Pros & Cons of Zoom: Analysis of a Video Conferencing Software

AJ ALMENDINGER

glimpse into the future of Roblox

Our vision to bring the world together through play has never been more relevant than it is now. As our founder and CEO, David Baszucki (a.k.a. Builderman), mentioned in his keynote, more and more people are using Roblox to stay connected with their friends and loved ones. He hinted at a future where, with our automatic machine translation technology, Roblox will one day act as a universal translator, enabling people from different cultures and backgrounds to connect and learn from each other.
During his keynote, Builderman also elaborated upon our vision to build the Metaverse; the future of avatar creation on the platform (infinitely customizable avatars that allow any body, any clothing, and any animation to come together seamlessly); more personalized game discovery; and simulating large social gatherings (like concerts, graduations, conferences, etc.) with tens of thousands of participants all in one server. We’re still very early on in this journey, but if these past five months have shown us anything, it’s clear that there is a growing need for human co-experience platforms like Roblox that allow people to play, create, learn, work, and share experiences together in a safe, civil 3D immersive space.
Up next, our VP of Developer Relations, Matt Curtis (a.k.a. m4rrh3w), shared an update on all the things we’re doing to continue empowering developers to create innovative and exciting content through collaboration, support, and expertise. He also highlighted some of the impressive milestones our creator community has achieved since last year’s RDC. Here are a few key takeaways:
And lastly, our VP of Engineering, Technology, Adam Miller (a.k.a. rbadam), unveiled a myriad of cool and upcoming features developers will someday be able to sink their teeth into. We saw a glimpse of procedural skies, skinned meshes, more high-quality materials, new terrain types, more fonts in Studio, a new asset type for in-game videos, haptic feedback on mobile, real-time CSG operations, and many more awesome tools that will unlock the potential for even bigger, more immersive experiences on Roblox.

Vibin’

Despite the virtual setting, RDC just wouldn’t have been the same without any fun party activities and networking opportunities. So, we invited special guests DJ Hyper Potions and cyber mentalist Colin Cloud for some truly awesome, truly mind-bending entertainment. Yoga instructor Erin Gilmore also swung by to inspire attendees to get out of their chair and get their body moving. And of course, we even had virtual rooms dedicated to karaoke and head-to-head social games, like trivia and Pictionary.
Over on the networking side, Team Adopt Me, Red Manta, StyLiS Studios, and Summit Studios hosted a virtual booth for attendees to ask questions, submit resumes, and more. We also had a networking session where three participants would be randomly grouped together to get to know each other.

What does Roblox mean to you?

We all know how talented the Roblox community is from your creations. We’ve heard plenty of stories over the years about how Roblox has touched your lives, how you’ve made friendships, learned new skills, or simply found a place where you can be yourself. We wanted to hear more. So, we asked attendees: What does Roblox mean to you? How has Roblox connected you? How has Roblox changed your life? Then, over the course of RDC, we incorporated your responses into this awesome mural.
📷
Created by Alece Birnbach at Graphic Recording Studio

Knowledge is power

This year’s breakout sessions included presentations from Roblox developers and staff members on the latest game development strategies, a deep dive into the Roblox engine, learning how to animate with Blender, tools for working together in teams, building performant game worlds, and the new Creator Dashboard. Dr. Michael Rich, Associate Professor at Harvard Medical School and Physician at Boston Children’s Hospital, also led attendees through a discussion on mental health and how to best take care of you and your friends’ emotional well-being, especially now during these challenging times.
📷
Making the Dream Work with Teamwork (presented by Roblox developer Myzta)
In addition to our traditional Q&A panel with top product and engineering leaders at Roblox, we also held a special session with Builderman himself to answer the community’s biggest questions.
📷
Roblox Product and Engineering Q&A Panel

