Who writes cluster-robust automation codes?
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For years, there has been a pervasive belief among the coding community that automation is the salvation of programming. And while automation certainly does save programming costs and allows for more efficient code reuse, it doesn’t replace the need for skilled programmers. Many of the top experts in this field are simply not able to write software because they have no experience with machine learning, AI, and automation. They’ve been around for decades, working with punched-card terminals and batch-processing machines. They’re not programmers
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I have worked with software engineers at IBM, TCS, and GE for the past 25 years. I was the lead author of many successful projects in R&D, product delivery, and support. Some of my work includes clustering algorithms for distributed systems, which enable parallel processing of data and tasks across multiple servers, maintaining high performance, resilience, and reliability for applications using distributed systems. In addition to clustering, I have also worked on fault tolerance, load balancing, and fault isolation algorithms, which are often used
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These days, software engineers are under immense pressure to deliver high-quality, high-performance software programs quickly. Software engineers work in teams, and there is a significant risk that defects will be introduced. In this situation, clustering is one of the most common approaches to solve this challenge. In fact, there are many clustering algorithms for solving the above problem. One of the widely used algorithms is called the “Robust AutoML”. However, I will present a paper published by a group of researchers, which outperformed this algorithm in real-world applications
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I have seen cluster-robust automation codes in various industries and fields of research. These are complex codes that can be complex even for highly skilled engineers. These codes are written using Python, which is a widely popular and widely used language for research, development, and automation. Firstly, I want to mention about Python syntax. find more information It is concise and easy to understand, and a well-written Python code makes the codebase more robust, scalable, and easier to maintain in the long run. Python also has built-in libraries and modules, which
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In the past, a cluster-robust automation code was written by an automation engineer with a lot of experience. I’m writing a cluster-robust automation code for a project. My automation code is the best. Let me describe my automation code. Automation Engineers spend much of their time in creating automation solutions for complicated processes. So, to make the processes easier for the engineers, they create automation solutions. But, I have to admit that a cluster-robust automation code is more complex than a standard autom
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“Who writes cluster-robust automation codes?” It wasn’t a catchy tagline but my actual question. But now that you have read the tagline, you will see why it’s a question worth asking. Let me explain. In an automated workflow, I’m using cluster-robust algorithms to optimize processes. Cluster-robust means the code doesn’t rely on individual process errors. I’m writing cluster-robust codes. Here’s my explanation. Software development is not just about code. It is about deliver
