const float fCameraHeight2 = fCameraHeight * fCameraHeight; const float fm_ESun = 150.0; const float fm_Kr = 0.0025; const float fm_Km = 0.0010; const float fKrESun = fm_Kr * fm_ESun; const float fKmESun = fm_Km * fm_ESun; const float fKr4PI = fm_Kr * 4 * 3.141592653; const float fKm4PI = fm_Km * 4 * 3.141592653; varying vec3 v3Direction; varying vec4 c0, c1; float scale(float fCos) { float x = 1.0 - fCos; return fScaleDepth * exp(-0.00287 + x*(0.459 + x*(3.83 + x*(-6.80 + x*5.25)))); } void main( void ) { // Get the ray from the camera to the vertex, and its length (which is the far point of the ray passing through the atmosphere) vec3 v3FrontColor = vec3(0.0, 0.0, 0.0); vec3 v3Pos = normalize(gl_Vertex.xyz) * fOuterRadius; vec3 v3Ray = v3CameraPos - v3Pos; float fFar = length(v3Ray); v3Ray = normalize(v3Ray); // Calculate the ray's starting position, then calculate its scattering offset vec3 v3Start = v3CameraPos; float fHeight = length(v3Start); float fDepth = exp(fScaleOverScaleDepth * (fInnerRadius - fCameraHeight)); float fStartAngle = dot(v3Ray, v3Start) / fHeight; float fStartOffset = fDepth*scale(fStartAngle); // Initialize the scattering loop variables float fSampleLength = fFar / fSamples; float fScaledLength = fSampleLength * fScale; vec3 v3SampleRay = v3Ray * fSampleLength; vec3 v3SamplePoint = v3Start + v3SampleRay * 0.5; // Now loop through the sample rays for(int i=0; i<nSamples; i++) { float fHeight = length(v3SamplePoint); float fDepth = exp(fScaleOverScaleDepth * (fInnerRadius - fHeight)); float fLightAngle = dot(normalize(v3LightPos), v3SamplePoint) / fHeight; float fCameraAngle = dot(normalize(v3Ray), v3SamplePoint) / fHeight; float fScatter = (-fStartOffset + fDepth*( scale(fLightAngle) - scale(fCameraAngle)))/* 0.25f*/; vec3 v3Attenuate = exp(-fScatter * (v3InvWavelength * fKr4PI + fKm4PI)); v3FrontColor += v3Attenuate * (fDepth * fScaledLength); v3SamplePoint += v3SampleRay; } // Finally, scale the Mie and Rayleigh colors and set up the varying variables for the pixel shader vec4 newPos = vec4( (gl_Vertex.xyz + view_position.xyz), 1.0); gl_Position = gl_ModelViewProjectionMatrix * vec4(newPos.xyz, 1.0); gl_Position.z = gl_Position.w * 0.99999; c1 = vec4(v3FrontColor * fKmESun, 1.0); c0 = vec4(v3FrontColor * (v3InvWavelength * fKrESun), 1.0); v3Direction = v3CameraPos - v3Pos; } Fragment Shader: uniform vec3 v3LightPos; varying vec3 v3Direction; varying vec4 c0; varying vec4 c1; const float g =-0.90f; const float g2 = g * g; const float Exposure =2; void main(void){ float fCos = dot(normalize(v3LightPos), v3Direction) / length(v3Direction); float fMiePhase = 1.5 * ((1.0 - g2) / (2.0 + g2)) * (1.0 + fCos*fCos) / pow(1.0 + g2 - 2.0*g*fCos, 1.5); gl_FragColor = c0 + fMiePhase * c1; gl_FragColor.a = 1.0; }

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  • Add Trace methods to System.Diagnostics.TraceListner

    - by user200295
    I wrote a Log class derived from System.Diagnostics.TraceListener like so public class Log : TraceListener This acts as a wrapper to Log4Net and allows people to use System.Diagnostics Tracing like so Trace.Listeners.Clear(); Trace.Listeners.Add(new Log("MyProgram")); Trace.TraceInformation("Program Starting"); There is a request to add additional tracing levels then the default Trace ones (Error,Warning,Information) I want to have this added to the System.Diagnostics.Trace so it can be used like Trace.TraceVerbose("blah blah"); Trace.TraceAlert("Alert!"); Is there any way I can do this with an extension class? I tried public static class TraceListenerExtensions { public static void TraceVerbose(this Trace trace) {} } but nothing is being exposed on the trace instance being passed in :(

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  • How do i translate movement on the Canvas3D to movement in the virtual 3D world

    - by Coder
    My goal is to move a shape in the virtual world in such a way so that it ends up where the mouse pointer is on the canvas. What i have: -mouse position (x,y) on a Canvas3D object -Point3d object of where a pick ray starting from the Canvas3D viewport intersects with the first scene object. (point in 3D space of where i want to start the drag) What i want: -Some way to translate the Point3d's coordinates so that the initial point of intersection (the Point3d object) is always overlapping the the mouse position on the canvas (same as when i used the pick ray to determine what the user clicked on from the Canvas3D object). Thanks!

