Modern C++ has base class features that can be used with other modern features of C++. The std::integral_constant is the base class for the C++ type traits in C++11, and in C++14, std::integral_constant gained an operator () overload to return the constant value. In this post, we explain what integral_constant and () operator are in C++14. What is integral_constant in C++? The std::integral_constant is the base class for the C++ type traits in header that wraps a static constant of specified type. The behavior in a code part that adds specializations for std::integral_constant is undefined. Here is the definition in header since C++11, template struct integral_constant; Here is a very simple example to how can we use std::integral_constant, in C++11 we can use ::value to retrieve its value, typedef std::integral_constant five; std::cout
Large language models (LLMs) are revolutionizing the way we interact with software by combining deep learning techniques with powerful computational resources. While this technology is exciting, many are also concerned about how LLMs can generate false, outdated, or problematic information, and how they sometimes even hallucinate (generating information that doesn’t exist) so convincingly. Thankfully, we can immediately put one rumor to rest. According to Alireza Goudarzi, senior researcher of machine learning (ML) for GitHub Copilot: “LLMs are not trained to reason. They’re not trying to understand science, literature, code, or anything else. They’re simply trained to predict the next token in the text.” Let’s dive into how LLMs come to do the unexpected, and why. This blog post will provide comprehensive insights into LLMs, including their training methods and ethical considerations. Our goal is to help you gain a better understanding of LLM capabilities and how they’ve learned to master language, seemingly, without reasoning. What are large language models? LLMs are AI systems that are trained on massive amounts of text data, allowing them to generate human-like responses and understand natural language in a way that traditional ML models can’t. “These models use advanced techniques from the field of deep learning, which involves training deep neural networks with many layers to learn complex patterns and relationships,” explains John Berryman, a senior researcher of ML on the GitHub Copilot team. What sets LLMs apart is their proficiency at generalizing and understanding context. They’re not limited to pre-defined rules or patterns, but instead learn from large amounts of data to develop their own understanding of language. This allows them to generate coherent and contextually appropriate responses to a wide range of prompts and queries. And while LLMs can be incredibly powerful and flexible tools because of this, the ML methods used to train them, and the quality—or limitations—of their training data, can also lead to occasional lapses in generating accurate, useful, and trustworthy information. Deep learning The advent of modern ML practices, such as deep learning, has been a game-changer when it comes to unlocking the potential of LLMs. Unlike the earliest language models that relied on predefined rules and patterns, deep learning allows these models to create natural language outputs in a more human-like way. “The entire discipline of deep learning and neural networks—which underlies all of this—is ‘how simple can we make the rule and get as close to the behavior of a human brain as possible?’” says Goudarzi. By using neural networks with many layers, deep learning enables LLMs to analyze and learn complex patterns and relationships in language data. This means that these models can generate coherent and contextually appropriate responses, even in the face of complex sentence structures, idiomatic expressions, and subtle nuances in language. While the initial pre-training equips LLMs with a broad language understanding, fine-tuning is where they become versatile and adaptable. “When developers want these models to perform specific tasks, they provide task descriptions and examples (few-shot learning) or task descriptions alone (zero-shot learning). The model then fine-tunes its pre-trained weights based on this information,” says Goudarzi. This process helps it adapt to the specific task while retaining the knowledge it gained from its extensive pre-training. But even with deep learning’s multiple layers and attention mechanisms enabling LLMs to generate human-like text, it can […]
