Velocity, A Managed Services Company offers a comprehensive suite of technology solutions and support services. Let our team of experts build the perfect IT solution for your business.

Velocity - Managed Solutions Provider - IT Solutions & Support

Velocity Global lets you hire, pay, and manage talent in 185+ countries. Simplify global HR and manage global teams with our best-in-class technology and expertise.

Global HR Platform for Distributed Teams | Velocity Global

Velocity, A Managed Solutions Company | 2,492 followers on LinkedIn. Technology solutions and service provider of voice, data, and network connectivity for multi-location enterprises. | Founded in 2005, Velocity is a technology managed solution provider for voice, data, wi-fi, POTS IN A BOX®, ...

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Velocity Companies provides a full spectrum of commercial and residential real estate services. Our firm is built to service our clients’ biggest challenges. Through our industry expertise, market awareness, opportunity sourcing, and key financial and community relationships, our clients ...

The Velocity Companies – A Real Estate Development Company

Velocity Solutions industry-leading platform uses machine-led intelligence that delivers powerful analytics and drives revenue, loans, account holder engagement and non-interest income to our client financial institutions.

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Velocity Global helps you effortlessly hire and onboard talent, no matter where they are. Meet our team and learn how we simplify work anywhere.

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With Velocity you can develop locally in your IDE, build, run, and debug directly on your cloud. Make changes and debug services that are running in complex, Kubernetes-based environments straight from your favorite IDE.

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Navisite today announced that it has acquired Velocity Technology Solutions, Inc. (“Velocity”), a global cloud managed service provider (MSP).

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Founded in 2014 on the principle ... asset, Velocity deploys cutting edge technologies and human experts to transform how high performance people discover and enjoy their world. We help our members do and be more in the digital age. ‍ Backed by $28 million in venture capital, we are one of the world’s fastest growing companies according ...

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Velocity Clinical Research is the world’s leading organization of fully integrated research sites. The company partners with pharmaceutical and biotechnology companies to research new drugs, medical devices, and diagnostics that could improve human health and wellbeing.

Velocity Clinical Research - Clinical Trial Site Organization

We help high performance people unlock the vast potential of their lives in the digital age. Welcome to concierge, reimagined.

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Founded in 2004, Velocity Financial is now recognized as a market leader in the origination and management of investor real estate loans and serves over 2,500 independent mortgage brokers in 46 states. Our strong brand recognition among mortgage brokers, proprietary technology, vertically ...

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Velocity Specialty Insurance Company (“Velocity Specialty”) is an AM Best (A-) rated E&amp;S Carrier writing middle market and small to medium business risks in catastrophe exposed areas through brokers, agents, and Velocity Risk Underwriters, LLC (“Velocity Risk”). Velocity Risk also acts ...

Velocity Specialty

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Velocity offers revenue based financing to D2C and eCommerce brands in India. Get flexible growth capital upto Rs.3 Crore for your business in just 7 days. Apply today!

Velocity - India’s Largest Revenue Based Financing Platform

The Velocity Company has been helping small businesses succeed since 2002 and has expanded to become the industry leader in small business solutions, media, and events. Assisting over 20,000 small businesses since our inception, we know the needs of Main Street America.

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However, financing for these firms ... economy companies. Estimates say that less than 3 per cent of digital-first businesses in India have secured venture capital, and an even smaller fraction, less than 0.5 per cent, have opted for venture debt. And that&#x27;s precisely what Abhiroop Medhekar, Atul K., and Saurav Swaroop wanted to address: the gap between the funding requirements of new-age businesses and finance availability. And so the idea for Velocity was ...

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Velocity is super amazing. Great customer service, and a fantastic team to ensure everything is taken care of. Amber is absolutely wonderful to work with and makes things simple! Would recommend Velocity to all companies looking for Delivery services!

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Velocity.Partners is an industry agnostic Venture Capital fund. Our mission is to fuel Greek entrepreneurs around the globe build world-class technology companies.

Velocity.Partners Venture Capital

Peter Thiel’s Valar Ventures has doubled down its bet on Velocity, which operates a revenue-based financing platform for e-commerce and direct-to-consumer

Velocity, a revenue-based financing platform in India, raises $20 ...

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Velocity delivers a streamlined, single-source approach to managed services for over 15 years – continually earning the trust of its growing client base in the retail, hospitality and motion picture industries. With an in-house team of seasoned software development and engineering experts and numerous hardware and software design and utility patents, Velocity offers highly customized, customer-focused and best-in-class solutions, by integrating the latest technologies available into all its product offerings. Based in Holland, Ohio, right outside of Toledo, and founded in 2005, Velocity is a privately held company with approximately 500 employees. The company has nine redundant data centers, more than 5,500 certified technicians throughout the U.S., and 450 carrier agreements and is a CLEC in all 50 states. Further information can be found at www.velocitymsc.com.

