What advanced programming skills do you use in system development?

In my view, Algorithms and Data Structures are the bedrock of successful system development. They are the keys to achieving optimal performance, scalability, and maintainability in software. Through meticulous algorithmic optimization and careful data structure selection, we can build efficient systems that meet the demands of modern software development. These skills empower us to tackle complex tasks with confidence, ensuring our systems are not only robust but also capable of scaling to meet future needs. In essence, Algorithms and Data Structures are the foundation upon which we construct reliable and high-performing software systems.

Our task: a data analytics platform for an e-commerce giant. To tackle vast data, we chose merge sort—its divide-and-conquer steps swiftly arranged datasets, preserving responsiveness. Security: Hashing protected sensitive data, while balanced binary trees organized our data kingdom, granting swift access. Scaling platform was an art. Profiling and refinement of algorithms and data structures unearthed hidden gems. Efficiency and scalability became our anthem. Our platform's triumph demonstrated that these skills were more than tools—they were the essence of code, shaping complexity, readability, and efficacy. In software, algorithms and data structures are the magicians, conjuring solutions, orchestrating success, and shaping the future.

Many often ask, even argue, “How crucial are algorithms and data structures, really?” The answer lies not in mastering just one, but in understanding the variety of options they present. Imagine owning only a hammer in your toolkit. While it’s efficient for nails, it’s not so useful when a screw appears. Similarly, knowing a single algorithm may get some jobs done, but there will always be scenarios where another approach could save time, money, or even open up innovative possibilities you never thought were feasible. Also,its not about knowing every single algorithm or data structure out there. It’s about having a broad understanding of what’s available. This empowers us to weigh the pros and cons and choose the one for the task at hand.

The most important thing in distributed/cloud system design is KISS. Components should be simple, small, and do hopefully one thing. That way, you don't get into complex debugging scenarios with an app that isn't all that debuggable (log/metric debug suffices). In the same vein of simplicity, ideally choose single threaded models - again when containers are cheap and multiprocessing is cheap, and wire times tend to be in msec, it's rare to truly need sub usec timing in coordinated activities. When you do, you do - fine, multithread. But it's the exception in modern architectures. Also consider when to use streaming processing architectures for data eng. It turns on whether or not your ontology of transforms is going to go broad.

We have two Fullstack projects where algorithm and DS choice played a pivotal role for performance optimization. Both in back end and front end for avoiding duplicacy we have used ordered Set and Enum data type and indexed hashing technique to reduce search time complexity. Besides that most of our sorting algorithms use insertion sort and merge sort for effective memory management and stability. Multi data type supported arrays holding objects sequenced with a pattern matching regex expression forms the strong foundation inside our code with parallel support of Material UI supported JS data structures. This assures readability, scalability, usability and maintainability. Object Relational mapping gives the added touch to persist data.

OOP is about objects. An object hides data and provides behavior. Unlike data structures, which provide data. That’s it. Everything else is about how to make objects work together! Think about it ??????

In system development, Object-Oriented Programming (OOP) is our North Star. OOP organizes data and behavior into modular objects. Classes define our objects, inheritance extends them, and polymorphism enhances flexibility. Encapsulation protects our code, revealing only what's necessary. Abstraction helps us focus on the big picture. Interfaces facilitate seamless integration, fostering interoperability. Singleton, Factory, Observer, Strategy, and Decorator patterns are our allies, solving complex design problems. In system development, OOP isn't just a tool—it's our language, weaving abstractions, bridging relationships, and crafting code for modularity, maintainability, and extensibility.

In my opinion, OOP has become a religion. And it is not surprising since that is what has been taught in schools for over 20 years. It works OK most of the time. Word of caution: OOP is neither a panacea for solving every problem nor even the best solution on occasion. It may be a good approach or not depending on the system requirements and design.

Considero la Programación Orientada a Objetos (POO) como un pilar fundamental. Esta metodología, que estructura sistemas complejos a través de clases y objetos, es crucial para un desarrollo eficiente y coherente. La herencia y el polimorfismo son aspectos que se valoran por su capacidad para reutilizar y flexibilizar el código. La encapsulación y la abstracción, por su parte, son esenciales para garantizar la seguridad y la claridad del dise?o. Además, patrones como Singleton, Factory, Observer, Strategy y Decorator son herramientas imprescindibles para enfrentarse a desafíos en la programación.

Object-Oriented Programming (OOP) initially appears theoretical but wields transformative power in coding. It enhances security and efficiency by optimizing memory usage. However, programmers often neglect OOP's key principles, Encapsulation and Abstraction, leaving their code vulnerable to security breaches. Embracing OOP and applying these principles strengthens code quality, fortifying it against threats while optimizing performance and resource utilization.