vcpkg 2023.10.19 Release: Export for Manifests, Documentation Improvements, and More… Augustin Popa November 3rd, 20230 0 The 2023.10.19 release of the vcpkg package manager is available. This blog post summarizes changes from August 10th, 2023 to October 19th, 2023 for the Microsoft/vcpkg, Microsoft/vcpkg-tool, and Microsoft/vcpkg-docs GitHub repos. Some stats for this period: 53 new ports were added to the open-source registry. If you are unfamiliar with the term ‘port’, they are packages that are built from source and are typically C/C++ libraries. 729 updates were made to existing ports. As always, we validate each change to a port by building all other ports that depend on or are depended by the library that is being updated for our nine main triplets. There are now 2,318 total libraries available in the vcpkg public registry. 34 contributors submitted PRs, issues, or participated in discussions in the main repo. The main vcpkg repo has over 5,700 forks and 19,900 stars on GitHub. Key changes Notable changes for this release are summarized below. vcpkg export now supports manifest mode The vcpkg export command can be used to export built packages from the installed directory to a standalone SDK. A variety of formats are supported, including NuGet, a zip, or a raw directory. The SDK contains all prebuilt binaries for the selected packages, their transitive dependencies, and integration files such as CMake toolchain or MSBuild props/targets. This command is useful for developers who want to export their dependencies to a portable format for their end users to consume, when those end users do not have vcpkg. Now, this command is supported for manifest-based (vcpkg.json) projects. Summary of changes: vcpkg export in manifest mode exports everything in the vcpkg_installed directory In manifest mode, the export command emits an error and fails when port:triplet arguments are provided, as they are not allowed in manifest mode. Added a guard to exit with an error message when the installed directory is empty. Previously, it just failed silently. Made –output-dir mandatory in manifest mode. Documentation for vcpkg export in manifest mode PR: Microsoft/vcpkg-tool#1136 Implemented default triplet changes announced earlier this year In a previous blog post, we announced that we would be changing the default behavior for commands that accept a triplet as an option but are not provided one. This change is now live. The default triplet assumed is no longer always x86-windows but will instead use a triplet inferred from your CPU architecture and operating system. PR: Microsoft/vcpkg-tool#1180 Improvements to vcpkg help The documentation provided when running vcpkg help or vcpkg help has been updated. This should make it easier to explore vcpkg without having to go to the documentation on Microsoft Learn and also improves the autocompletion (Tab) experience for the tool. Below are some screenshots of the new experience. Before (left) and after (right) when running vcpkg help (or not providing any commands to vcpkg): Summary of changes: We now show a more complete list of available commands and options. Available commands now organized by category and sorted alphabetically. Added a link to our online vcpkg documentation. Cleaned up some of the wording. Before (left) and after (right) when running vcpkg help install: Summary of changes: Added synopsis describing what the command does. In some cases, added additional examples for different usage […]
Hello C++ Developers, Embarcadero and Whole Tomato developer teams are working hard on to release of RAD Studio 12, and it seems like we may (or not) see the early released version of the new C++ compiler before 2024. The new 64-bit Clang Toolchain in RAD Studio 12 may have a new bcc64x C++ compiler. The news is amazing. Before it comes, let’s keep learning some modern C++ features to heat up from now on. This week, we have 3 more modern C++ features that can be used in C++ Builder. The concurrency support library in modern C++ is designed to allow your programs to read and write data securely in thread operations allowing us to develop faster multi-thread code. There are differences between mutual exclusion (std::mutex) and shared mutex (std::shared_mutex) and in another post, we explain these. The tuple (std::tuple) was introduced in C++11 and improved in C++14. In the last post, we explain tuple addressing via type features that come with the C++14 standard. Our educational LearnCPlusPlus.org site has a broad selection of new and unique posts with examples suitable for everyone from beginners to professionals alike. It is growing well thanks to you, and we have many new readers, thanks to your support! The site features a treasure-trove of posts that are great for learning the features of modern C++ compilers with very simple explanations and examples. RAD Studio’s C++ Builder, Delphi, and their free community editions C++ Builder CE, and Delphi CE are powerful tools for modern application development. Table of Contents Do you want to know some news about C++ Builder 12? How to use modern C++ with C++ Builder? How to learn modern C++ for free using C++ Builder? Where I can I learn C++ and test these examples with a free C++ compiler? Do