2020 Game Jam

The Game Jam is always one of our favorite events of RDC. It’s a chance for folks to come together, flex their development skills, and come up with wildly inventive game ideas that really push the boundaries of what’s possible on Roblox. We had over 60 submissions this year—a new RDC record.
Once again, teams of up to six people from around the world had less than 24 hours to conceptualize, design, and publish a game based on the theme “2020 Vision,” all while working remotely no less! To achieve such a feat is nothing short of awe-inspiring, but as always, our dev community was more than up for the challenge. I’ve got to say, these were some of the finest creations we’ve seen.
WINNERS
Best in Show: Shapescape Created By: GhettoMilkMan, dayzeedog, maplestick, theloudscream, Brick_man, ilyannna You awaken in a strange laboratory, seemingly with no way out. Using a pair of special glasses, players must solve a series of anamorphic puzzles and optical illusions to make their escape.
Excellence in Visual Art: agn●sia Created By: boatbomber, thisfall, Elttob An obby experience unlike any other, this game is all about seeing the world through a different lens. Reveal platforms by switching between different colored lenses and make your way to the end.
Most Creative Gameplay: Visions of a perspective reality Created By: Noble_Draconian and Spathi Sometimes all it takes is a change in perspective to solve challenges. By switching between 2D and 3D perspectives, players can maneuver around obstacles or find new ways to reach the end of each level.
Outstanding Use of Tech: The Eyes of Providence Created By: Quenty, Arch_Mage, AlgyLacey, xJennyBeanx, Zomebody, Crykee This action/strategy game comes with a unique VR twist. While teams fight to construct the superior monument, two VR players can support their minions by collecting resources and manipulating the map.
Best Use of Theme: Sticker Situation Created By: dragonfrosting and Yozoh Set in a mysterious art gallery, players must solve puzzles by manipulating the environment using a magic camera and stickers. Snap a photograph, place down a sticker, and see how it changes the world.
OTHER TOP PICKS
HONORABLE MENTIONS
For the rest of the 2020 Game Jam submissions, check out the list below:
20-20 Vision | 20/20 Vision | 2020 Vision, A Crazy Perspective | 2020 Vision: Nyon | A Wild Trip! | Acuity | Best Year Ever | Better Half | Bloxlabs | Climb Stairs to 2021 | Double Vision (Team hey apple) | Eyebrawl | Eyeworm Exam | FIRE 2020 | HACKED | Hyperspective | Lucid Scream | Mystery Mansion | New Years at the Museum | New Year’s Bash | Poor Vision | Predict 2020 | RBC News | Retrovertigo | Second Wave | see no evil | Sight Fight | Sight Stealers | Spectacles Struggle | Specter Spectrum | Survive 2020 | The Lost Chicken Leg | The Outbreak | The Spyglass | Time Heist | Tunnel Vision | Virtual RDC – The Story | Vision (Team Freepunk) | Vision (Team VIP People ####) | Vision Developers Conference 2020 | Vision Is Key | Vision Perspective | Vision Racer | Visions | Zepto
And last but not least, we wanted to give a special shout out to Starboard Studios. Though they didn’t quite make it on time for our judges, we just had to include Dave’s Vision for good measure. 📷
Thanks to everyone who participated in the Game Jam, and congrats to all those who took home the dub in each of our categories this year. As the winners of Best in Show, the developers of Shapescape will have their names forever engraved on the RDC Game Jam trophy back at Roblox HQ. Great work!

‘Til next year

And that about wraps up our coverage of the first-ever digital RDC. Thanks to all who attended! Before we go, we wanted to share a special “behind the scenes” video from the 2020 RDC photoshoot.
Check it out:
It was absolutely bonkers. Getting 350 of us all in one server was so much fun and really brought back the feeling of being together with everyone again. That being said, we can’t wait to see you all—for real this time—at RDC next year. It’s going to be well worth the wait. ‘Til we meet again, my friends.
© 2020 Roblox Corporation. All Rights Reserved.

Improving Simulation and Performance with an Advanced Physics Solver

August

05, 2020

by chefdeletat
PRODUCT & TECH
📷In mid-2015, Roblox unveiled a major upgrade to its physics engine: the Projected Gauss-Seidel (PGS) physics solver. For the first year, the new solver was optional and provided improved fidelity and greater performance compared to the previously used spring solver.
In 2016, we added support for a diverse set of new physics constraints, incentivizing developers to migrate to the new solver and extending the creative capabilities of the physics engine. Any new places used the PGS solver by default, with the option of reverting back to the classic solver.
We ironed out some stability issues associated with high mass differences and complex mechanisms by the introduction of the hybrid LDL-PGS solver in mid-2018. This made the old solver obsolete, and it was completely disabled in 2019, automatically migrating all places to the PGS.
In 2019, the performance was further improved using multi-threading that splits the simulation into jobs consisting of connected islands of simulating parts. We still had performance issues related to the LDL that we finally resolved in early 2020.
The physics engine is still being improved and optimized for performance, and we plan on adding new features for the foreseeable future.

