The use of F# demonstrates a sweet spot for the language within enterprise software
I have written an application to balance the national power generation schedule for a portfolio of power stations to a trading position for an energy company. The client and server components were in C# but the calculation engine was written in F#.
The use of F# to address the complexity at the heart of this application clearly demonstrates a sweet spot for the language within enterprise software, namely algorithmically complex analysis of large data sets. My experience has been a very positive one.
At Credit Suisse, we’ve been using F# to develop quantitative models for financial products
Building valuation models for derivative trades requires rapid development of mathematical models, made possible by composition of lower-level model components. We have found that F#, with the associated toolset, provides a unique combination of features that make it very well suited to this kind of development. In this talk, I will explain how we are using F# and show why it is a good match. I will also talk about the problems we have had, and outline future enhancements that would benefit this kind of work.
The F# code is consistently shorter, easier to read, easier to refactor and contains far fewer bugs. As our data analysis tools have developed … we’ve become more productive.
At Kaggle we initially chose F# for our core data analysis algorithms because of its expressiveness. We’ve been so happy with the choice that we’ve found ourselves moving more and more of our application out of C# and into F#. The F# code is consistently shorter, easier to read, easier to refactor, and, because of the strong typing, contains far fewer bugs.
As our data analysis tools have developed, we’ve seen domain-specific constructs emerge very naturally; as our codebase gets larger, we become more productive.
The fact that F# targets the CLR was also critical - even though we have a large existing code base in C#, getting started with F# was an easy decision because we knew we could use new modules right away.
The performance is phenomenal. We can now re-calculate the entire bank portfolio from scratch in less than a second and the response-time for single deal verification calculation is far below 100 milliseconds.
I first evaluated F# back in 2006 - 2007 for the purpose of math oriented high performance applications within Financial Risk. I got in spring 2009 a mission to implement a new Real-time Counter-party Risk system covering all possible present and future deal types within the entire bank. The effort was started with only three resources, me as architect and lead developer and two colleagues – one risk expert and one high performing developer. Our first intention was to use C#, but I did a quick proof-of-concept with F# implementing a low level TCP/IP-communication to an existing risk-system. This showed us and our management that F# could give us a real productivity boost due to its support for multiple paradigms and functional concepts together with an impressive support for multi-threading.
Our first delivery is approaching rapidly and F# has proved itself as a real life-saver. We started off using C# in many places but have since then moved almost entirely into F# due to its ability to reduce the amount of code required and its simplicity when developing massive parallel computations. The performance is phenomenal. We can now re-calculate the entire bank portfolio from scratch in less than a second and the response-time for single deal verification calculation is far below 100 milliseconds(the original demand was 200 milliseconds to make the application usable for electronic markets). Although some gains are to be attributed to how we have built our calculation models, F# made it possible for us to implement our algorithms and techniques with very little code and with a huge similarity to the original mathematical models and regulations (which is important for verification of correctness). We have also been able to use the support for Async-workflows producing code that is simple and clear and easy to understand but still runs in parallel when required.
The present application contains 35 to 40.000 lines of F#-code and an equal amount of C#-code. However, our estimate is that the F# code contains at least 80% of the functionality (which is pretty amazing!). Our experience shows us that the number of code lines shrinks with a ratio of 1/2 to 1/4 by just porting functionality from C# to F# (not counting single character or empty lines in the C#-code). We have by remodeling increased the ratio to the area of 1/5 to 1/8, where the remodeling involves replacing object oriented constructs with functional ones (and actually removing mutable states). One example from last week was a limit-utilization module written in F# but using an object-oriented approach containing +300 lines of code. I rewrote it to below 70 lines of code just by shifting paradigm (and the rewrite made it much easier to understand and verify)!