you want to know some news about C++ Builder 12? RAD Studio, C++ Builder 12 may come with a new C++ compiler that has 64bits Windows CLANG 15.x based compiler. If you want to discover what’s coming in the next RAD Studio 12. Secure your spot from this link now: https://ow.ly/NZFQ50PVL13 Some of the technical features are: Uses Clang 15 Uses LLVM’s lld as the linker Emits COFF64 object files (note this means Delphi can also emit COFF64 object files in 12.0: the compiler option “-jf:coff” is specified by our targets files when the “-JL” or “-JPHN[E]” options are specified) Emits PDB format debug info Uses the Itanium ABI (not Microsoft ABI) Uses LLVM’s libc++ STL Uses UCRT for the C runtime Uses a mix of LLVM and MinGW for the C++ runtime Targets Win64 Named bcc64x Here are more details about it, Win64 Clang Toolchains in RAD Studio 12 How to use modern C++ with C++ Builder? In modern C++, the concurrency support library is designed to solve read and write data securely in thread operations that allow us to develop faster multi-thread apps. This library includes built-in support for threads (std::thread), atomic operations (std::atomic), mutual exclusion (std::mutex), condition variables (std::condition_variable), and many other features. In C++14, in addition to mutex, there is a shared_mutex which is an instance of the class located in header. In the first post, we explain using shared mutexes locking in Modern C++. There are differences between mutual exclusion (std::mutex) which comes with C++11 and shared mutex (std::shared_mutex) which comes with C++14 standards. In the next post, we explain a frequently asked mutex question in modern C++, what are […]
Atlassian today added generative artificial intelligence (AI) capabilities to Jira Service Management, an IT service management (ITSM) platform built on top of Jira project management software already used widely by DevOps teams. Generative AI is at the core of a virtual agent that analyzes and understands intent, sentiment, context and profile information to personalize interactions. Based on the same natural language processing (NLP) engine that Atlassian is embedding across its portfolio, the virtual agent dynamically generates answers from sources such as knowledge base articles, onboarding guides and frequently asked questions (FAQs) documents. In addition, it can facilitate conversations with human experts any time additional expertise is required to respond to more complex inquiries. Atlassian is also extending the reach of Atlassian Intelligence, a generative AI solution launched earlier this year, to provide concise summaries of all conversations, knowledge base articles and other resolution paths recommended by previous agents that have handled similar issues. It will also help IT staff craft better responses and adjust their tone to be more professional or empathetic if needed. During setup, support teams can easily configure the virtual agent experiences to match how they deliver service without writing a single line of code. Edwin Wong, head of product for IT solutions at Atlassian, said these additions are part of a larger commitment Atlassian is making to unify the helpdesk experience. The company plans to leverage Atlassian Intelligence to coordinate routing of all employee requests to the right tools as it aggregates requests from multiple communications channels such as web portals, email, chat and from within third-party applications, he noted. The overall goal is to reduce the number of tickets generated by leveraging AI as much as possible to handle service requests in a way that costs less to implement and maintain, Wong said. In the longer term, Atlassian will also apply generative AI to enable organizations to automate IT asset management further, he added. There is little doubt at this juncture that AI will be pervasively applied across both ITSM and DevOps workflows. As those advances are made, it should also become easier to address issues that arrive either programmatically or by generating a ticket for a service request that is then processed by an ITSM platform such as Jira Service Management. Each organization will need to decide how quickly to incorporate AI into ITSM, but hopefully, the level of burnout experienced by IT personnel will be sharply reduced as more tasks are automated. Less clear is the impact AI will have on the size of IT teams required to provide those services, but for the foreseeable future, there will always be a need for some level of human supervision. In the meantime, IT teams should take an inventory of the processes that are likely to be automated by AI today with an eye toward restructuring teams as more tasks are automated. Ultimately, the goal should be to let machines handle the tasks they do best so humans can provide higher levels of service that deliver more value to the business.