Implementing the Laws of Physics

📷
The main objective of a physics engine is to simulate the motion of bodies in a virtual environment. In our physics engine, we care about bodies that are rigid, that collide and have constraints with each other.
A physics engine is organized into two phases: collision detection and solving. Collision detection finds intersections between geometries associated with the rigid bodies, generating appropriate collision information such as collision points, normals and penetration depths. Then a solver updates the motion of rigid bodies under the influence of the collisions that were detected and constraints that were provided by the user.
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The motion is the result of the solver interpreting the laws of physics, such as conservation of energy and momentum. But doing this 100% accurately is prohibitively expensive, and the trick to simulating it in real-time is to approximate to increase performance, as long as the result is physically realistic. As long as the basic laws of motion are maintained within a reasonable tolerance, this tradeoff is completely acceptable for a computer game simulation.

Taking Small Steps

The main idea of the physics engine is to discretize the motion using time-stepping. The equations of motion of constrained and unconstrained rigid bodies are very difficult to integrate directly and accurately. The discretization subdivides the motion into small time increments, where the equations are simplified and linearized making it possible to solve them approximately. This means that during each time step the motion of the relevant parts of rigid bodies that are involved in a constraint is linearly approximated.
📷📷
Although a linearized problem is easier to solve, it produces drift in a simulation containing non-linear behaviors, like rotational motion. Later we’ll see mitigation methods that help reduce the drift and make the simulation more plausible.

Solving

📷
Having linearized the equations of motion for a time step, we end up needing to solve a linear system or linear complementarity problem (LCP). These systems can be arbitrarily large and can still be quite expensive to solve exactly. Again the trick is to find an approximate solution using a faster method. A modern method to approximately solve an LCP with good convergence properties is the Projected Gauss-Seidel (PGS). It is an iterative method, meaning that with each iteration the approximate solution is brought closer to the true solution, and its final accuracy depends on the number of iterations.
📷
This animation shows how a PGS solver changes the positions of the bodies at each step of the iteration process, the objective being to find the positions that respect the ball and socket constraints while preserving the center of mass at each step (this is a type of positional solver used by the IK dragger). Although this example has a simple analytical solution, it’s a good demonstration of the idea behind the PGS. At each step, the solver fixes one of the constraints and lets the other be violated. After a few iterations, the bodies are very close to their correct positions. A characteristic of this method is how some rigid bodies seem to vibrate around their final position, especially when coupling interactions with heavier bodies. If we don’t do enough iterations, the yellow part might be left in a visibly invalid state where one of its two constraints is dramatically violated. This is called the high mass ratio problem, and it has been the bane of physics engines as it causes instabilities and explosions. If we do too many iterations, the solver becomes too slow, if we don’t it becomes unstable. Balancing the two sides has been a painful and long process.

Mitigation Strategies

📷A solver has two major sources of inaccuracies: time-stepping and iterative solving (there is also floating point drift but it’s minor compared to the first two). These inaccuracies introduce errors in the simulation causing it to drift from the correct path. Some of this drift is tolerable like slightly different velocities or energy loss, but some are not like instabilities, large energy gains or dislocated constraints.
Therefore a lot of the complexity in the solver comes from the implementation of methods to minimize the impact of computational inaccuracies. Our final implementation uses some traditional and some novel mitigation strategies:
  1. Warm starting: starting with the solution from a previous time-step to increase the convergence rate of the iterative solver
  2. Post-stabilization: reprojecting the system back to the constraint manifold to prevent constraint drift
  3. Regularization: adding compliance to the constraints ensuring a solution exists and is unique
  4. Pre-conditioning: using an exact solution to a linear subsystem, improving the stability of complex mechanisms
Strategies 1, 2 and 3 are pretty traditional, but 3 has been improved and perfected by us. Also, although 4 is not unheard of, we haven’t seen any practical implementation of it. We use an original factorization method for large sparse constraint matrices and a new efficient way of combining it with the PGS. The resulting implementation is only slightly slower compared to pure PGS but ensures that the linear system coming from equality constraints is solved exactly. Consequently, the equality constraints suffer only from drift coming from the time discretization. Details on our methods are contained in my GDC 2020 presentation. Currently, we are investigating direct methods applied to inequality constraints and collisions.