Velocity

By Professional Scrum Trainer, , ILLIA Pavlichenko Scrum.org In this article, I will discuss the dangerous dynamic that can arise when a Product Owner, Scrum Master, or the management of an organization focuses a Development Team on velocity. What does velocity refer to? The concept of velocity signifies: The speed at which a Development Team converts Product Backlog Items into a Product Increment that is RELEASABLE. Pay particular attention to the highlighted word. Feature velocity is applicable when a Development Team can deliver an Increment that is releasable at least once per Sprint. In this case, Done = DoD = releasable. Awesome! But even in this case velocity does not show: Whether the client’s problem was resolved. Whether team is working on the highest priority problems. Amount of value delivered. Level of client satisfaction. Velocity only shows that the team was busy with something. But is this an accurate measure of the success of the products and services? Do the clients value products based on how busy company’s staff are? To put it another way, Velocity reflects the volume of a Development Team’s output. Unfortunately, this is not enough for the creation of successful products and services. The feature velocity of component teams = 0 Component teams have the most stable feature velocity. Because it always equals zero. Component teams are by definition not able to convert Product Backlog Items into value for a client. At a minimum they need integration with other component teams. When a team has Undone work In my opinion, the most dangerous dynamic arises in cases where a Development Team is not capable of generating a Product Increment that is releasable each Sprint. This means that Done = DoD + Undone and team optimizes just the part of the whole flow. Let us examine a system diagram that shows the link between the strength of DoD and organizational agility. The stronger the DoD, the smaller Undone work in the Sprint. Undone work limits the team regarding the number of potential releases, and, as a result, also regarding the amount of feedback that can be received from the market. The more feedback, the more decisions can be made by the Product Owner on the re-ordering of a Product Backlog. That could be called organizational agility — being able to quickly change the direction of a Product’s development. This may prompt a Scrum Team to undertake additional improvements to create an even stronger and more exhaustive DoD. d By strengthening the DoD, velocity decreases an becomes real How is the strengthening of a DoD reflected in velocity? The velocity will decrease at least in the short term. But this is not a problem if the goal is flow optimization (shortest Lead Time), learning and agility. Velocity decreases and becomes more real! But how likely is it that a Development Team would strengthen the DoD, if they know that team effectiveness is evaluated according to the velocity? My answer is unlikely. Focus on velocity keeps the team away from strengthening their DoD. As a result, that inhibits feedback from market, learning and agility. Focusing on velocity inhibits organizational agility. When I was a young and an inexperienced Scrum Master many years ago, I focused my teams on velocity excessively, which reduced their agility and increased the amount of Undone work. Nowadays, my advice to Scrum Masters who are just starting out goes something like this: Forget about velocity, if your team cannot produce an increment that is releasable at least every Sprint. Focus on strengthening your DoD first. What should we measure then? I recommend focusing on metrics that show the ability to deliver actual value to the market and satisfy client’s needs. For example, Scrum.org has developed framework , and is offering a range of metrics that shows: Evidence-Based Management A team’s ability to create value in the long term The speed at which value is generated (Time 2 Market). How much actual value is delivered to the market. n In conclusio I would like to repeat once more the fundamental idea that I want to convey with this article. The basic idea of a Scrum is to create an increment that is releasable at least every Sprint. If your team is already at that stage, then the concept of velocity is useful and genuinely demonstrates the speed at which a team converts Product Backlog Item elements into an increment. If not, please focus on strengthening Definition of Done (DoD) and flow optimization. The Article’s Main Ideas Velocity denotes the speed at which a Development Team converts Product Backlog Items into a Product Increment that is releasable. Velocity does not show whether clients’ problems are being resolved, nor whether value is being delivered, as reflects volume of output. Velocity only shows that a team was busy with something. The feature velocity of component teams is always zero. When team focuses on velocity and has Undone, it is unlikely they would strengthen the DoD. Focusing on velocity inhibits organizational agility. Focus on the value that is actually delivered to the market. Scrum ON! Originally published at agilix.nl on February 15, 2019.

Why focus on Velocity inhibits Agility

I don’t know about you — but when you talk about stocks, or markets, or funds — the general rule of thumb is: Past performance is not an indicator of future outcomes. Have you noticed that is software engineering, we tend to this advice? We tend to use our to our and our . We like to look at to determine what we can achieve within the . Why do we ignore this commonly accepted rule of thumb from finance? Are humans and our efforts really more predictable than a market? I don’t think so — but I’ll dig deeper. ignore current velocity calculate next velocity future velocities past performance next sprint/quarter/year Recording Velocity One of the things you’ll find most “ ” teams doing is recording . If it’s not the team, it’ll be the . It’s their job to give some security to a business and be able to say what they think they can while . Velocity is normally (from experience) regarded as the number of your team can get “ ” in a sprint. Basically, you record this over time to get to a point where you can predict what the deal will be able to achieve next sprint (and beyond). agile velocity PO (Product Owner) achieve minimizing risk story points done P.S. I put done in quotes because every team’s definition of done is different. Your team needs to figure this out for yourself. Some previous definition of done’s I’ve had are: Merged to master. QA tested. Deployed to live. Development finished. Story points? Story points are of the required for a story. They should be associated with a . Obviously, there are to every rule. When you’re first estimating, you’ll probably end up using . But it should be a direct conversion. Generally, I’ve used T-Shirt size estimates and sometimes they have numbers associated with those sizes. You add up all your story points done and that will give you the velocity for that week. very rough estimates effort never time exceptions days not one-to-one XS, S, M, L (after large, the stories should be broken up), XL, XXL, XXXL etc. 1, 2, 3, 5, 7, 13, etc. Is Velocity Meaningful? Normally, when a member joins a team (or leaves), it’ll probably take around for velocity to . Why’s that? Because it takes a time for a team to build and to measure their performance accurately for their products. So, while you can record velocity, it probably until your team builds the trust. That said, it is good to keep at it during this first six months to build up the trust in the numbers. But can you ever trust the numbers completely? They’re just rough guides remember. Some stories might have hidden complexity. Over time, your team will figure this out and your estimates will improve. 6 months stabilize long trust won’t mean anything Using Velocity — what does it mean? You can’t compare two teams’ velocities. It just won’t work. One team may and one team may . will have for the teams. So why would you even use them? In my team at Agoda, rather than the PO (Product Owner) say what will be completed in a quarter to management, we work the PO to determine our past quarter’s velocity and can use that to give an of what we’ll get done next quarter. This means that you have ample stories in the backlog estimated. underestimate overestimate Story points different meanings with approximation Now, this does not mean that you’ll work day and night to complete what you committed to. No. This means that you can manage expectations of management and the team. PO’s are always coming up with ideas and changing plans. Guess what? You can (based on your estimates) stories out of your commitments if your PO changes plans all the time. You can say “if you add this story — it will probably remove the bottom two from the quarterly goals. Are you okay with that?”. The PO will most likely answer yes and you aren’t stuck with unmanageable goals. kick To Sum it All Up is a funny metric that be across an organisation. You can to use velocity to future commitments and/or sprints, but that doesn’t mean that it’ll be 100% accurate. Plans change all the time. People will come and go from your teams. However, it can be useful to predict what features you might want to include and how to them. You should use story points and time to base your estimates. Story points should not be related to time, but to effort. Lastly, figure out what your “done” is. Velocity cannot consistent try predict roughly prioritise not Originally published at www.alexaitken.nz on July 9, 2018.