C++11 introduced new forms of literals using modified syntax and semantics to provide User-Defined Literals (UDL) also known as Extensible Literals. While there was the ability to use them the standard library did not use any of them. In C++14, the commission added some standard literals. In this post, we explain user-defined literals operators and we explain some of these standard literals added in C++14. What are the user defined literal operators in C++? C++11 introduced new forms of literals using modified syntax and semantics in order to provide User-Defined Literals (UDL) also known as Extensible Literals. Using user-defined literals, user-defined classes can provide new literal syntax and they can be used with the operator “” to combine values with conversion operators. Here below, we explain how to use user-defined literals in C++. What are the standard user-defined literals in C++14? In C++14, we have some standard user-defined literal operators that comes with standard library. These are literals for basic strings, for chrono types, and for complex number types. We can access to these operators by: using namespace std::literals; using namespace std::string_literals; using namespace std::literals::string_literals; C++14 adds the following standard literals below, For the string types there is an operator”” s() for basic string, s : std::basic_string types for creating the various string types std::string, std::wstring, etc. here how we can use it with auto, auto str = “LearnCPlusPlus.org”s; // auto deduction to string Suffixes for std::chrono::duration values, h : hour type for the std::chrono::duration time intervals m : minute type for the std::chrono::duration time intervals s : second type for the std::chrono::duration time intervals ms : millisecond type for the std::chrono::duration time intervals ns : nanosecond type for the std::chrono::duration time intervals us : u.second type for the std::chrono::duration time intervals here how we can use them with auto, auto durh = 24h; // auto deduction to chrono::hours auto durm = 60min; // auto deduction to chrono::minutes auto durs = 120s; // auto deduction to chrono::seconds auto durms = 1000ms; // auto deduction to chrono::milliseconds auto durns = 2000ns; // auto deduction to chrono::nanoseconds Suffixes for complex number literals, if : imaginary number for the std::complex types i : imaginary number for the std::complex types il : imaginary number for the std::complex types here how we can use them with auto, auto zi = 5i; // auto deduction to complex auto zif = 7if; // auto deduction to complex auto zil = 9il; // auto deduction to complex there are more definitions. Is there a full example of how to use standard user-defined literals in C++14? Here is a full example about standard user-defined literals in C++. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 #include #include #include #include #include using namespace std::literals; using namespace std::string_literals; // using namespace std::literals::string_literals; int main() { auto str = “LearnCPlusPlus.org”s; // auto deduction to string auto durh = 24h; // auto deduction to chrono::hours auto durm = 60min; // auto deduction to chrono::minutes auto durs = 120s; // auto deduction to chrono::seconds auto durms = 1000ms; // auto deduction to chrono::milliseconds auto durns = 2000ns; // auto deduction to chrono::nanoseconds auto zi = 5i; // auto deduction to complex auto zif = 7if; // auto deduction to complex auto zil = 9il; // auto deduction to complex } For more information about the standard user-defined literals, please […]
Microsoft Visual C++ at CppCon 2023 Trip Report Sinem Akinci November 2nd, 20230 0 The Visual C++ team attended CppCon 2023, the largest in-person C++ conference, in Aurora, Colorado from October 2-6th. There were over 700 attendees from the C++ community, and we really enjoyed getting a chance to meet all of you and talk about your unique backgrounds and C++ experiences. Some of our team member’s talks are now available to watch on YouTube so that you can watch them even if you missed CppCon to learn the latest for our tooling and more: How Visual Studio Code Helps You Develop More Efficiently in C++ – Alexandra Kemper and Sinem Akinci – YouTube New in Visual Studio: CMake Debugger, Better Diagnostics, and Video Games – David Li & Mryam Girmay – YouTube Lifetime Safety in C++: Past, Present and Future – Gabor Horvath – CppCon 2023 – YouTube The venue was at the Gaylord Rockies this year. The Gaylord Rockies is a resort with a massive convention center and many restaurants to go check out. Somehow, it still felt small, as we were constantly running into familiar C++ faces and meeting them in different areas in the convention center. There really is no experience like it. The Microsoft Booth We had a chance to talk to customers at our Microsoft booth we had during the week, and it was great to meet to you all. It was a great learning experience seeing, in real time, what was affecting our users across a wide area of use cases. For example, we will inform the public more about our Windows Subsystem for Linux (WSL) support in Visual Studio through online videos and documentation and improve our VS Code setup process. Thank you to everyone who took the time to fill out our survey and talk to us. Our Talks What is a conference without the talks? The Visual C++ team at Microsoft gave several talks, and we highly recommend checking them out when they are available on YouTube: Lifetime Safety in C++ – Gabor Horvath New in Visual Studio: CMake Debugger, Better Diagnostics, and Video Games – David Li & Mryam Girmay Cooperative C++ Evolution: Towards a Typescript for C++ – Herb Sutter (Keynote) How Visual Studio Code