Around 2018, I read "Clojure for the Brave and True" and instantly fell in love. While working as a File Systems developer at HPE, I couldn't use Clojure directly, but it fundamentally shifted my perspective. Immutability's power in enabling simplicity resonated deeply, and I carried these ideas forward when I designed and implemented a financial rule engine for Loan-Front, a fintech startup at the time. This engine remains their core middleware, and the company thrives to this day. "Clojure" is definitely on my reread list, but I believe brushing up my machine learning skills first would be wise.

Our project was plagued by mutable data and tangled logic. Then, FP arrived. were our saviors. They brought clarity, making code behave predictably. Higher-order functions were our revelation. Lambda expressions and closures became our secret weapons. They unleashed concise, expressive, and reusable code snippets, empowering us to conquer complexity. With map, filter, and reduce, we composed symphonies of data transformation. Our code became testable, efficient, and a joy to work with. We combined FP with Object-Oriented Programming, creating a hybrid wonder. This fusion promoted modularity and parallelizability, a harmony of two paradigms. In our journey, FP was a revolution. It transformed chaos to elegance and complexity to clarity.

Utilizing functional programming techniques, such as higher-order functions, immutability, and pure functions, I create cleaner, more predictable, and maintainable code. Higher-order functions allow for greater abstraction and modularity, enabling flexible and reusable components. Immutability ensures data structures are not modified after creation, eliminating side effects and making the program state predictable and easier to debug. Pure functions produce consistent outputs for the same inputs and have no side effects, enhancing reliability and testability. These techniques reduce bugs and improve software quality, resulting in a more stable, readable, and maintainable codebase.

Sure FP is a blessing in disguise. Map , filter and reduce concepts brought a new dimension to our code. From jquery our projects transited to ReactJS which had extensive benefits including DOM manipulation, consistent routing, usage of lazy loading hooks and Lazy evaluating promises are really wonderful as these terms sound. The class and object coding added to this FP adds like a cheery on the top of the cake to shape the vanilla JS to really achieve the desired objective.

Functional Programming (FP) is a programming paradigm centered around the evaluation and manipulation of functions. Here are its key aspects: 1. Pure Functions 2. Immutability 3. First-Class and Higher-Order Functions 4. Recursion 5. Declarative Style 6. No Mutable State Popular languages that support functional programming concepts include Haskell, Lisp, Scala, Clojure, and JavaScript (with its functional programming features like higher-order functions and immutable data structures). Advantages of FP include: - Conciseness and Readability - Easier Parallelization - Predictability While not suitable for every scenario, understanding and applying functional programming concepts can lead to more robust, maintainable, and scalable.

Testing is what define a good solution, if you don't know that your system is still working after some changes you can't refactor, you can't change, you can't improve, so basically you need to take a great risk in order to change to the new business needs, because as a Teacher tells me the only constant in our business is change. Debugging is so important for a developer to understand a flow that I can't add anything, but debugging is just a tool we use when testing fails.

In our fast-paced world of system development, a pivotal moment emerged. We faced elusive bugs that disrupted our progress. Debugging became our beacon, aided by tools like debuggers and loggers. It led us to the root causes of errors, transforming chaos into clarity. Testing, too, played a vital role. We wielded automated tests, unit and integration frameworks, code coverage tools, and mock objects. These tools fortified our code, ensuring functionality, reliability, and security. Our journey wasn't just about fixing errors or meeting specs. Debugging and testing safeguarded our code's quality and fortified our system. In the realm of system development, they are the keepers of code integrity and the architects of a robust digital future.

At FanDuel we followed the data flowing to and forth to develop the microservices in Spring Boot. This allowed for rapid development of a working system. If it was broken we would collaberate by checking in the code and asking another contributor to take over the code. Unit testing was used to check the utility methods and Mockito was used to mock code passing in something then checking the transform to the output. If necessary data was passed back to test the return path. A fully tested system is essential to prevent the spread fo mistakes in future development.

Debugging and testing are crucial steps in software development. Debugging is the process of identifying and fixing errors or bugs in code, while testing involves systematically evaluating the software's functionality to ensure it meets the desired specifications. In debugging, developers use tools like debuggers, print statements, and logs to locate and understand the source of issues. They often employ techniques like code review and peer debugging to get fresh perspectives. Testing involves various levels like Unit Testing, Integration Testing, System Testing, Acceptance Testing etc

An essential part of system development! As we have started working Agile and thus releasing and delivering faster and more often to production environments and our customers, we see the impact of our software much faster and more often. The way we master our tools and grow our skills, the lesser negative impact we will have on our customers.

In our workplace, we embarked on a transformative journey—mastering version control and collaboration. Guided by Git and its companions, we choreographed our code's evolution. We tracked changes, synchronized efforts, and sculpted a code masterpiece. Best practices became our daily routine. Code conventions and meticulous documentation ensured clarity. Code quality metrics became our compass, leading us to code brilliance. Our journey wasn't just about managing code; it was about fostering unity, teamwork, and a culture of code excellence. In system development, version control and collaboration were more than skills—they were the architects of harmony, the enablers of teamwork, and the guarantors of code excellence.