Past Velocity and Prediction

When I think about technical debt, I still remember the first application I created that made me realize the consequences of an unsuitable architecture. It happened back in the late 1990s, when I was first getting started as a consultant. The client had requested use of the Lotus Notes platform to build a procurement system for their customers. Using the Lotus Notes client and a custom application, end-users could make requests that would be tracked by the application and fulfilled by the product owner’s team. In theory, it was a really cool idea – especially since web-developed applications were not prevalent and everyone used Lotus Notes on a daily basis. The core problem is that the data was very relational in design – and Lotus Notes was not a relational database. The solution’s design required schema management within every Lotus Notes document and leaned on a series of multi-value fields to simulate the relationships between data attributes. It was a mess. A great deal of logic in the Lotus Notes application would not have been required if a better platform had been recommended. The source code was complicated to support. Enhancements to the data structure resulted in major refactoring of the underlying code – not to mention running server-based jobs to convert the existing data. Don’t get me started on the effort behind report creation. Since I was early in my career, I have focused on providing a solution that the client wanted rather than trying to offer a better solution. This was certainly a lesson I learned early in my career, but in the years since that project, I’ve come to realize that the consequence of architectural technical debt is an unfortunate reality we all face. Let’s explore the concept of architecture tech debt a little more at a macro level. Architectural Tech Debt (ATD) The Architectural Technical Debt (ATD) Library at Carnegie Mellon University provides the following definition.) of ATD: Architectural technical debt is a design or construction approach that's expedient in the short term, but that creates a technical context in which the same work requires architectural rework and costs more to do later than it would cost to do now (including increased cost over time). In the “Quick Answer: How to Manage Architecture Technical Debt” (published 09/22/2023), Gartner Group defines ATD as follows: Architecture technical debt is that type of technical debt that is caused by architectural drift, suboptimal architectural decisions, violations of defined target product architecture and established industry architectural best practices, and architecture trade-offs made for faster software delivery. In both cases, benefits that often yield short-term celebrations can be met with long-term challenges. This is similar to my Lotus Notes example mentioned in the introduction. To further complicate matters, tooling to help identify and manage tech debt for software architecture has been missing in comparison to the other aspects of software development: For code quality, observability, and SCA, proven tooling exists with products like Sonarqube, Datadog, New Relic, GitHub, and Snyk. However, the software architecture segment has lagged behind without any proven solutions. This is unfortunate, given the fact that ATD is consistently the largest – and most damaging – type of technical debt, as found in the “Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt” 2015 study published by Carnegie Mellon. The following illustration summarizes Figure 4 from that report, concluding that bad architecture choices were the clear leader in sources of technical debt. If not managed, ATD can continue to grow over time at an increasing rate, as demonstrated in this simple illustration: Without mitigation, architecture debt will eventually reach a breaking point for the underlying solution being measured. Managing ATD Before we can manage ATD, we must first understand the problem. Desmond Tutu once wisely said, “There is only one way to eat an elephant: a bite at a time.” The shift-left approach embraces the concept of moving a given aspect closer to the beginning than at the end of a lifecycle. This concept gained popularity with shift-left for testing, where the test phase was moved to a part of the development process and not a separate event to be completed after development was finished. Shift-left can be implemented in two different ways in managing ATD: Shift-left for resiliency — identifying sources that have an impact on resiliency and then fixing them before they manifest in performance.
Shift-left for security — detect and mitigate security issues during the development lifecycle. Just like shift-left for testing, a prioritized focus on resilience and security during the development phase will reduce the potential for unexpected incidents. Architectural observability Architectural observability gives engineering teams the ability to incrementally address architectural drift within their services at a macro level. In fact, the Wall Street Journal reported the cost to fix technical debt at $1.52 trillion earlier this year in “The Invisible $1.52 Trillion Problem: Clunky Old Software,” article. To be successful, engineering leadership must be in full alignment with the following organizational objectives: Resiliency — to recover swiftly from unexpected incidents.
Scalability — to scale appropriately with customer demand.
Velocity — to deliver features and enhancements inline with product expectations.
Cloud Suitability — transforming legacy solutions into efficient cloud-native service offerings. I recently discovered vFunction’s AI-driven architectural observability platform, which is focused on the following deliverables: Discover the real architecture of solutions via static and dynamic analysis.
Prevent architecture drift via real-time views of how services are evolving.
Increase resiliency of applications via the elimination of unnecessary dependencies and improvements between application domains and their associated resources.
Manage and remediate tech debt via AI-driven observability. Additionally, the vFunction platform provides the side-benefit of providing a migration path to transform from monoliths to cloud-native solutions. Once teams have modernized their platforms, they can continuously observe them for ongoing drift. If companies already have microservices, they can use vFunction to detect complexity in distributed applications and address dependencies that impact resiliency and scalability. In either case, once implemented, engineering teams can mitigate ATD well before reaching the breaking point. In the illustration above, engineering teams are able to mitigate technical debt as a part of each release,due to the implementation of the vFunction platform and an underlying shift-left approach. Conclusion My readers may recall that I have been focused on the following mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester The vFunction platform adheres to my mission statement by helping engineering teams employ a shift-left approach to the resiliency and security of their services at a macro level. This is an important distinction because without such tooling, teams are likely to mitigate at a micro level, resolving tech debt that doesn’t really matter from an organizational perspective. When I think back to that application that made me realize the challenges with tech debt, I can’t help but think about how that solution yielded more issues than it did benefits with each feature that was introduced. Certainly, the use of shift-left for resiliency alone would have helped surface issues with the underlying architecture at a point where the cost of considering alternatives would be feasible. If you are interested in learning more about the vFunction solution, you can read more about them here. Have a really great day! When I think about technical debt, I still remember the first application I created that made me realize the consequences of an unsuitable architecture. It happened back in the late 1990s, when I was first getting started as a consultant. The client had requested use of the Lotus Notes platform to build a procurement system for their customers. Using the Lotus Notes client and a custom application, end-users could make requests that would be tracked by the application and fulfilled by the product owner’s team. In theory, it was a really cool idea – especially since web-developed applications were not prevalent and everyone used Lotus Notes on a daily basis. Lotus Notes The core problem is that the data was very relational in design – and Lotus Notes was not a relational database. The solution’s design