Can Help You Develop More Efficiently in C++ – Alexandra Kemper & Sinem Akinci Regular, Revisited – Victor Ciura Getting Started with C++ – Michael Price [Herb Sutter’s Keynote on Cooperative C++ Evolution: Towards a Typescript for C++. Full house!] [Michael Price on Getting Started with C++, discussing the tools beginners can use to get started on their C++ journey] My Talk Mine and Alex’s joint talk on Visual Studio Code went great (despite slight technical difficulties ????). The turnout was really strong, and it was empowering to see so many people interested to learn about the latest features in VS Code. In our talk, we covered a variety of enhancements that our teams working on the C++ Tools and CMake Tools extensions have developed over the past year to help you all the way from getting started with C++ for the first time to working in your large C++ repositories. Many C++ users came up to us after to ask more questions about what was presented, specifically to learn more about GitHub […]
Hello C++ Developers, this week, we have 3 more modern C++ features that can be used in C++ Builder. In C++14 you can store string in strings using modern programming methods. In the first post, we explain how you can preserve the string format especially when we use a string in a string with /”. Containers are powerful data storage arrays in modern C++ and they are very useful for iterating and searching data with their amazing methods and properties. In another post today we explain what the containers in modern C++ are, their types, and their methods. In C++14, there is a new decltype that is used with the auto keyword, and in the last post pick, we explain how you can use it. Our educational LearnCPlusPlus.org site has a broad selection of new and unique posts with examples suitable for everyone from beginners to professionals alike. It is growing well thanks to you, and we have many new readers, thanks to your support! The site features a treasure-trove of posts that are great for learning the features of modern C++ compilers with very simple explanations and examples. RAD Studio’s C++ Builder, Delphi, and their free community editions C++ Builder CE, and Delphi CE are powerful tools for modern application development. Table of Contents Where I can I learn C++ and test these examples with a free C++ compiler? How to use modern C++ with C++ Builder? How to learn modern C++ for free using C++ Builder? Do you want to know some news about C++ Builder 12? Where I can I learn C++ and test these examples with a free C++ compiler? If you don’t know anything about C++ or the C++ Builder IDE, don’t worry, we have a lot of great, easy to understand examples on the LearnCPlusPlus.org website and they’re all completely free. Just visit this site and copy and paste any examples there into a new Console, VCL, or FMX project, depending on the type of post. We keep adding more C and C++ posts with sample code. In today’s round-up of recent posts on LearnCPlusPlus.org, we have new articles with very simple examples that can be used with: The free version of C++ Builder 11 CE Community Edition or a professional version of C++ Builder or free BCC32C C++ Compiler and BCC32X C++ Compiler or the free Dev-C++ Read the FAQ notes on the CE license and then simply fill out the form to download C++ Builder 11 CE. How to use modern C++ with C++ Builder? In development, sometimes we want to preserve the string format especially when we use a string in a string with /”. In C++14 and above, there is a std::quoted template that allows handling strings safely where they may contain spaces and special characters and it keeps their formatting intact. In the first post, we explain the std::quoted template, and how you can use it with in examples. Containers are powerful data storage arrays in modern C++ and they are very useful to iterate and search data with their amazing methods and properties. The C++ Standards library defines 4 container types. In the next post, we explain containers and types in modern C++. The auto keyword arrives with the new features of C++11 and the standards above. In C++14, there is a new decltype that is used with the auto keyword. […]
This blog post is based on a pre-release version of the RAD Studio software and it has been written with specific permission by Embarcadero. No feature is committed until the product GA release. RAD Studio 12 is just around the corner, and we have exciting news to share! In August, we ran an unusual webinar where we shared a behind-the-scenes look at some technology we’ve been working on for C++Builder and the C++ side of RAD Studio. One of the things we previewed was an upgraded Clang-based Win64 compiler – though not just an upgrade but some major technological improvements to core areas, with a new STL, a new linker, and more. It is a thorough rework of the entire toolchain with a strong eye to making the right decisions for quality and longevity. Table of Contents New Clang Platform standards High performance for the compiled code. Optimised runtimes Excellent language standards compatibility. Excellent quality in all areas, such as exception handling A robust STL. A linker that can handle anything Tech details Status Toolchains in version 12.0 Overall New Clang The C++ compiler is foundational to RAD Studio. Through the Clang & LLVM work, we make LLVM available to Delphi. And, of course, we need a modern, powerful C++ compiler to provide our C++ developers with the best source compatibility, libraries, app performance, and more. Our goals for the work are: Very high quality. A robust STL. A linker that can handle anything and any quantity you give it. Excellent quality in all areas, such as exception handling Excellent language