Rocky has a wide range of content to help users get the most out of the software. In this FAQ, we answer the Top 10 Rocky Content Frequently asked questions. Click here to learn more: https://lnkd.in/d3ddWztw #engineering #dem #particle #simulation
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🔄 The Importance of Reverse Engineering in Existing Software Products 🛠️ When working with an established software product, one of the most critical yet often overlooked practices is reverse engineering. Here's why it’s crucial: 🔍 Understanding the Legacy: Before making any changes, it's essential to fully grasp how the existing system works. Reverse engineering helps uncover the underlying architecture, design patterns, and code dependencies that might not be documented. 🛡️ Mitigating Risks: Reverse engineering allows us to identify potential pitfalls and legacy code issues that could break functionality if not handled carefully. It’s about knowing what you’re dealing with before diving into modifications. 🔧 Facilitating Innovation: By understanding the existing product in depth, we can more effectively integrate new features without disrupting the user experience. It ensures that the innovation we bring is built on a solid foundation. 🚀 Accelerating Development: Rather than starting from scratch, reverse engineering enables us to reuse and enhance what already works. This not only speeds up development but also maintains continuity with the product’s established strengths. 💡 Continuous Learning: For developers, reverse engineering is an invaluable learning tool. It exposes you to different coding styles, architectural decisions, and problem-solving approaches, enriching your own skill set. In a world where software evolves rapidly, reverse engineering is key to maintaining, improving, and future-proofing existing products. Embrace it as a strategic tool in your development arsenal! #SoftwareDevelopment #ReverseEngineering #LegacyCode #Innovation #ProductDevelopment #ContinuousLearning
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🌟 Welcome to my in-depth exploration of Text Blaze for prompt engineering! 🚀 Whether you're a Mac or Windows user, learn how Text Blaze can revolutionize your workflow with advanced prompt creation techniques. Discover how to effortlessly integrate complex prompts into your daily tasks, boosting productivity like never before. 💻 In this video, I guide you through Text Blaze's features, from basic structures to dynamic placeholders and AI-driven outputs. See firsthand how this tool serves as both a clipboard manager and prompt library, streamlining your work across different environments. 🔍 **What We'll Cover:** - Discovering the best ways to search for effective prompts - Building a comprehensive prompt library before the prompt engineering course 📚 - Exploring the software needed to streamline this process 🖥️ --- 👀 **In This Video:** - Initial attempts to capture the perfect prompts 🧐 - The "Aha!" moment when the right tool is found: Text Blaze 🎉 - Installation and testing on both web and desktop platforms 💻🖥️ - The decision-making process for business investments 💼 - Overcoming shortfalls and eliminating friction at work 🛠️ - Utilizing marketing templates and sending effective prompts 📤 - Easy updates and organization with Notion 📁 🔔 **Don't Forget to Like, Comment, and Subscribe for More AI Tips and Tricks!** 👍💬🔔 📲 **Follow Rifat on LinkedIn for More Updates:** [Add me on LinkedIn](https://lnkd.in/eHuwVYsi) Join me on this journey to mastering prompt engineering! Enhance your skills and efficiency with Text Blaze, and stay ahead in the realm of productivity. 🔍 **References:** - **Text Blaze:** Revolutionize your workflow with advanced prompt creation techniques. [Text Blaze](https://blaze.today) - **Connect with me on LinkedIn for more updates:** [Rifat Erdem Sahin](https://lnkd.in/eHuwVYsi)
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Navigating the Lifecycle: Software vs. Physical Products In the realm of product development, the lifecycle of a software product diverges significantly from that of a physical one. Unlike physical products, software evolves continuously, traversing through phases of conception, development, deployment, and maintenance in a perpetual loop. Software engineering encounters unique challenges due to this dynamic lifecycle. Unlike physical products with finite versions, software undergoes iterative updates, making predicting its lifecycle challenging. Additionally, software's intangible nature allows for easier modifications but also demands stringent quality control to prevent bugs and vulnerabilities. Furthermore, software products often face scalability issues, especially with rapidly growing user bases. Unlike physical products, which may require significant manufacturing adjustments for scaling, software can adapt more flexibly but may encounter performance bottlenecks. Maintenance presents another hurdle, as software requires ongoing updates to adapt to evolving technologies and user needs. This constant upkeep demands significant resources and attention, unlike physical products that may have more predictable maintenance schedules. Despite these challenges, the dynamic nature of software allows for rapid innovation and adaptation, enabling it to stay relevant in an ever-changing market landscape. Understanding and navigating these unique aspects of the software lifecycle are essential for software engineers to create successful and sustainable products in today's digital age.
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Application-Level Tracing: The Good, the Bad, and the Alternative https://lnkd.in/dTHCRFp2 The Sailormen's Legacy: A "Trace" of the Past By the late 16th century, sailors were measuring speed with a chip log — a method crucial for navigation. Knots were tied at regular intervals in a rope, with one end attached to a pie-slice-shaped piece of wood ("chip") and flung behind the vessel. The rope played freely as the ship traveled for a fixed amount of time, which was measured using an hourglass. The number of knots that passed over the stern was counted to determine the ship's speed, with one knot equaling one nautical mile an hour. Thus, a ship going at 15 knots could traverse 15 nautical miles in an hour. Records of these measurements were kept in a logbook, which was used to calculate the ship's speed over a given period. This logbook was also used to record the ship's course, weather conditions, and other relevant information. The term "log" was derived from this practice, and it has since been used in various contexts to refer to a record of events or activities. In software engineering, the principle of logging has been refined and expanded to include “traces." In software development, tracing represents a dynamic method of observing, debugging, and recording activities within an application, providing a more detailed, sometimes interactive, insight than traditional logging.