required schema management within every Lotus Notes document and leaned on a series of multi-value fields to simulate the relationships between data attributes. It was a mess. A great deal of logic in the Lotus Notes application would not have been required if a better platform had been recommended. The source code was complicated to support. Enhancements to the data structure resulted in major refactoring of the underlying code – not to mention running server-based jobs to convert the existing data. Don’t get me started on the effort behind report creation. Since I was early in my career, I have focused on providing a solution that the client wanted rather than trying to offer a better solution. This was certainly a lesson I learned early in my career, but in the years since that project, I’ve come to realize that the consequence of architectural technical debt is an unfortunate reality we all face. Let’s explore the concept of architecture tech debt a little more at a macro level. Architectural Tech Debt (ATD) The Architectural Technical Debt (ATD) Library at Carnegie Mellon University provides the following definition .) of ATD: definition Architectural technical debt is a design or construction approach that's expedient in the short term, but that creates a technical context in which the same work requires architectural rework and costs more to do later than it would cost to do now (including increased cost over time). Architectural technical debt is a design or construction approach that's expedient in the short term, but that creates a technical context in which the same work requires architectural rework and costs more to do later than it would cost to do now (including increased cost over time). In the “Quick Answer: How to Manage Architecture Technical Debt” (published 09/22/2023), Gartner Group defines ATD as follows: Architecture technical debt is that type of technical debt that is caused by architectural drift, suboptimal architectural decisions, violations of defined target product architecture and established industry architectural best practices, and architecture trade-offs made for faster software delivery. Architecture technical debt is that type of technical debt that is caused by architectural drift, suboptimal architectural decisions, violations of defined target product architecture and established industry architectural best practices, and architecture trade-offs made for faster software delivery. In both cases, benefits that often yield short-term celebrations can be met with long-term challenges. This is similar to my Lotus Notes example mentioned in the introduction. To further complicate matters, tooling to help identify and manage tech debt for software architecture has been missing in comparison to the other aspects of software development: For code quality, observability, and SCA, proven tooling exists with products like Sonarqube, Datadog, New Relic, GitHub, and Snyk. However, the software architecture segment has lagged behind without any proven solutions. This is unfortunate, given the fact that ATD is consistently the largest – and most damaging – type of technical debt, as found in the “ Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt ” 2015 study published by Carnegie Mellon. Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt The following illustration summarizes Figure 4 from that report, concluding that bad architecture choices were the clear leader in sources of technical debt. If not managed, ATD can continue to grow over time at an increasing rate, as demonstrated in this simple illustration: Without mitigation, architecture debt will eventually reach a breaking point for the underlying solution being measured. Managing ATD Before we can manage ATD, we must first understand the problem. Desmond Tutu once wisely said, “There is only one way to eat an elephant: a bite at a time.” Desmond Tutu The shift-left approach embraces the concept of moving a given aspect closer to the beginning than at the end of a lifecycle. This concept gained popularity with shift-left for testing, where the test phase was moved to a part of the development process and not a separate event to be completed after development was finished. Shift-left can be implemented in two different ways in managing ATD: Shift-left for resiliency — identifying sources that have an impact on resiliency and then fixing them before they manifest in performance. Shift-left for security — detect and mitigate security issues during the development lifecycle. Shift-left for resiliency — identifying sources that have an impact on resiliency and then fixing them before they manifest in performance. Shift-left for security — detect and mitigate security issues during the development lifecycle. Just like shift-left for testing, a prioritized focus on resilience and security during the development phase will reduce the potential for unexpected incidents. Architectural observability Architectural observability gives engineering teams the ability to incrementally address architectural drift within their services at a macro level. In fact, the Wall Street Journal reported the cost to fix technical debt at $1.52 trillion earlier this year in “The Invisible $1.52 Trillion Problem: Clunky Old Software,” article . article To be successful, engineering leadership must be in full alignment with the following organizational objectives: Resiliency — to recover swiftly from unexpected incidents. Scalability — to scale appropriately with customer demand. Velocity — to deliver features and enhancements inline with product expectations. Cloud Suitability — transforming legacy solutions into efficient cloud-native service offerings. Resiliency — to recover swiftly from unexpected incidents. Scalability — to scale appropriately with customer demand. Velocity — to deliver features and enhancements inline with product expectations. Cloud Suitability — transforming legacy solutions into efficient cloud-native service offerings. I recently discovered vFunction ’s AI-driven architectural observability platform, which is focused on the following deliverables: vFunction Discover the real architecture of solutions via static and dynamic analysis. Prevent architecture drift via real-time views of how services are evolving. Increase resiliency of applications via the elimination of unnecessary dependencies and improvements between application domains and their associated resources. Manage and remediate tech debt via AI-driven observability. Discover the real architecture of solutions via static and dynamic analysis. Discover Prevent architecture drift via real-time views of how services are evolving. Prevent Increase resiliency of applications via the elimination of unnecessary dependencies and improvements between application domains and their associated resources. resiliency Manage and remediate tech debt via AI-driven observability. remediate Additionally, the vFunction platform provides the side-benefit of providing a migration path to transform from monoliths to cloud-native solutions. Once teams have modernized their platforms, they can continuously observe them for ongoing drift. If companies already have microservices, they can use vFunction to detect complexity in distributed applications and address dependencies that impact resiliency and scalability. In either case, once implemented, engineering teams can mitigate ATD well before reaching the breaking point. In the illustration above, engineering teams are able to mitigate technical debt as a part of each release,due to the implementation of the vFunction platform and an underlying shift-left approach. Conclusion My readers may recall that I have been focused on the following mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester The vFunction platform adheres to my mission statement by helping engineering teams employ a shift-left approach to the resiliency and security of their services at a macro level. This is an important distinction because without such tooling, teams are likely to mitigate at a micro level, resolving tech debt that doesn’t really matter from an organizational perspective. When I think back to that application that made me realize the challenges with tech debt, I can’t help but think about how that solution yielded more issues than it did benefits with each feature that was introduced. Certainly, the use of shift-left for resiliency alone would have helped surface issues with the underlying architecture at a point where the cost of considering alternatives would be feasible. If you are interested in learning more about the vFunction solution, you can read more about them here . here Have a really great day!