standards compatibility. High performance for the compiled code. Optimised runtimes. Match platform standards as much as possible How are we meeting those? Let’s go in reverse order. Platform standards The new toolchain is based on Clang 15*. The previous toolchain used the ELF object file format, a primarily Unix/Linux format, for historical reasons that are actually (long story) related to Kylix. For this toolchain, we are moving to COFF, which is the standard object file format for Windows compilers of any compiled language. Similarly, we are using the PDB debug format, which again is the standard. While we are not officially supporting any third party tools, there are many tools developers use which understand COFF & PDB and we hope that by adhering to the platform norms, we open up the opportunity to use a wide variety of tools with your apps and C++Builder. [*] Clang 15 was current when this work started, and we are avoiding changing the wheels while the car is in motion. We plan to remain up to date and move forward with Clang itself in future. High performance for the compiled code. While we are aiming for correct compiled code behaviour above all else, we are also aiming for high performance. The new toolchain’s technology generates more optimized code, and allows additional optimisations that were not previously possible in future. Optimised runtimes A C++ toolchain has multiple layers: a C runtime (providing things like printing to a console or file IO), a C++ runtime (providing things like exception handling), and the STL (providing C++ library functions like standard IO, algorithms, collections, etc.) For our toolchain, we are replacing all three. Image showing three layers of the C++ runtime: standard library, C++ RTL, and C […]
The world of DevOps is like a labyrinth—filled with choices at every turn. Some paths lead to efficiency and success, while others may lead to unexpected challenges and delays. In the spirit of Halloween, let’s explore the tricks and treats of DevOps choices to ensure your team ends up with a bag full of treats rather than some nasty tricks. Version Control: Treats of Consistency, Tricks of Complexity Treat: Implementing a robust version control system is crucial for any DevOps team. Tools like Git provide a reliable way to track changes, collaborate on code and maintain a history of your project’s evolution. Trick: However, the complexity of these systems can lead to confusion and errors if not properly understood. Branching strategies, for instance, need to be clearly defined to avoid chaotic merges and lost work. Continuous Integration & Continuous Deployment (CI/CD): Speedy Treats, Tricky Configurations Treat: CI/CD pipelines automate the process of code integration, testing and deployment, speeding up release cycles and ensuring more reliable software. Trick: Setting up these pipelines can be complex and error-prone. Misconfigurations can lead to failed builds, delayed releases or even the deployment of buggy code to production. Containerization: The Sweetness of Isolation, Beware of the Overhead Treat: Containers provide isolated environments for applications, ensuring consistency across development, testing and production. Tools like Docker and Kubernetes have revolutionized application development and deployment. Trick: Containerization adds an additional layer of complexity to your infrastructure. Mismanagement of containers can lead to resource inefficiencies, and Kubernetes itself has a steep learning curve. Monitoring and Logging: The Treat of Visibility, The Trick of Overload Treat: Comprehensive monitoring and logging give teams visibility into system performance and behavior, enabling proactive issue resolution and performance optimization. Trick: The sheer volume of logs and metrics can be overwhelming. Without proper tools and strategies for filtering and analysis, important information can be lost in the noise. Infrastructure-as-Code (IaC): Sweet Automation, Sour Complexity Treat: IaC tools like Terraform and AWS CloudFormation allow teams to automate and version infrastructure setup, ensuring consistency and reducing manual errors. Trick: IaC scripts can become complex and difficult to maintain. Errors in these scripts can lead to misconfigured infrastructure, potential security issues and resource waste. Collaboration and Communication: Treats of Teamwork, Tricks of Misunderstanding Treat: DevOps emphasizes the importance of collaboration between development and operations teams, fostering a culture of shared responsibility and continuous improvement. Trick: Miscommunication and lack of alignment between teams can lead to inefficiencies, mistakes and a breakdown in the collaborative process. Security: The Unseen Specter Treat: DevSecOps enables a “shift left” on security, integrating security checks and practices early in the development life cycle, ensuring safer, more secure applications. Trick: But this integration requires continuous attention and maintenance. Outdated dependencies, misconfigured settings and inadequate security practices can leave your applications vulnerable, turning the unseen specter of security issues into a ghastly reality. What about you? What areas of DevOps are ripe for trick or treat this Halloween season? In the grand scheme, DevOps offers a treasure trove of benefits, from faster releases and improved collaboration to higher-quality software. However, it’s not without its challenges. Navigating the DevOps landscape requires a careful balance between embracing automation and maintaining control. By being aware of the potential tricks and focusing on the treats, teams can build efficient, reliable and […]
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