Grange Insurance parallelized its rating engine to take better advantage of multicore server hardware
For nearly 75 years, Grange Insurance has offered competitive products and services to policyholders in more than a dozen U.S. states. To maintain its well-earned reputation and standing, the company decided to enhance its rating engine—a software tool for rating policies and performing what-if modeling, impact analyses, and other vital activities. Working with the Sophic Group and using the Microsoft Visual Studio Team System development environment and F# programming language, Grange Insurance parallelized its rating engine to take better advantage of multicore server hardware, and in so doing garnered significant performance benefits. Processes that used to require hours now take just minutes, enabling the company to trim time-to-market by weeks and making it far easier for independent agents to sell and service Grange products.
Large insurance company developed an entire pension quote calculator entirely in F# in under 100 days with no prior F# experience at all…
One of the world’s largest insurance companies have F# code in production, are starting several more projects in F#. We are currently consulting for this company (£2.5bn profit) who have migrated some of their number crunching and business logic to F# and are so happy with the results (10x faster and 10x less code vs their Visual C++ 6) that they are proposing to migrate 1,600,000 lines of code to F#. In particular, their developers found F# easy to learn and use.
… my predecessor developed an entire pension quote calculator (typically scheduled to take 300-400 man days) entirely in F# in under 100 days with no prior F# experience at all. Performance is 10× better than the C++ that it replaces because the new code avoids unnecessary copying and exploits multicore parallelism. Part of my job here will be to give basic F# training to around 20 people and bring a few people up to expert level.
In answer to “Can you give any evidence for 10x performance gain over C++?”. The insurer’s C++ code is a simple manual translation from very inefficient Mathematica code that suffers from several pathological performance problems mainly centered around excessive copying. The F# rewrite does not have these problem. The 10x performance gain was verified by the client.
Our risk and analytic capabilities (…) are entirely written in F#
…work directly with Trafigura’s Chief Risk Officer/Head of Quantitative Analysis, cranking code and rapidly extending our risk and analytic capabilities, which are entirely written in F#.
Trafigura Limited engages in the supply and offtake of crude oil, petroleum products, liquefied petroleum gas, metals, and metal ores and concentrates worldwide. Its solutions include trading, financing, hedging, and logistical support….
The F# solution offers us an order of magnitude increase in productivty…
F# is becoming an increasingly important part of our server side infrastructure that supports our mobile and web-based social games with millions of active users. F# first came to prominence in our technology stack in the implementation of the rules engine for our social slots games which by now serve over 700,000 unique players and 150,000,000 requests per day at peaks of several thousand requests per second. The F# solution offers us an order of magnitude increase in productivity and allows one developer to perform the work that are performed by a team of dedicated developers on an existing Java-based solution, and is critical in supporting our agile approach and bi-weekly release cycles.
The agent-based programming model offered by F#’s MailboxProcessor allows us to build thread-safe components with high-concurrency requirements effortlessly, without using locks and sacrificing maintainability and complexity. These agent-based solutions also offer much improved efficiency and latency whilst running at scale. Indeed our agent-based stateful server for our MMORPG has proved a big success and great cost saver that we’re in the process of rolling it out across all of our social games!
For a machine learning scientist, speed of experimentation is the critical factor to optimize.
I wrote the first prototype of the click prediction system deployed in Microsoft AdCenter in F# in a few days.
For a machine learning scientist, speed of experimentation is the critical factor to optimize. Compiling is fast but loading large amounts of data in memory takes a long time. With F#’s REPL, you only need to load the data once and you can then code and explore in the interactive environment. Unlike C# and C++, F# was designed for this mode of interaction. It has the ease of use of Matlab or Python, both of which I have used extensively in the past. One problem with Matlab and Python is that they are not strongly typed. No compile-time type checking hurts speed of experimentation because of bugs, lack of reusability, high cost of refactoring, no intellisense, and slow execution. Switching to F# was liberating and exhilarating. 2 caveats: Not every problem fits that model. With a bit of discipline, such as avoiding massive parallelism for as long as possible, the model goes a long way. The second caveat is that the cost of learning F# is steep. For me, it was 2 weeks of decreased productivity. It has proven a worthwhile investment.