Managing Architectural Tech Debt

স্থাপত্য প্রযুক্তি ঋণ ব্যবস্থাপনা

Verwalten von technischen Architekturschulden

Gestión de la deuda tecnológica arquitectónica

Gérer la dette technologique architecturale

वास्तुकला तकनीक ऋण का प्रबंधन

アーキテクチャ技術負債の管理

건축 기술 부채 관리

Gerenciando dívidas de tecnologia arquitetônica

Управление долгом за архитектурные технологии

Mimari Teknoloji Borcunu Yönetmek

Quản lý nợ công nghệ kiến trúc

管理建筑技术债务

In our last post, we introduced you to the project and how it offers a revolutionary set of language extensions for Java, including the ability to parse and process files seamlessly in Java. Today, we will take a look at another exciting feature of the Manifold project: string templates. Manifold JSON https://www.youtube.com/watch?v=ite6a5y50yQ&embedable=true But before we get to that, some of the feedback I got from the previous post was that I was unclear about Manifold. Manifold is a combination of an IDE plugin and plugins to Maven or Gradle. Once used we can enhance the Java language (or environment) almost seamlessly in a fluid way. A frequent question was how is it different from something like ? Lombok There are many similarities and in fact, if you understand Lombok then you are on your way to understand Manifold. Lombok is a great solution for some problems in the Java language. It is a bandaid on the verbosity of Java and some of its odd limitations (I mean bandaid as a compliment, no hate mail). Manifold differs from Lombok in several critical ways: It’s modular - all the extensions built into Manifold are separate from one another. You can activate a particular feature or leave it out of the compiler toolchain. It’s bigger - Lombok has many features but Manifold's scope is fantastic and far more ambitious. It tries to do the “right thing” - Lombok is odd. We declare private fields but then use getters and setters as if they aren’t private. Manifold uses properties (which we will discuss later) that more closely resemble what the Java language “should have offered”. Manifold also has some drawbacks: It only works as a compiler toolchain and only in one way. Lombok can be compiled back to plain Java source code and removed. It only supports one IDE - IntelliJ. These partially relate to the age of Manifold which is a new project by comparison. But it also relates to the different focus. Manifold focuses on language functionality and a single working fluid result. JEP 430 String Interpolation One of the big features coming to JDK 21 is , which is a string interpolation language change. JEP 430 It will allow writing code like this: String name = "Joan";
String info = STR."My name is \{name}"; In this case, will have the value . This is just the tip of the iceberg in this JSR as the entire architecture is pluggable. I will discuss this in a future video but for now, the basic functionality we see here is pretty fantastic. info “My name is Joan” Unfortunately, it will take years to use this in production. It will be in preview in JDK 21, then it will be approved. We will wait for an LTS, and then wait for the LTS to reach critical mass. In the meantime, can we use something as nice as this today? Maven Dependencies Before we dive into the code, I want to remind you that all the code for this and other videos in this series is available on (feel free to star it and follow). GitHub String templating has no dependencies. We still need to make changes to the pom file but we don’t need to add dependencies. I’m adding one dependency here for the advanced templates we will discuss soon. All that’s needed is the compiler plugin. That means that string templates are a compile-time feature and have no runtime impact! <dependencies>
   <dependency>
       <groupId>systems.manifold</groupId>
       <artifactId>manifold-templates-rt</artifactId>
       <version>${manifold.version}</version>
   </dependency>
</dependencies>

<build>
   <plugins>
       <plugin>
           <groupId>org.apache.maven.plugins</groupId>
           <artifactId>maven-compiler-plugin</artifactId>
           <version>3.8.0</version>
           <configuration>
               <source>19</source>
               <target>19</target>
               <encoding>UTF-8</encoding>
               <compilerArgs>
                   
                   <arg>-Xplugin:Manifold</arg>
               </compilerArgs>

               
               <annotationProcessorPaths>
                   <path>
                       <groupId>systems.manifold</groupId>
                       <artifactId>manifold-strings</artifactId>
                       <version>${manifold.version}</version>
                   </path>
                   <path>
                       <groupId>systems.manifold</groupId>
                       <artifactId>manifold-templates</artifactId>
                       <version>${manifold.version}</version>
                   </path>
               </annotationProcessorPaths>
           </configuration>
       </plugin>
   </plugins>
</build> Manifold String Interpolation To begin, we can create a new variable that we can use to get external input. In the second line, we integrate that variable into the printout: String world = args.length > 0 ? args[0] : "world";
System.out.println("Hello $world! I can write \$world as the variable..."); The backslash syntax implicitly disables the templating behavior, just like in other string elements in Java. This will print . “Hello world! I can write $world as the variable…” There’s something that you can’t really see in the code, you need to look at a screenshot of the same code: ![]( align="center") https://cdn.hashnode.com/res/hashnode/image/upload/v1683029461078/84f52be2-30c3-435f-bbf6-4a53937b3859.png It’s subtle, do you see it? Notice the expression, it is colored differently. It's no longer just a string but a variable embedded in a string. This means that we can control-click it and go to the variable declaration, rename it, or see find its usage. $world There's another way to escape a string, and we can use the annotation on a method or a class to disable this functionality in the respective block of code. @DisableStringLiteralTemplates This can be useful if we use the dollar sign frequently in a block of code: @DisableStringLiteralTemplates
private static void noTemplate(String word) {
   System.out.println("Hello $world!");
} Templates The Manifold project allows us to create JSP-like templates without all of the baggage. We can define a base class to a template to create generic code for the templates and place common functionality in a single location. We can create a file called HelloTemplate.html.mtl in the resources/templates directory with the following content. Notice the params we define in the template file can be anything: <%@ params(String title, String body) %>
<!DOCTYPE html>
<html lang="en">
<head>
 <meta charset="UTF-8">
 <title>${title}</title>
</head>
<body>
   ${body}
</body>
</html> This will seem very familiar to those of us with a JSP background. We can then use the file in the Java code like this, we can pass the parameters and they will replace the appropriate blocks in the HTML file: System.out.println(HelloTemplate.render("My Title", "My Body")); Notice the generated template it compiled to a class, similar to JSP. Unlike JSP this template isn’t a servlet and can be used in any context. A local application, a server, etc. The templating language is more lightweight and doesn’t depend on various server APIs. It is also less mature. The main value is in using such an API to generate arbitrary files like Java source files or configuration files. The templating capabilities are powerful yet simple. Just like we could in JSP, we can embed Java source code into the template e.g. we can include control flow and similar restrictions just like we could in JSP: <% if(body != null) {%>
   ${body}
<% } %> Why Not: JSP, Velocity, Thymeleaf, or Freemarker? There are so many templating languages in Java already… Adding yet another one seems like a heavy burden of replication. I think all of those are great and this isn’t meant to replace them, at least not yet. Their focus is very much on web generation, they might not be ideal for more fluid use cases like code generation or web frameworks like Spark. Another big advantage is size and performance. All of these frameworks have many dependencies and a lot of runtime overhead. Even JSP performs the initial compilation in runtime by default. This templating support is compiled and Spartan, in a good way. It’s fast, simple, and deeply integrated into the application flow. Import We can import Java packages just like we can in every Java class using code like this: <%@ import com.debugagent.stringtemplates.* %> Once imported we can use any class within the code. Notice that this import statement must come above other lines in the code, just like a regular import statement. Include We can use include to simply include another template into the current template, allowing us to assemble sophisticated templates like headers and footers. If we want to generate a complex Java class, we can wrap the boilerplate in a generic template and include that in. We can conditionally include a template using an if statement and use a for loop to include multiple entries: <%@ include JavaCode("ClassName", classBody) %> Notice that we can include an entry with parameters and pass them along to the underlying template. We can pass hardcoded strings or variables along the included chain. A Lot More I skipped extends because of a documentation issue, which has since been fixed. it has a lot of potential. There’s layout functionality that has a lot of potentials but is missing parameter passing at the moment. But the main value is in the simplicity and total integration. When I define a dependency on a class and remove it from the code the error appears even in the template file. This doesn’t happen in Thymeleaf. Final Word In conclusion, with the Manifold project, we can write fluent text processing code today without waiting for a future JVM enhancement. The introduction of String templates can help Java developers generate files that aren't a web application, which is useful in several cases e.g. where code generation is needed. Manifold allows us to create JSP-like templates without all of the baggage and generate any arbitrary file we want. With the inclusion of sophisticated options like layout, the sky's the limit. There’s a lot more to Manifold and we will dig deeper into it as we move forward. Also published here.