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  • How to investigate if opencl is possible for an algorithm

    - by Marnix
    I have a heavy-duty algorithm in C# that takes two large Bitmaps of about 10000x5000 and performs photo and ray collision operations on a 3D model to map photos on the 3D model. I would like to know if it is possible to convert such an algorithm to OpenCL to optimize parallel operations during the algorithm. But before asking you to go into the details of the algorithm, I would like to know how I can investigate if my algorithm is convertible to OpenCL. I am not experienced in OpenCL and I would like to know if it is worth it to get into it and learn how it works. Are there things I have to look for that will definitely not work on the graphics card? (for-loops, recursion) Update: My algorithm goes something like: foreach photo split the photo in 64x64 blocks foreach block cast a ray from the camera to the 3D model foreach triangle in 3D model perform raycheck

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  • Garbage Collection Java

    - by simion
    On the slides i am revising from it says the following; Live objects can be identified either by maintaining a count of the number of references to each object, or by tracing chains of references from the roots. Reference counting is expensive – it needs action every time a reference changes and it doesn’t spot cyclical structures, but it can reclaim space incrementally. Tracing involves identifying live objects only when you need to reclaim space – moving the cost from general access to the time at which the GC runs, typically only when you are out of memory. I understand the principles of why reference counting is expensive but do not understand what "doesn’t spot cyclical structures, but it can reclaim space incrementally." means. Could anyone help me out a little bit please? Thanks

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  • Garbage Collection in Java

    - by simion
    On the slides I am revising from it says the following: Live objects can be identified either by maintaining a count of the number of references to each object, or by tracing chains of references from the roots. Reference counting is expensive – it needs action every time a reference changes and it doesn’t spot cyclical structures, but it can reclaim space incrementally. Tracing involves identifying live objects only when you need to reclaim space – moving the cost from general access to the time at which the GC runs, typically only when you are out of memory. I understand the principles of why reference counting is expensive but do not understand what "doesn’t spot cyclical structures, but it can reclaim space incrementally." means. Could anyone help me out a little bit please? Thanks

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

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

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  • An XEvent a Day (1 of 31) – An Overview of Extended Events

    - by Jonathan Kehayias
    First introduced in SQL Server 2008, Extended Events provided a new mechanism for capturing information about events inside the Database Engine that was both highly performant and highly configurable. Designed from the ground up with performance as a primary focus, Extended Events may seem a bit odd at first look, especially when you compare it to SQL Trace. However, as you begin to work with Extended Events, you will most likely change how you think about tracing problems, and will find the power...(read more)

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  • Fail to install eclipse-cdt on ubuntu 11.10 for ARM panda board

    - by Jiangning
    I failed to install install eclipse-cdt on ubuntu 11.10 for ARM panda board with the command line below, sudo apt-get install eclipse-cdt Tracing the problem, I find the root cause is eclipse-rcp : Depends: libequinox-osgi-java (= 3.5.2-11ubuntu3) but 3.7.0-0ubuntu1 is to be installed Actually, I can't find this version of libequinox-osgi-java package at all in apt-get for ARM. So how to get it installed? Thanks, -Jiangning

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  • DTracing a PHPUnit Test: Looking at Functional Programming