As a machine learning practitioner programming in F#, I constantly switch between two activities: 1) writing prototype code (highly interactive ugly code with throw away results, functions, and visualizations) and 2) upgrading prototype code to library standard (fast, generic, reusable). When I go back to writing prototypes, I build on top of the newly upgraded functions. In F#, the cost of switching between these two modes is minimal: often nothing needs to be done other than adding comments and deleting deprecated functions.
This means that most of the time is dedicated to experimenting and the majority of the code is close to shipping quality. Some people can do this in C# or Matlab, but I find that F# excels at it.
I started F# with deep suspicions regarding efficiency. My first test was to link F# with C++/CLI and check performance of calling SSE/AVX optimized code. As hoped, F# is comparable to C# when it comes to speed. You have the same flexibility to link with well optimized code. The inline generics are truly magical: same IL in the linked DLLs, but the functions expand to specialized fast code when you instantiate them. Compromises between intuitive code and efficient code still need to be made. I found that “for” loop, “tail recursive” loop, or Parallel.For with ThreadLocal loops, are faster than a succession of piped IEnumerables (seq in F#). F# does not hamper one’s ability to write ugly fast code. Rest assured.
Several people in the machine learning group in Microsoft Research have switched to F# for the reasons above. The world is slowly moving toward functional programming with good justifications: the code is cleaner and easier to debug in a distributed environment. Among the available functional languages, F# is a compelling option.
The results speak for themselves.
As a business we actively seek improvement every single day. This is the same for our IT systems, so we have been searching for a means to do that in our in-house software systems.
The F# type system has allowed us to do this - by eliminating null references, increasing type safety and creating rich domain models that help us express hard-and-fast business rules in a way that we can really lean on the compiler; while actually reducing our total lines of code (and noise!). Doing so has reduced both our requirement for expensive bug hunts in our production systems, and the overall cost of maintaining unnecessary code complexity.
We have been evaluating F# for a year now, and have components in our production systems that have been bug-free since deployment. The results speak for themselves.
…we have decided to use F# as our functional language to have automatic integration with rest of the system…
We develop security product to protect critical infrastructure (e.g. Oil Refinery, Airport, etc) for countries across the globe…. In core of our product there are prediction algorithms. We use different modeling and theorems (Monte Carlo, Action, etc) to implement the prediction components. … Since we are rewriting our next generation product using .NET, we have decided to use F# as functional language to have automatic integration with rest of the system. … We also have advanced machine learning components (Artificial Intelligence) and functional languages are the best fit to write AI stuff. We are planning to use F# as the primary programming language in this area because of its interoperability with .NET.
With its new tools, the bank can speed development by 50 percent or more, improve quality, and reduce costs.
A large financial services firm in Europe sought new development tools that could cut costs, boost productivity, and improve the quality of its mathematical models. To address its needs, the bank deployed F#, the .NET Framework, and Visual Studio. It will soon upgrade to Visual Studio 2010 and then integrated F#. With its new tools, the bank can speed development by 50 percent or more, improve quality, and reduce costs.
F# encourages Reason Driven Development that leads to virtually bug-free code
We are using F# because it considerably increases speed of software development which is crucial for a small company with limited development resources. The most enjoyable feature of this language is that the developer can reason about the code instead of relying only on unit tests. I would say the language encourages Reason Driven Development methodology which leads to virtually bug-free code. F# as strongly typed functional language ideally fits for tasks our software solves – Fixed Income securities trading optimization. It is also very important that F# computation engine could be seamlessly integrated with other parts of .NET-based software product.
At a major Investment Bank, we used F# to build an Early Warning Indicator System for Liquidity Risk
Early Warning Indicators is a standalone dashboard application to monitor real-time market movements and highlight potential risk for further analysis. EWI subscribed to real-time equity, Forex and commodity prices and needed to calculate Red/Amber/Green status in real-time for tolerance breaches and to generate dashboard reports as needed.