The Manifold Project: Exploring String Templates for Java Development

Upon doing research for this post, I was thinking of the ways friends at certain FAANG companies talk about their work. Often nonchalantly, they describe their days as mostly consisting of working 3-4 hours, checking off their work tickets and punching out 40 full-time hours. While the pandemic has taken away their access to nap pods and recreational basketball on campus, they are left unsure of what to do with the rest of their allotted work hours. It all became far too realistic once I stumbled upon a Hacker News forum post from January of 2020. A pleading developer asked fellow peers: With nearly 1,500 upvotes and just under 1,000 replies, the developer dilemma that has been hiding in plain sight from engineering managers for decades has now turned to disenfranchisement for many. How do you measure developer productivity, and are we really seeing value from these metrics? “I've been slacking off google for 6 years. How can I stop this?” Input and output measurements: the good and the bad Input measurements are the general basis of how not just developer efficiency is measured, but really any organization. Input comes in many forms; most commonly, you see input as a measurement of hours worked. 40-hours a week of work means good, efficient work was produced, right? The problem arises when this rudimentary way of measuring time and output is met with “negative work.” This is work that is done with such little consideration that it must be re-done later, resulting in dead hours of developer time and much more cost to the business. Output measurements in the developer community are a disaster. Gauging work output based on lines of code or amount of pull requests is very similar to measuring a restaurant’s success by the amount of leftover food they have at the end of a night. It may be beneficial to some extent in determining the overall success of the restaurant, sure. However, if there was too much food ordered or one item was more popular than another on a given day, then this measurement provides little utility. Another problem is that most of these metrics can easily be manipulated by the developer. A task set for 1 week could potentially take a programmer mere hours to complete, resulting in missed opportunities for the business to grow at a much faster rate. Measuring bugs, tickets completed and metrics similar to this also resolve tricky waters. Developers can purposefully write more lines of code, without ever being checked for code quality and awarded at their job. The same goes for much of anything else ticketed to their weekly tasks. Measuring developer productivity: the way right While the case for individual productivity metrics has been hotly discussed, at the end of the day, productivity and developer efficiency are . both individual and team sports Development teams are much like a basketball team’s rotating 10 rosters. Some players are shooters, specifically, put in to generate points and seek a lead. Others are defensive specialists, who come in during tight moments and shut down a fiery assist maker or take the right charge on a paint-driving play. Some are just overall role players! They come in, put up generalist minutes and come back out. The team functions together with individual player attributions summarizing an inevitable outcome. That being said, individual characteristics make up the general whole. Sharpshooters need to produce a certain field goal percentage for a given team’s needs, a defender needs a track record of tight defence and a low point allowed percentage, and this goes on and on. This is the same way development teams should work. You may have force-multipliers, team members who come in and generate a lot of buzz for the workload, while others are more janitorial - they go back through, test and reconfigure buggy code and make sure all of it runs the way it should be. These types of team players are difficult to gauge in terms of productivity but are critical to the health of the organization. Their individual output, however, is an essential facet of how this team succeeds and will continue to succeed based on their previous work assumptions. Measuring development velocity and agility Arguably two of the most effective ways to measure developer productivity are through measuring velocity and agility. Development velocity calculates the net total tasks completed by a team over a set period that rely heavily on the developer’s own predetermined set boundaries for the time allotted. Velocity is a measure, and a planning measure solely. Velocity works best when it’s paired with foundational questions like, “how much work can my team get done this month?” Velocity provides contextual data to support this response. planning Development agility measures any given response to change. It’s iterative, generally software heavy, and aims to deliver working software to any particular customer quickly. Collaboration and incorporating the individual’s unique skill into the team is what drives developer productivity. A developer in agile development, as described by , “acknowledges that software is developed by people operating in groups which the talents of those folks, their ability to collaborate is at the core for the success of the project.” geeksforgeeks The third agile principle The is a sort of sacred document for developers. In this, the founders reiterate the mission, to “[b]uild projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.” Agile Manifesto The only genuine way to measure developer productivity is to make sure organizations incentivize developers to be the best they can be. The goal is to instil working environments that challenge and bring individualism, all the while being areas for growth and areas that allow for value to be added. Developers are most productive when they can run and operate on their own schedules. By leveraging which input and output benefits are conducive for your team, assessing the need for individual success to make the team shine, as well as getting a firm understanding of velocity and agility, your development team will be ready to improve code quality and work more efficiently than ever before.