Getting More Details

Traditionally there are two mathematical models for articulated mechanisms: there are reduced coordinate methods spearheaded by Featherstone, that parametrize the degrees of freedom at each joint, and there are full coordinate methods that use a Lagrangian formulation.
We use the second formulation as it is less restrictive and requires much simpler mathematics and implementation.
The Roblox engine uses analytical methods to compute the dynamic response of constraints, as opposed to penalty methods that were used before. Analytics methods were initially introduced in Baraff 1989, where they are used to treat both equality and non-equality constraints in a consistent manner. Baraff observed that the contact model can be formulated using quadratic programming, and he provided a heuristic solution method (which is not the method we use in our solver).
Instead of using force-based formulation, we use an impulse-based formulation in velocity space, originally introduced by Mirtich-Canny 1995 and further improved by Stewart-Trinkle 1996, which unifies the treatment of different contact types and guarantees the existence of a solution for contacts with friction. At each timestep, the constraints and collisions are maintained by applying instantaneous changes in velocities due to constraint impulses. An excellent explanation of why impulse-based simulation is superior is contained in the GDC presentation of Catto 2014.
The frictionless contacts are modeled using a linear complementarity problem (LCP) as described in Baraff 1994. Friction is added as a non-linear projection onto the friction cone, interleaved with the iterations of the Projected Gauss-Seidel.
The numerical drift that introduces positional errors in the constraints is resolved using a post-stabilization technique using pseudo-velocities introduced by Cline-Pai 2003. It involves solving a second LCP in the position space, which projects the system back to the constraint manifold.
The LCPs are solved using a PGS / Impulse Solver popularized by Catto 2005 (also see Catto 2009). This method is iterative and considers each individual constraints in sequence and resolves it independently. Over many iterations, and in ideal conditions, the system converges to a global solution.
Additionally, high mass ratio issues in equality constraints are ironed out by preconditioning the PGS using the sparse LDL decomposition of the constraint matrix of equality constraints. Dense submatrices of the constraint matrix are sparsified using a method we call Body Splitting. This is similar to the LDL decomposition used in Baraff 1996, but allows more general mechanical systems, and solves the system in constraint space. For more information, you can see my GDC 2020 presentation.
The architecture of our solver follows the idea of Guendelman-Bridson-Fedkiw, where the velocity and position stepping are separated by the constraint resolution. Our time sequencing is:
  1. Advance velocities
  2. Constraint resolution in velocity space and position space
  3. Advance positions
This scheme has the advantage of integrating only valid velocities, and limiting latency in external force application but allowing a small amount of perceived constraint violation due to numerical drift.
An excellent reference for rigid body simulation is the book Erleben 2005 that was recently made freely available. You can find online lectures about physics-based animation, a blog by Nilson Souto on building a physics engine, a very good GDC presentation by Erin Catto on modern solver methods, and forums like the Bullet Physics Forum and GameDev which are excellent places to ask questions.

In Conclusion

The field of game physics simulation presents many interesting problems that are both exciting and challenging. There are opportunities to learn a substantial amount of cool mathematics and physics and to use modern optimizations techniques. It’s an area of game development that tightly marries mathematics, physics and software engineering.
Even if Roblox has a good rigid body physics engine, there are areas where it can be improved and optimized. Also, we are working on exciting new projects like fracturing, deformation, softbody, cloth, aerodynamics and water simulation.
Neither Roblox Corporation nor this blog endorses or supports any company or service. Also, no guarantees or promises are made regarding the accuracy, reliability or completeness of the information contained in this blog.
This blog post was originally published on the Roblox Tech Blog.
© 2020 Roblox Corporation. All Rights Reserved.

Using Clang to Minimize Global Variable Use

July

23, 2020

by RandomTruffle
PRODUCT & TECH
Every non-trivial program has at least some amount of global state, but too much can be a bad thing. In C++ (which constitutes close to 100% of Roblox’s engine code) this global state is initialized before main() and destroyed after returning from main(), and this happens in a mostly non-deterministic order. In addition to leading to confusing startup and shutdown semantics that are difficult to reason about (or change), it can also lead to severe instability.
Roblox code also creates a lot of long-running detached threads (threads which are never joined and just run until they decide to stop, which might be never). These two things together have a very serious negative interaction on shutdown, because long-running threads continue accessing the global state that is being destroyed. This can lead to elevated crash rates, test suite flakiness, and just general instability.
The first step to digging yourself out of a mess like this is to understand the extent of the problem, so in this post I’m going to talk about one technique you can use to gain visibility into your global startup flow. I’m also going to discuss how we are using this to improve stability across the entire Roblox game engine platform by decreasing our use of global variables.