The business wanted the flexibility to define formulas using Excel expressions, but spreadsheet components could not cope with the data-rate without conflation and management didn’t want a solution that relied on an Excel template and IT change control to add new indicators.
F# was chosen for development productivity, performance of a cell framework implemented using computation expressions; ease with which Excel expressions could be parsed as a DSL and .NET integration with QALib, Market and timer-series data.
Post implementation review highlighted that (given resource and time constraints) functionality would have been sacrificed without F# and its associated tooling.
I keep being surprised by how compact and readable F# is…
We have set up a complete risk management system that combines several data sources, presents them in a … WPF user interface, and does a LOT of calculation behind the scenes. When the calculation requires a proper algorithm (i.e. anything that is more complex than a simple for loop), our choice has been F#. I have to say I keep being surprised by how compact it is and, nonetheless, how readable it is even when I’m reading code that I hadn’t looked at or thought about for six months.
The efficient use of functional programming throughout the R&D cycle helped make the cycle faster and more efficient.
The credit markets have varying pockets of liquidity. Market participants would like to understand how the liquidity of their set of entities changes relative to the overall market. A liquidity scoring model is needed to provide these metrics across the entire CDS universe. Functional programming and specifically F# was used in order to provide the market with a fast and accurate solution. … The research and development cycle was made faster and more efficient by the effective use of functional programming.
The efficient use of functional programming throughout the R&D cycle helped make the cycle faster and more efficient. Less time was spent on translating requirements, miscommunications etc and more on producing a fast and accurate solution quickly.
Since programmers can understand your quant code they can focus on their core competency – developing fast and reliable production code. The development exercise becomes catered towards optimization, performance tuning and error handling (i.e. making the code reliable) Functionality is not lost from the prototype due to miscommunication or rather crude documentation/requirements, which saves time in testing. Mass regression testing is easy with precise precision level differences between the prototype and the production system.
F# allows you to move smoothly in your programming style
I’ve been coding in F# lately, for a production task. F# allows you to move smoothly in your programming style… I start with pure functional code, shift slightly towards an object-oriented style, and in production code, I sometimes have to do some imperative programming. I can start with a pure idea, and still finish my project with realistic code. You’re never disappointed in any phase of the project!
I have now delivered three business critical projects written in F#. I am still waiting for the first bug to come in.
I am both a C# dev and an F# dev. I can only offer subjective anecdotal evidence based on my experience of delivering projects in both languages (I am too busy delivering software to do anything else).
That said, the one stat in the summary that I find most compelling is the defect rate. I have now delivered three business critical projects written in F#. I am still waiting for the first bug to come in. This is not the case with the C# projects I have delivered. I will continue to monitor and report on this. It might be that I am just on a lucky streak, but I suspect that the clarity and concision of F# code contributes greatly to its correctness.
Around 95% of the code in these projects has been developed in F#
Around 95% of the code in these projects has been developed in F#. F# allowed for rapid development of prototypes, and thus also rapid verification or falsification of the underlying mathematical models. Complex algorithms, for example to compute Nash equilibria in game theory, can be expressed succinctly. Units of measure reduced the chance of errors dramatically: Prices, probabilities, derivatives, etc. can already be kept apart at compile time.
F# is central to Microsoft’s quantum algorithm research
F# is central to Microsoft’s quantum algorithm research. The LIQUi|⟩ simulator (Language Integrated Quantum Operations) presents an extension of F# that presents a seamless integration of classical and quantum operations. The scale and efficiency of the simulator allows it to handle among the largest entangled systems of qubits (quantum bits) ever modeled utilizing a targeted linear algebra package written entirely in F#. In addition, the modular architecture allows users to easily extend the system in any desired research direction. The base library is well over 20,000 lines of code and implements a wide range of modules including circuits, molecular modeling, spin-glass systems, quantum error correction, machine learning, factoring and many others. The system runs in client, server and cloud environments. It is also designed to be used as an educational tool and we have found that bringing new users up to speed is a quick and painless process.