How to Measure Productivity as a Developer

This story was originally posted on September 25, before Hardfork20 went live. In another couple of hours Hardfork20 will occur on Steem blockchain. Top 20 witnesses are running their nodes on version 0.20.2 which means they are all set for the hardfork. What is Hardfork? For those of you who are not familiar with the term, Hardfork means an upgrade to the blockchain. The current code release or the upgrade can be found on This release is called Hence you might be hearing the word if you are reading any blogs related to this upgrade. Steem Github Page Velocity. Velocity Hardfork What is Steem Blockchain? Steem is a DPOS based blockchain built for websites and apps that are centred around content. Steem makes it easier for content driven websites to run on blockchain. Steem has an inbuilt reward mechanism which incentivises content creators, content curators and app developers based on the value they add to the overall network. The common misconception is that This is farthest from the truth. Steem blockchain is just the backend and there can be any number of interfaces (websites or apps) that can be built on steem blockchain. Steem Blockchain= www.steemit.com Image from steemit.com As you can see from this image Steem blockchain forms the central piece and there other services and apps that make use of this blockchain like , , , , , https://steemit.com https://busy.org/ https://steepshot.io/ https://join.utopian.io/ https://d.tube/ https://esteem.app/ There are just some of the apps that are live and popular already. There are many more and you can check them out on https://steemprojects.com/ What are the new features in Velocity Hardfork? Velocity Hardfork has many important changes. Most of these changes will have a great impact on User experience and Interaction, how apps will work in future and how Steem Media Tokens will finally shape up. The major features in this Hardfork are 1 . Unlimited Editing Prior to this hardfork content couldn’t be edited once the rewards were awarded. This effective meant that you couldn’t update the content after seven days. While this makes sense to keep the demand for new content high on the platform it also meant that you couldn’t update your content after seven days if you found something missing or error prone. Most of the times you need to update you content as the context changes. If this was not the case we would have so many posts on Steem blockchain which would have been full of broken links as the time progresses. With hardfork 20 this is going to change. 2 . Resource Credits Implementation Most of the blockchains do not take into consideration the future cost of current actions on blockchain. While various transactions on blockchain are seemingly free it is not. There is a cost to every action and it has to be borne by somebody. It may not be you at the time, but the cost has to be borne nevertheless. With centralised services the cost is borne by the likes of Facebook and Google as they invest it in you now so that they can later sell ads to you, sell your data to the third parties or use you to train their massive AI models :) It is the same with blockchains as well. Whether you realise or not there is a cost for every action and that is borne by somebody. In fact it costs money for you to create an account on Steem blockchain and perform every action like post, comment and upvote on the blockchain. But you may not realise this as this is being paid by Steem INC for now. Currently the cost approximates are not accurate and a lot of generalisations have been made. With Resource Credits Steem will be able to identify the costs of each and every action. This will also help the app developer identify the costs of the transactions so that they can make sure that UI/UX of their users doesn’t suffer. It might take some time for the equilibrium to reached. Based on how the community responds witnesses will be able to make some tweaks over the time so that the User experience is not hampered but at the same time there is a better mechanism to handle the spam on the platform. But the outcome in Steem will be much more interesting as it will affect the existing community. The outcome of this experiment might define how the content based and community based websites of future will be defined. EOS is also doing something on similar lines. 3. Free Account creation by Dapps Currently it takes close to 1 weeks to 2 weeks to create accounts on Post Hardfork20 users will be able to purchase Account Creation Tokens using their Resource Credits (RCs). These Account Creation Tokens can be used to create accounts for the new users on the platform. The supply of these Account Creation Tokens will be decided by the witnesses. Initially the supply of these Account Creation Tokens will be low and hence their exchange rate very high. This will make sure that new accounts are not flooded on the platform. Once the equilibrium is reached Apps will be able to better estimate the cost of account creation and they can purchase the Account Creation Tokens accordingly. www.steemit.com We are working on a product that will be based on Steem blockchain. We thought of releasing a beta after integrating with the SMTs (First or second quarter of 2019). But after some deliberation we have decided to build it on the existing steem blockchain and integrate with the SMTs once they are ready for deployment. So each of the changes introduced in Hardfork will be important for us as they will address our pain points. Feature Wishlist One feature we wish was part of this Hardfork was perpetual rewards. But after posting comments on few posts looks like this is not going to be implemented in the core any time soon. The consensus amongst the development team and the witnesses seems to be that if it can be handled in the second layer, then it should be handled in the second layer. The idea seems to be that only minimal required changes will be made to the core blockchain. I think this makes sense. So we will be handling the perpetual tokens on our interface. But we are not sure how it will translate in general as most of the users still use and I don’t think steemit will do anything in this regard. www.steemit.com However these are some interesting changes in this particular Hardfork and we are looking forward to how they will play out over the next week. Its not going to be all rosy. In fact there was an issues over the last week and steem blockchain was down for couple of hours. Why was Steem blockchain down last week? Steem blockchain was down last week. The issue was related to this hardfork. All the witnesses and exchanges were asked to run their nodes on version 0.20.0 But due to a bug in the latest code the blockchain was down. The built in safety measures made sure that the funds were not at risk and took the blockchain down until the issue was fixed. You can read more about it in their blog detailing what went wrong. There are many people including a couple of witnesses who expressed their discomfort saying that the upgrade should have been tested further and it might have been a good idea not to club all the critical upgrades in a Hardfork. But however from we can see that top 25 witnesses are already running on 0.20.2 and hence it will go live at September 25, 2018 at 15:00:00 UTC if there are no major hiccups. https://steemd.com/witnesses Let us know how this hardfork will affect your product or service. If you are an end user be patient over the next week and provide your feedback. The community needs it :) References Latest blog about hardfork by Steemit — https://steemit.com/steem/@steemitblog/hardfork-20-what-to-expect-tomorrow Recent blogs by steemitblog about the Steem roadmap — https://steemit.com/@steemitblog ATS Witness’ thoughts on velocity — https://steemit.com/witness/@ats-witness/steem-hardfork-20-thoughts-on-velocity