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Should software prototypes include automated tests? 🤔 As with most software engineering decisions, it depends. But on what exactly? Let’s break it down: 1️⃣ Mission-criticality: If lives depend on it—think self-driving cars or elevators—automated tests are non-negotiable. Even for a prototype, tests help reduce faults and create a baseline spec that evolves as the project matures. The higher the stakes, the stronger the case for tests. 2️⃣ Time to market: Prototypes often need to be delivered at lightning speed. If you're building something purely for a quick demo or proof-of-concept, structured manual testing might suffice. Just remember—this is fine only if it’s never going to touch production workloads. 3️⃣ Future plans: Ask yourself: Will this code be reused? Will it evolve into the final product? Will a larger team maintain it later? If the answer is yes, you’re better off including tests now. Adding them later is always harder. 4️⃣ Scrap or scale: If the prototype is a throwaway—meant to be replaced by something new—automated tests may not be necessary. But if the goal is to refine and scale, even minimal test coverage can save you from future headaches. My Take 🎯 Personally, I rarely skip writing tests. Even in prototypes, they provide clarity, confidence, and a safety net. But ultimately, the decision depends on your project goals, timelines, and constraints. Prototyping is both an art and a science. The best approach is the one that balances speed with long-term value. What’s your view? Are automated tests a must for prototypes, or do you skip them to move fast? Let me know in the comments! 🚀 #SoftwareEngineering #Prototyping #BestPractices
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💡 Seeking solutions for working on your complex #EmbeddedSystems projects? 💁We have a knowledge source article that may be right for you. 🆕How to integrate multiple SCADE models into one executable #SafetyCriticalSystems #embeddedsoftware
How to integrate multiple SCADE models into one executable - Ansys Knowledge
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💡 Seeking solutions for working on your complex #EmbeddedSystems projects? 💁We have a knowledge source article that may be right for you. 🆕How to integrate multiple SCADE models into one executable #SafetyCriticalSystems #embeddedsoftware
How to integrate multiple SCADE models into one executable - Ansys Knowledge
ansyskm.ansys.com
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𝐃𝐨𝐜𝐤𝐞𝐫 𝐂𝐨𝐦𝐦𝐚𝐧𝐝𝐬 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 🐳 As Docker gains traction, mastering essential commands becomes crucial for developers and ops engineers alike. This cheat sheet highlights key Docker commands for efficient management: 𝐃𝐞𝐯𝐎𝐩𝐬 𝐅𝐑𝐄𝐄 𝐖𝐞𝐛𝐢𝐧𝐚𝐫 & 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 https://lnkd.in/dmB4EgdR 𝐈𝐦𝐚𝐠𝐞𝐬: docker build: Create an image from a Dockerfile. docker pull: Fetch an image from a registry. docker push: Upload an image to a registry. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬: docker run: Start a new container based on an image. docker start: Start one or more stopped containers. docker stop: Stop one or more running containers. docker restart: Restart one or more containers. docker logs: View logs from a container. 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬: docker network create: Create a new network. docker network connect: Attach a container to a network. 𝐕𝐨𝐥𝐮𝐦𝐞𝐬: docker volume create: Create a new volume for persisting data. 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬: docker service create: Deploy a new service. docker service logs: Fetch logs of a service. 𝐂𝐥𝐞𝐚𝐧𝐮𝐩: docker system prune: Remove unused resources from the Docker environment. With these commands, you can: Build and share container images effortlessly. Manage running containers with ease. Establish networks and persist data using volumes. Define and scale services across multiple containers seamlessly. Keep your Docker environment clean by removing unused resources efficiently. Follow Omkar Srivastava for more content. PS- I shared my Knowledge which is totally based out of my personal opinion & have no link with my employers like Microsoft, Autodesk etc..
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Imagine a world where your software heals itself, much like our own bodies recover from a cold. Well, now it's a reality due to a Self-Healing Code, a groundbreaking technology that uses AI and ML to detect, diagnose, and repair software issues automatically. How to implement a Self-Healing Code? 1️⃣ Implement monitoring tools to continuously track software health, creating alerts for potential issues. 2️⃣ Use ML algorithms to analyze alerts, learning from historical data for accurate error diagnosis. 3️⃣ Upon issue identification, enable the system to implement repairs autonomously - restarting components, applying patches, or modifying code parameters. 4️⃣ Seamlessly incorporate self-healing mechanisms into your CI/CD pipelines, ensuring these capabilities are integral to your software systems. 5️⃣ Use an Internal Development Platform to optimize tech workflow and enhance developer experience, investing in productivity and uninterrupted software operation. What tools might you need? Kubernetes, Spring Boot, Prometheus, Transformatic, and similar tools allow you to implement self-healing strategies effectively. Have you ever thought of implementing self-healing code in your organization?
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Navigating Software vs. Physical Products' Lifecycle. The process of developing software products is different from physical products. Physical products go through stages like design, production, distribution, and disposal, which have clear milestones and schedules. On the other hand, software products are more dynamic. They go through cycles of development, testing, deployment, and enhancements, continuously adapting to changing requirements and technology. Software engineers face the challenge of managing these iterative cycles efficiently. Unlike physical products, software can be easily changed after release, so engineers need to continuously maintain and update it to ensure functionality and security. They must be agile and flexible, responding quickly to user feedback and emerging trends. Scalability is another challenge for software products. As user populations grow and technology advances, engineers need to design systems that can handle increased demands without sacrificing performance or reliability. Quality assurance is also different for software products. Unlike physical products, software flaws may not be immediately apparent, so comprehensive testing and robust debugging procedures are necessary.
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