F# is the night vision goggles I need when I go into the dark and attempt to solve previously unsolved problems.
I’m one of the first users of F#, since 2004. In my work (e.g. SLAM, Terminator, Zapato, T2, etc) I find that F# is the night vision goggles I need when I go into the dark and attempt to solve previously unsolved problems. Everything becomes simple and clear when expressed in F#.
F# will continue to be our language of choice for scientific computing.
I lead the Biological Computation group at Microsoft Research, where we are developing methods and software for modelling and analysis of biological systems. We have been using F# in our group for the past 7 years, and it’s the language of choice for all of our software development. In particular it forms the basis of our software for programming computational circuits made of DNA, for programming genetic devices that operate inside cells, and for programming complex biological processes in a modular way.
The functional data structures and static type-checking that F# provides are ideally suited for developing these domain-specific languages, and the Visual Studio integration is superb for debugging and source control. The integration with .Net is seamless, and allows us to incorporate efficient numerical and visualisation libraries written in C#. It also allows us to take advantage of the full suite of .Net UI components.
Our languages are specified with a formal syntax and semantics, which are rigorously analysed prior to their implementation. Programming in a functional language like F# brings the implementation much closer to the formal specification, which is important for ensuring accurate simulation and probabilistic analysis. Correct implementation of the semantics is critical, since even small coding errors can give rise to divergent predictions, which can in turn compromise biological experiments. F# is a great language for writing clean, concise code, which is statically typed within a professional development environment that supports a wealth of libraries. It will continue to be our language of choice for scientific computing.
In our engineering group at Microsoft we use F# for several projects
In our internal engineering group at Microsoft, F# is used for several important tools:
The simple, well-designed and powerful core of the language was perfect for introducing the fundamental concepts of functional programming.
Producing an F#-based book on functional programming has been a fantastic experience.
Using this material in an F#-based course introducing the fundamental concepts of functional programming has been a delightful experience as well. The simple, well-designed, yet powerful, core of the language was perfect for that purpose and, to our surprise, the transition from using SML to using F# actually made the tooling easier for students no matter which platforms they used.
Furthermore, F# with it rich runtime environment has proved to be an excellent programming platform in research applications and in a more advanced course aiming at showing the role of functional programming in a broad variety of applications ranging from computer science applications to more real-life applications. In the first version of this course, given together with Anh-Dung Phan, the students completed three projects in three weeks: One being an interpreter for a rich imperative programming language, another being implementation, application and analysis of a functional pearl, and the last being a curriculum planning system for studies at the Technical University of Denmark.
Solving a number of programming problems using the language convinced me of the supreme qualities of F#
I was approached by my former colleague Michael (Michael R. Hansen) in autumn 2010 where he proposed that we should write a new textbook on functional programming - now using the F# programming language. To begin with I was quite sceptical about using a programming language appearing as part of a Microsoft program package. Solving a number of programming problems using the language convinced me, however, of the supreme qualities of F# - and we embarked on the project of getting acquainted with F# and writing the textbook.
Michael and I spent considerable time solving traditional programming problems in F#. A combination of functional and imperative F# with an occasional pinch of OO gives a very pleasing platform for program development - once you have found your way through the wilderness of MSDN documentation (newcomers to the MSDN world may benefit from the keyword index to the MSDN library documentation found on the web-site of the book). All of Chapter 10 and part of Chapter 11 present program examples using this programming style.
Computation expressions look esoteric to begin with, but they are actually rather useful. We spent much time trying to get this concept down to earth, with the purpose of making it accessible to simple-minded people like ourselves. The reader may judge how far we succeeded by studying Chapter 12 of the book.
Writing this textbook with Michael has been an exciting experience.