Why Hardfork20 is a big deal for Steem Blockchain

raised this very interesting point on Twitter, something worth serious thought… David Hussman But Agile already has an alternative word for sprint — . “Sprint” is Scrum-specific terminology. Iteration Words are vague, and drag oft-unintended implications around with them. The word “sprint” implies a velocity — in a forward direction, for a short period, . as fast as humanly possible Of course, in the real world, you don’t run a sprint and immediately follow it with another sprint, and another, in an uninterrupted sequence. You’d quickly fall over from exhaustion. So as a metaphor for software development, it’s problematic. The Tortoise and the Hare, Disney 1935 Agile has always had this problem — the idea that Agile is a way to develop software, rather than a way. Frankly, I think this is one of the things that sold the industry on Agile. And now, twenty years since Scrum and Extreme Programming hit the scene, people still expect Agile to be faster, as opposed to better. faster better And David hits the nail on the head here… the idea that Agile is rather than is embedded right in the most fundamental terminology of the most widely-used Agile methodology. It’s a problem we’re bringing on ourselves. fast good “Iteration” has different implications. First, it implies that we are taking something we already have, and making it better. But perhaps more importantly, it does imply a pace of change. Iterations can be fast, or they can be slow. The important part is the improvement, not the speed. not This gets to the heart of Agile, for me. When we finish an iteration, we should be in a better place than when we started the iteration. We should see visible progress. The curse of Waterfall was not being able to see progress (and due to that lack of visibility, not being able to make course corrections). The curse of Scrum seems to be this false idea of maximum speed. When we’re driving and conditions are sketchy ahead of us, we slow down. We don’t drive at maximum speed. The beauty of Agile is that it helps us deal with uncertain conditions, because the road to our products is rarely straight and level and dry. Agile isn’t how fast you can go, it’s how fast you can turn. The other day, I watched , a classic documentary about Formula One auto racing in the early 1970s. At the start of the movie, the narrator made an interesting point — “These cars aren’t just fast. They’re ” Formula One cars can brake hard, accelerate hard, and turn hard, much harder than ordinary cars. They’re the fastest cars not because they have the highest top speed, but rather because they are the most responsive to complex, always-changing conditions. The Quick and the Dead quick. And that’s what I want Agile to be. Not necessarily fast, just quick. Not sprints, just iterations.

Iterations, not sprints

The clock is ticking, deadlines are looming, and the project isn't moving as fast as it should. In comes the seemingly obvious solution - hiring more software developers. More people should equal faster work, right? But let's step back for a moment. This isn't a production line; it's a complex process that involves more than just coding. Simply inflating your team doesn't guarantee quicker development. Sometimes, it can even slow you down. So what does speed up software development, if not just headcount? That's what I’m going to explore. I’ll get into the bones of why more software engineers don't necessarily mean faster progress and what alternatives can genuinely boost your productivity. And trust me, it's not about working harder; it's about working smarter. The Myth of More It's easy to see why the 'more engineers, faster development' myth is so prevalent. It seems intuitive, doesn't it? The more people working on a task, the quicker it gets done. But when we look closer, this notion doesn't quite hold up, particularly in software development. Enter : Brooks's Law "Adding manpower to a late software project makes it later." This principle was born out of Fred Brooks's book , a seminal work in software engineering (despite having glaring gender inclusion issues throughout, which readers should be conscious of!). "The Mythical Man-Month" In short, we increase the communication overhead as we add more people to a project. More people mean more lines of communication, more chances of miscommunication, and more time spent on coordination rather than productive work. It's not a linear progression. It's exponential. Now, let's throw new hires into the mix. Getting a new engineer up to speed takes time and effort. It involves time, resources, and often the help of existing team members - which takes them away from their tasks. The ramp-up time is real, and it can be substantial. And what about the complexities of modern software projects? They are typically interwoven, multi-faceted entities that lend themselves poorly to the divide-and-conquer approach. We aren't dealing with a pile of tasks that can be handled independently. Everything is interconnected. Changes in one area can have ripple effects, causing the need for adjustments, testing, and quality assurance elsewhere. So, while the appeal of adding more engineers to speed things up is understandable, it's a short-sighted solution. Process and Communication: Efficiency Beyond Headcount So, achieving faster development isn't about simply filling more chairs. It's about maximising the potential of those already seated. Here’s how we do it. Next-level Agile Agile methodologies provide the framework for reducing waste and increasing efficiency. However, in software development, it's not just about eliminating redundant tasks or automating repetitive ones. It goes deeper. It needs to be about understanding your unique "value stream," where the real value is created in your development process, and optimising for it. This could mean different things to different teams – it may lie in design, testing, deployment, or elsewhere. Collaboration is ready for the AI era Fostering effective communication is a known mantra, but let's push it further. With a seasoned team of engineers, the issue isn't basic communication – it's about creating a shared context. Each team member should have real-time access to the collective knowledge, changes, and progress. Achieving this certainly wasn’t trivial before the AI boom, but I’m working on something that will hopefully make it trivial. is a tool I’ve been developing with my team to solve this. It’s an AI tool that aggregates and analyses data from Slack, Jira and GitHub. CollabGPT It can be queried in natural language, and provides extremely smart summaries of what activity has happened, and actionable suggestions on what needs to be done. Find out more about CollabGPT, if you want to level up collaboration in your software team. The Software Development Cycle in the AI Era My team who work in software. recently surveyed 200+ people Teams who have adopted AI say, on average, their software development life cycle is 2.5x faster because of adopting AI. Those same teams predict they’ll be 3.5x faster within a year. But there’s resistance to AI. , how green the tech is (48%), and struggle with battling a general resistance to change (38%). Leaders worry about data privacy (48%) The question is: can non-adopting teams afford to be left behind like this? More than 7 in 10 companies have no guidelines around AI adoption, which likely contributes to the hesitancy. Without a collective understanding and agreement about what safe and unsafe AI looks like, it’s impossible to make good decisions about how to adopt. These organisations end up with blanket bans. I wrote a list of AI for engineers that CTOs need to know about, which you can read here. Paving the Way to Efficient Development Adding engineers is not a silver bullet for fast-tracking project timelines. Sometimes, it might be the answer. More often, it's better processes, streamlined communication, and efficient tools that truly fuel acceleration. The truth is, our industry's clock is always ticking. But with the right tools and approaches in place, we're not just keeping pace; we're defining the tempo. For those curious about how AI can impact your teams, I'd love you to consider exploring our AI tool, CollabGPT. It reduces information overload and enhances collaboration in development teams. Find out about CollabGPT Also published . here

VELOCITY

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Since 2005

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VELOCITY

velocitymsc.com

501-1K employees

Since 2005

COMPANY RANKING

VELOCITY

EVERGREEN INDEX #885

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