Introducing -finstrument-functions

Nothing excites me more than learning about a new obscure compiler option that I’ve never had a use for before, so I was pretty happy when a colleague pointed me to this option in the Clang Command Line Reference. I’d never used it before, but it sounded very cool. The idea being that if we could get the compiler to tell us every time it entered and exited a function, we could filter this information through a symbolizer of some kind and generate a report of functions that a) occur before main(), and b) are the very first function in the call-stack (indicating it’s a global).
Unfortunately, the documentation basically just tells you that the option exists with no mention of how to use it or if it even actually does what it sounds like it does. There’s also two different options that sound similar to each other (-finstrument-functions and -finstrument-functions-after-inlining), and I still wasn’t entirely sure what the difference was. So I decided to throw up a quick sample on godbolt to see what happened, which you can see here. Note there are two assembly outputs for the same source listing. One uses the first option and the other uses the second option, and we can compare the assembly output to understand the differences. We can gather a few takeaways from this sample:
  1. The compiler is injecting calls to __cyg_profile_func_enter and __cyg_profile_func_exit inside of every function, inline or not.
  2. The only difference between the two options occurs at the call-site of an inline function.
  3. With -finstrument-functions, the instrumentation for the inlined function is inserted at the call-site, whereas with -finstrument-functions-after-inlining we only have instrumentation for the outer function. This means that when using-finstrument-functions-after-inlining you won’t be able to determine which functions are inlined and where.
Of course, this sounds exactly like what the documentation said it did, but sometimes you just need to look under the hood to convince yourself.
To put all of this another way, if we want to know about calls to inline functions in this trace we need to use -finstrument-functions because otherwise their instrumentation is silently removed by the compiler. Sadly, I was never able to get -finstrument-functions to work on a real example. I would always end up with linker errors deep in the Standard C++ Library which I was unable to figure out. My best guess is that inlining is often a heuristic, and this can somehow lead to subtle ODR (one-definition rule) violations when the optimizer makes different inlining decisions from different translation units. Luckily global constructors (which is what we care about) cannot possibly be inlined anyway, so this wasn’t a problem.
I suppose I should also mention that I still got tons of linker errors with -finstrument-functions-after-inlining as well, but I did figure those out. As best as I can tell, this option seems to imply –whole-archive linker semantics. Discussion of –whole-archive is outside the scope of this blog post, but suffice it to say that I fixed it by using linker groups (e.g. -Wl,–start-group and -Wl,–end-group) on the compiler command line. I was a bit surprised that we didn’t get these same linker errors without this option and still don’t totally understand why. If you happen to know why this option would change linker semantics, please let me know in the comments!

Implementing the Callback Hooks

If you’re astute, you may be wondering what in the world __cyg_profile_func_enter and __cyg_profile_func_exit are and why the program is even successfully linking in the first without giving undefined symbol reference errors, since the compiler is apparently trying to call some function we’ve never defined. Luckily, there are some options that allow us to see inside the linker’s algorithm so we can find out where it’s getting this symbol from to begin with. Specifically, -y should tell us how the linker is resolving . We’ll try it with a dummy program first and a symbol that we’ve defined ourselves, then we’ll try it with __cyg_profile_func_enter .
[email protected]:~/src/sandbox$ cat instr.cpp int main() {} [email protected]:~/src/sandbox$ clang++-9 -fuse-ld=lld -Wl,-y -Wl,main instr.cpp /usbin/../lib/gcc/x86_64-linux-gnu/crt1.o: reference to main /tmp/instr-5b6c60.o: definition of main
No surprises here. The C Runtime Library references main(), and our object file defines it. Now let’s see what happens with __cyg_profile_func_enter and -finstrument-functions-after-inlining.
[email protected]:~/src/sandbox$ clang++-9 -fuse-ld=lld -finstrument-functions-after-inlining -Wl,-y -Wl,__cyg_profile_func_enter instr.cpp /tmp/instr-8157b3.o: reference to __cyg_profile_func_enter /lib/x86_64-linux-gnu/libc.so.6: shared definition of __cyg_profile_func_enter
Now, we see that libc provides the definition, and our object file references it. Linking works a bit differently on Unix-y platforms than it does on Windows, but basically this means that if we define this function ourselves in our cpp file, the linker will just automatically prefer it over the shared library version. Working godbolt link without runtime output is here. So now you can kind of see where this is going, however there are still a couple of problems left to solve.
  1. We don’t want to do this for a full run of the program. We want to stop as soon as we reach main.
  2. We need a way to symbolize this trace.
The first problem is easy to solve. All we need to do is compare the address of the function being called to the address of main, and set a flag indicating we should stop tracing henceforth. (Note that taking the address of main is undefined behavior[1], but for our purposes it gets the job done, and we aren’t shipping this code, so ¯\_(ツ)_/¯). The second problem probably deserves a little more discussion though.