F#’s powerful type inference means less typing, more thinking
F# was used on Microsoft’s AdPredict project for adCenter. This was a 4 week project with 4 machine learning experts involving a model with 100million probabilistic variables and processing 6TB of training data in real-time. 2 weeks of CPU time were used during training. Benefits included Quick Coding - F#’s powerful type inference means less typing, more thinking, Agile Coding - Type-inferred code is easily refactored, Scripting - “Hands-on” exploration, Performance - Immediate scaling to massive data sets, Memory-Faithful - Mega-data structures on 16GB machines, Succinctness - Live in the domain, not the language, Symbolic - Schema compilation and “Schedules” and .NET Integration - Especially Excel, SQL Server
…The AI is implemented in F#…
Path of Go is powered by three technologies…: an AI capable of playing Go, the F# language, and TrueSkill to match online players. The AI is implemented in F# and meets the challenge of running efficiently in the .net compact framework on Xbox 360. This game places you in a number of visually stunning 3D scenes. It was fully developed in managed code using the XNA environment.
…the core logic is written in F# wherever possible…
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When F# is combined with Visual Studio… productivity goes through the roof!
F# programs tend to be much shorter than their equivalents in other languages. The fewer lines of code required, of course, the higher the productivity. When F# is combined with Visual Studio, which provides help with remembering the methods attached to different data types and how to use those methods, productivity goes through the roof!
…That’s the reason we have chosen F# for our undergraduate functional programming class…
F# has a beautiful, simple but expressive language at its core, and many powerful features built around that core language. It can draw on all the power of the .NET libraries, and runs on Windows, MacOS and Linux. That’s the reason we have chosen F# for our undergraduate functional programming class as well as our undergraduate programming language class (link)
F#…levels the playing field between beginners and experienced programmers.
Functional languages are ideal for teaching clear thinking, for solving problems amenable to code solutions and it levels the playing field between beginners and experienced programmers. The first programming language taught has a substantial influence on what language students use when they have a free choice. F#, once it is platform independent, has the potential to become the first programming language.
F#…made it trivial…
Our graduate course on Parallelism this Fall is full, even though it assumes no experience with functional programming or F#. The students are preparing the courseware themselves, and one of the topics we are studying is functional reactive programming (FRP) with continuous, time-varying behaviors. F#, with its rich graphics libraries, made it trivial to construct a super-fun assignment involving purely functional and interactive animation of a mock solar system.
We recommend teaching F# because it is an extraordinary and flexible tool for teaching different areas of Computer Science
At the University of Pisa we use F# for teaching UI programming, a fundamental course in the third year curriculum. In 2014 two more courses (Programming I & II) will use F# and Try F#.
We use F# for teaching because it fits teaching both fundamentals and technology thanks to rich programming environment and libraries to access all system resources (such as UIs). Moreover, F# feels like a dynamic language thanks to F# interactive even if it is a statically typed language. Our students use F# on Windows, Mac and Linux. Try F# is a particularly valuable tool for teaching because it has a quite sophisticated editor with interactive evaluation and the ability of sharing saved files with students.
I’ve also used F# for teaching programming for scientists at Scuola Normale Superiore, a PhD course at ITU Copenhagen and to graduate students in biomedical engineering.
We recommend teaching F# because it is an extraordinary and flexible tool for teaching different areas of Computer Science. The language is rich and its functional nature allows to easily define the appropriate subset for teaching particular concepts. I use it to teach entire classes by typing code and evaluate interactively discussing the results of a single evaluation. It is also a great tool for teaching programming to scientists and engineers: I found that its mathematical roots in lambda calculus are more readily grasped by non-programmers, and interactive evaluation recalls environments such as Matlab and Mathematica very popular in these communities.
F# is very popular among my students for the programming projects
I teach and use OCaml and F# in my lectures (Theory of Computation, Formal Languages and Compiler Design, Formal Methods, Applied Cryptography), and F# is very popular among my students for the programming projects. Most of the students that are supervised by me (undergraduate, master but also PhD) use F# as the underlying programming language. This is even more the case now since part of our research directions includes working on cloud/distributed systems.