Git is the version control that we are leveraging for our projects. We use a central repository.We have multiflavored application having two versions- web and mobile. Applications are deployed in the environments with code pulled from Git using a CI/CD automated Jenkins build pipeline in 5 flavors- DEV->UAT->PREPROD-> PRODUCTION and TRAINING. We have a Devops release tracking mechanism in place and use auto mail transponders to communicate of installations to respective stakeholders. ANDROID Playstore caters our mobile version Production releases.

Version control is a system that records changes to files over time, allowing multiple people to work on a project simultaneously. It provides a history of changes, the ability to revert to previous states, and facilitates collaboration and branching the system. The most commonly used version control systems are Git, SVN, and Mercurial. Collaboration in software development involves team members working together efficiently on the same project. It encompasses several aspects, including communication, teamwork, and sharing resources. For example:- Communication, Issue Tracking, Code Reviews, Collaborative Coding, Continuous Integration and Continuous Deployment (CI/CD pipelines), Documentation or Test cases etc.

Collaboration is vital for any product or project to success. It empowers us to track code changes, work seamlessly with other developers, and maintain code quality through practices like code conventions and documentation.

Using version control is essential in today's development landscape, given the numerous adjustments, support, and new features involved in software/web/mobile projects. I've experienced moments of making incorrect pushes, but it's possible to recover the correct version using a branch that contains the right version. Another advantage is that a new team member can download previous versions and understand the improvements made to the software. It prevents deploying the wrong application to production, as you can quickly roll back to the previous version and make adjustments. In summary, having version control brings many benefits.

We all have drive a car or use a computer, and we don't need to know how the computer does things, we just press a button and words appear, well with Frameworks and Library is the same, we just use them because a lot of people already test them and show us that it works, and if all fails you can change it, or overwrite it with yours.

Frameworks and libraries are essential components in software development that simplify and expedite the process of building applications. They provide pre-written, reusable code modules, tools, and structures that developers can solve common problems efficiently. Frameworks provide a structured blueprint and guidelines for building applications, while libraries offer specific, ready-made functions or modules to perform tasks. Both frameworks and libraries significantly accelerate the development process, improve code quality, and allow developers to focus on implementing unique features rather than dealing with low-level details. The choice between using a framework or a library depends on the project's complexity and requirements.

When using common frameworks and libraries it's also crucial to keep an eye for vulnerabilities and CVEs regarding them. As a vulnerability in a single one of them could lead to vulnerability in your product without you putting it there or even being aware of the said vulnerability.

I highly recommend learning how to use frameworks and libraries, as they greatly optimize the delivery of software/web/mobile stages or the entire project. However, before diving into using a framework or library, start by mastering the native programming language associated with these tools. This will enable you to effectively address any challenges that arise during implementation. If possible, creating your own framework or library can be very beneficial, providing a deep understanding and mastery of how they function.

Requirement Analysis: Getting this phase right sets the tone for the entire project. A clear understanding of what the system needs is achieved by: Data Modeling: Use an Entity-Relationship Diagram for a solid project foundation. It helps in understanding the complex database interactions. Prototyping: Use Python for a quick, functional prototype to simulate main features, turning theoretical plans into a tangible model for stakeholders. DSLs: Leverage Domain-Specific Languages to translate technical jargon into easy-to-understand terms, bridging the gap between tech teams and business stakeholders. NLP: Employ Natural Language Processing to sift through extensive requirements, highlighting key points and ensuring nothing is overlooked.

The most advanced programming skill is writing simple code that doesn't contain any surprises. Knowing when five lines of self-explanatory code is better than a 'clever' one-liner is a real skill. (The answer is almost always).

Thread pools, queues. Not really a programming skill, but only using threads and pools (efficiently considering the OS capabilities) you can execute the required procedures achieving performant solutions without creating bottlenecks on system level. Remember async is not a feature, but limitation.

The most important skill for system development is communication. In order to understand the problem you are solving you need to communicate effectively with stakeholders. And if you don't understand the problem and your stakeholders' perspectives it is harder design an effective adaptable long term solution for it. I successfully led a greenfield development project that had failed at least twice before, it only succeeded because I was able to communicate my understanding of, and how I would address, the concerns of key stakeholders who had sunk the prior attempts at writing this. Though to be fair my team had delivered some related wins that also helped my proposals get a fair hearing.

Aside from an actually good testing system, I think another thing that helps a lot to contribute to apps that are developed by many mates is to have a nicely implemented linting system. i.e. having most of the style rules enforced in pre-commit hooks (git FTW). Also, automate all that can be automated: linters, testing, coverage checks, deploy, and anything else that needs to be done "more than twice".