Symbolizing the Traces

In order to symbolize these traces, we need two things. First, we need to store the trace somewhere on persistent storage. We can’t expect to symbolize in real time with any kind of reasonable performance. You can write some C code to save the trace to some magic filename, or you can do what I did and just write it to stderr (this way you can pipe stderr to some file when you run it).
Second, and perhaps more importantly, for every address we need to write out the full path to the module the address belongs to. Your program loads many shared libraries, and in order to translate an address into a symbol, we have to know which shared library or executable the address actually belongs to. In addition, we have to be careful to write out the address of the symbol in the file on disk. When your program is running, the operating system could have loaded it anywhere in memory. And if we’re going to symbolize it after the fact we need to make sure we can still reference it after the information about where it was loaded in memory is lost. The linux function dladdr() gives us both pieces of information we need. A working godbolt sample with the exact implementation of our instrumentation hooks as they appear in our codebase can be found here.

Putting it All Together

Now that we have a file in this format saved on disk, all we need to do is symbolize the addresses. addr2line is one option, but I went with llvm-symbolizer as I find it more robust. I wrote a Python script to parse the file and symbolize each address, then print it in the same “visual” hierarchical format that the original output file is in. There are various options for filtering the resulting symbol list so that you can clean up the output to include only things that are interesting for your case. For example, I filtered out any globals that have boost:: in their name, because I can’t exactly go rewrite boost to not use global variables.
The script isn’t as simple as you would think, because simply crawling each line and symbolizing it would be unacceptably slow (when I tried this, it took over 2 hours before I finally killed the process). This is because the same address might appear thousands of times, and there’s no reason to run llvm-symbolizer against the same address multiple times. So there’s a lot of smarts in there to pre-process the address list and eliminate duplicates. I won’t discuss the implementation in more detail because it isn’t super interesting. But I’ll do even better and provide the source!
So after all of this, we can run any one of our internal targets to get the call tree, run it through the script, and then get output like this (actual output from a Roblox process, source file information removed):
excluded_symbols = [‘.\boost.*’]* excluded_modules = [‘/usr.\’]* /uslib/x86_64-linux-gnu/libLLVM-9.so.1: 140 unique addresses InterestingRobloxProcess: 38928 unique addresses /uslib/x86_64-linux-gnu/libstdc++.so.6: 1 unique addresses /uslib/x86_64-linux-gnu/libc++.so.1: 3 unique addresses Printing call tree with depth 2 for 29276 global variables. __cxx_global_var_init.5 (InterestingFile1.cpp:418:22) RBX::InterestingRobloxClass2::InterestingRobloxClass2() (InterestingFile2.cpp.:415:0) __cxx_global_var_init.19 (InterestingFile2.cpp:183:34) (anonymous namespace)::InterestingRobloxClass2::InterestingRobloxClass2() (InterestingFile2.cpp:171:0) __cxx_global_var_init.274 (InterestingFile3.cpp:2364:33) RBX::InterestingRobloxClass3::InterestingRobloxClass3()
So there you have it: the first half of the battle is over. I can run this script on every platform, compare results to understand what order our globals are actually initialized in in practice, then slowly migrate this code out of global initializers and into main where it can be deterministic and explicit.

Future Work

It occurred to me sometime after implementing this that we could make a general purpose profiling hook that exposed some public symbols (dllexport’ed if you speak Windows), and allowed a plugin module to hook into this dynamically. This plugin module could filter addresses using whatever arbitrary logic that it was interested in. One interesting use case I came up for this is that it could look up the debug information, check if the current address maps to the constructor of a function local static, and write out the address if so. This effectively allows us to gain a deeper understanding of the order in which our lazy statics are initialized. The possibilities are endless here.

Further Reading

If you’re interested in this kind of thing, I’ve collected a couple of my favorite references for this kind of topic.
  1. Various: The C++ Language Standard
  2. Matt Godbolt: The Bits Between the Bits: How We Get to main()
  3. Ryan O’Neill: Learning Linux Binary Analysis
  4. Linkers and Loaders: John R. Levine
  5. https://eel.is/c++draft/basic.exec#basic.start.main-3
Neither Roblox Corporation nor this blog endorses or supports any company or service. Also, no guarantees or promises are made regarding the accuracy, reliability or completeness of the information contained in this blog.
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Binary Options Trading System 2016 - Best Binary Option Trading Automated Software Robot Review

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