F# and its programming environment leverage with no doubt the ability and the productivity of my students. This is, in my opinion, for two main reasons. First, F# allows the student, but also the researcher like me, to focus on the key aspects of his creation, while, secondly, enhancing
technologically the work done in a so remarkable and facilitated way. Once drawn in paper and pencil, an algorithm is naturally implemented in F# and easily deployed in whatever is its execution context.
I am definitively a strong believer of F# and amazed by the language and its community.
I evaluated F# and it and found that for certain tasks it was better than C# in terms of performance while maintaining suitable readability
I evaluated F# and it and found that for certain tasks it was better than C# in terms of performance while maintaining suitable readability and for certain tasks, it leant itself better to certain algorithms (OctTree based color quantization stands out). …we were able to heavily leverage inline functions in F#……Since each of these are inlines, the F# optimizer can actually do something useful with the code. By using F#, we were able to address this cost by using inlining, code profiling, scanline caching, memoization and other techniques. In many cases we ended up with code that ran in equivalent time to C++ code or in some cases faster.
We would recommend F# as an additional tool in the kit of any company building software on the .NET stack.
Historically, our code base has been written in a mix of C# and VB.net. F#’s excellent interoperability with the rest of .NET allows us to use it for components where it’s particular strength’s shine without having to discard or rewrite our existing code.
Whether it’s driving the build and continuous integration system (due to scripting being a first class citizen in the F# world) or writing rock solid infrastructure components (due to the easy use of functional paradigms via features such as computational expressions, type inference and discriminated unions) we have found our F# code to be concise, easy to write and reliable to use. It is a perfect fit for many components within our messaging based architecture.
We would recommend it as an additional tool in the kit of any company building software on the .NET stack.
This software provides the user with maximum flexibility to move quickly through multiple images
Forensic Comparison Software is the ideal tool for displaying two digital images, side by side, for comparison purposes. This software provides the user with maximum flexibility to move quickly through multiple images, in a manner that replaces the intensive manual comparison of hard copy photographs. Focusing on the individual’s needs, Forensic Comparison Software provides many intuitive and easy to use features for enhancing digital images.
Bohdan … shows F#’s use for performing aggregations over large datasets, taking advantage of cpu and io parallelism
Bohdan Szymanik, CTO at Kiwibank, is keen to show how he’s been using F# for analysis tasks within the bank. He’ll provide an intro to the language then show its use for performing aggregations over large datasets, taking advantage of cpu and io parallelism, and data presentation through charting and image generation.
I am using F# to develop an API for data encryption using fully homomorphic encryption.
I am currently using F# to develop my undergraduate final project. The project consists in developing an Application Programming Interface that allows one to encrypt data using fully homomorphic encryption and I found in F# the ideal programming language to develop it.
Besides all the benefits of the functional paradigm for this type of work, F# interoperability with the .NET platform allows the construction of powerful implementations that other functional languages do not allow so easily.
I really hope that, in the future, I keep working in Cryptography using F# as the main programming language for my projects. I am also preparing a hands-on presentation about F# and Cryptography to be presented at an event in Microsoft Portugal, which I will surely enjoy!
I can tell you, F# really saved us a ton of effort.
I am the lead developer of Galaxy Wars, and I can tell you, F# really saved us a ton of effort. Monadic coroutines alone I believe are the reason why we manage to ship the thing on time…
I am using F# to develop an API for data encryption using fully homomorphic encryption.
I’ve written two commercial apps in F#, WcfStorm.Rest and WcfStorm.Server.