    - by cj
    Here's a quick example of using DTrace Dynamic Tracing to work out what a PHP code base does. I was reading the article Functional Programming in PHP by Patkos Csaba and wondering how efficient this stype of programming is. I thought this would be a good time to fire up DTrace and see what is going on. Since DTrace is "always available" even in production machines (once PHP is compiled with --enable-dtrace), this was easy to do. I have Oracle Linux with the UEK3 kernel and PHP 5.5 with DTrace static probes enabled, as described in DTrace PHP Using Oracle Linux 'playground' Pre-Built Packages I installed the Functional Programming sample code and Sebastian Bergmann's PHPUnit. Although PHPUnit is included in the Functional Programming example, I found it easier to separately download and use its phar file: cd ~/Desktop wget -O master.zip https://github.com/tutsplus/functional-programming-in-php/archive/master.zip wget https://phar.phpunit.de/phpunit.phar unzip master.zip I created a DTrace D script functree.d: #pragma D option quiet self int indent; BEGIN { topfunc = $1; } php$target:::function-entry /copyinstr(arg0) == topfunc/ { self->follow = 1; } php$target:::function-entry /self->follow/ { self->indent += 2; printf("%*s %s%s%s\n", self->indent, "->", arg3?copyinstr(arg3):"", arg4?copyinstr(arg4):"", copyinstr(arg0)); } php$target:::function-return /self->follow/ { printf("%*s %s%s%s\n", self->indent, "<-", arg3?copyinstr(arg3):"", arg4?copyinstr(arg4):"", copyinstr(arg0)); self->indent -= 2; } php$target:::function-return /copyinstr(arg0) == topfunc/ { self->follow = 0; } This prints a PHP script function call tree starting from a given PHP function name. This name is passed as a parameter to DTrace, and assigned to the variable topfunc when the DTrace script starts. With this D script, choose a PHP function that isn't recursive, or modify the script to set self->follow = 0 only when all calls to that function have unwound. From looking at the sample FunSets.php code and its PHPUnit test driver FunSetsTest.php, I settled on one test function to trace: function testUnionContainsAllElements() { ... } I invoked DTrace to trace function calls invoked by this test with # dtrace -s ./functree.d -c 'php phpunit.phar \ /home/cjones/Desktop/functional-programming-in-php-master/FunSets/Tests/FunSetsTest.php' \ '"testUnionContainsAllElements"' The core of this command is a call to PHP to run PHPUnit on the FunSetsTest.php script. Outside that, DTrace is called and the PID of PHP is passed to the D script $target variable so the probes fire just for this invocation of PHP. Note the quoting around the PHP function name passed to DTrace. The parameter must have double quotes included so DTrace knows it is a string. The output is: PHPUnit 3.7.28 by Sebastian Bergmann. ......-> FunSetsTest::testUnionContainsAllElements -> FunSets::singletonSet <- FunSets::singletonSet -> FunSets::singletonSet <- FunSets::singletonSet -> FunSets::union <- FunSets::union -> FunSets::contains -> FunSets::{closure} -> FunSets::contains -> FunSets::{closure} <- FunSets::{closure} <- FunSets::contains <- FunSets::{closure} <- FunSets::contains -> PHPUnit_Framework_Assert::assertTrue -> PHPUnit_Framework_Assert::isTrue <- PHPUnit_Framework_Assert::isTrue -> PHPUnit_Framework_Assert::assertThat -> PHPUnit_Framework_Constraint::count <- PHPUnit_Framework_Constraint::count -> PHPUnit_Framework_Constraint::evaluate -> PHPUnit_Framework_Constraint_IsTrue::matches <- PHPUnit_Framework_Constraint_IsTrue::matches <- PHPUnit_Framework_Constraint::evaluate <- PHPUnit_Framework_Assert::assertThat <- PHPUnit_Framework_Assert::assertTrue -> FunSets::contains -> FunSets::{closure} -> FunSets::contains -> FunSets::{closure} <- FunSets::{closure} <- FunSets::contains -> FunSets::contains -> FunSets::{closure} <- FunSets::{closure} <- FunSets::contains <- FunSets::{closure} <- FunSets::contains -> PHPUnit_Framework_Assert::assertTrue -> PHPUnit_Framework_Assert::isTrue <- PHPUnit_Framework_Assert::isTrue -> PHPUnit_Framework_Assert::assertThat -> PHPUnit_Framework_Constraint::count <- PHPUnit_Framework_Constraint::count -> PHPUnit_Framework_Constraint::evaluate -> PHPUnit_Framework_Constraint_IsTrue::matches <- PHPUnit_Framework_Constraint_IsTrue::matches <- PHPUnit_Framework_Constraint::evaluate <- PHPUnit_Framework_Assert::assertThat <- PHPUnit_Framework_Assert::assertTrue -> FunSets::contains -> FunSets::{closure} -> FunSets::contains -> FunSets::{closure} <- FunSets::{closure} <- FunSets::contains -> FunSets::contains -> FunSets::{closure} <- FunSets::{closure} <- FunSets::contains <- FunSets::{closure} <- FunSets::contains -> PHPUnit_Framework_Assert::assertFalse -> PHPUnit_Framework_Assert::isFalse -> {closure} -> main <- main <- {closure} <- PHPUnit_Framework_Assert::isFalse -> PHPUnit_Framework_Assert::assertThat -> PHPUnit_Framework_Constraint::count <- PHPUnit_Framework_Constraint::count -> PHPUnit_Framework_Constraint::evaluate -> PHPUnit_Framework_Constraint_IsFalse::matches <- PHPUnit_Framework_Constraint_IsFalse::matches <- PHPUnit_Framework_Constraint::evaluate <- PHPUnit_Framework_Assert::assertThat <- PHPUnit_Framework_Assert::assertFalse <- FunSetsTest::testUnionContainsAllElements ... Time: 1.85 seconds, Memory: 3.75Mb OK (9 tests, 23 assertions) The periods correspond to the successful tests before and after (and from) the test I was tracing. You can see the function entry ("->") and return ("<-") points. Cross checking with the testUnionContainsAllElements() source code confirms the two singletonSet() calls, one union() call, two assertTrue() calls and finally an assertFalse() call. These assertions have a contains() call as a parameter, so contains() is called before the PHPUnit assertion functions are run. You can see contains() being called recursively, and how the closures are invoked. If you want to focus on the application logic and suppress the PHPUnit function trace, you could turn off tracing when assertions are being checked by adding D clauses checking the entry and exit of assertFalse() and assertTrue(). But if you want to see all of PHPUnit's code flow, you can modify the functree.d code that sets and unsets self-follow, and instead change it to toggle the variable in request-startup and request-shutdown probes: php$target:::request-startup { self->follow = 1 } php$target:::request-shutdown { self->follow = 0 } Be prepared for a large amount of output!

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