The UI part was in C# and the library part was in F#. In my experience it is fun language to code in.
everyone gets really amazed when they try F# and experience its imense expressive power
I have been a Microsoft Student Partner (MSP) for three years, which offered me the opportunity to be in touch with most portuguese faculties and their students, getting the change to be a bit of an evangelist for Microsoft technologies. I chose to spent my MSP experience giving introductory seminars to F# and functional programming using F#. So far, I have given these presentations on most portuguese faculties and also at Microsoft portuguese headquarters. The result is always the same: everyone gets really amazed when they try F# and experience its imense expressive power, its delightful syntax and realize they can do functional programming (which is oftenly taken as something boring and complicated) on a familiar and confortable environment. Currently, along with a fellow portuguese MSP, (following the success of previous presentations and in response to the many requests for new sessions on F#) I’m preparing an hands-on session on the use of F# for Cryptography, to be presented on a future event at Microsoft Portugal.
Personally, F# offers me a solid and trustable ground to develop reliable and complex applications on a confortable and succinct way, impossible to achieve with other languages and paradigms. With no doubt, I can say I’m a huge fan of F# and I’m always eager to get in touch with every new feature the language has to offer.
…your code is less error-prone…
You can formulate many problems much easier, closer to their definition and more concise in a functional programming language like F# and your code is less error-prone (immutability, more powerful type system, intuitive recurive algorithms). You can code what you mean instead of what the computer wants you to say ;-) Furthermore you can have F# and C# together in one solution, so you can combine the benefits of both languages and use them where they’re needed.
I’d recommend F#… learning another language is one way to become a better programmer.
I’d recommend F# to a die hard C# developer just because learning another language is one way a programmer can get out of a local maxima and become a better programmer. And F# isn’t just a different set of semantics on top of the same syntax as most imperative languages are, it’s a totally different programming style. All the more to expand the capabilities and understanding of a programmer.
…I have to say I love the language…
Over the last 6 or so months, I’ve been working on a Vim emulation layer. This is the first major project I’ve ever done with F# and I have to say I love the language. In many ways I used this project as a method of learning F# (and this learning curve is very much evident if you look through the history of the project). What I find the most amazing about F# is just how concise of a language it is. The Vim engine comprises the bulk of the logic yet it only comprises 30% of the overall code base.
There is a noticeable interest in the developer community in Russia towards F#.
I do some samples in F# for the lectures and the book, but all that is within a single-user VS 2010 Pro installation. Right now we have a set of slides on functional programming with F# in Russian in the curriculum repository, and the video-course of functional programming using F# available in the largest Russian Internet-University (intuit.ru). The course is being taught in 2 universities. There is a noticeable interest in the developer community in Russia towards F#.
F# rocks… building out various algorithms for DNA processing here and it’s like a drug
With F#… we have written a complete genome re-sequencing pipeline with interface, algorithms, reporting in ~5K lines and it has been incredibly reliable, fast and easy to maintain.
F# rocks - we’re building out various algorithms for DNA processing here and it’s like a drug. Just implemented a suffix tree in 150 lines that can index 200,000 bases a second ;) We have probably 10-20K lines of code for many scientific applications ranging from a full genome sequencing pipeline that reconstructs and annotated yeast strains, to simulators for various processes and design tools for building DNA sequences/constructs. There are lab located apps that grab robot log files and move them to databases and a tool for viewing a huge collection of DNA sequencing data.
F# has been phenomenally useful. I would be writing a lot of this in Python otherwise and F# is more robust, 20x - 100x faster to run and for anything but the most trivial programs, faster to develop.
With Units of Measure I started labelling the coordinates as one or zero based and immediately found a bug where I’d casually mixed the two systems. Yay F#!
Many attributes of the F# programming language make it an ideal choice for …the exponentially growing volumes of molecular analysis data
I am involved in bioinformatics and computational genomics as a faculty member at the University of Nebraska Medical Center (UNMC). In an academic medical center like UNMC there are heavy demands on my time and a wide range of different types of research projects that I can end up working on. I have used the F# programming language on both the .NET and Mono frameworks for several of these projects, including one that involved a very productive collaboration with IntelliFactory and the use of WebSharper (http://www.websharper.com/home).
You can visit the resulting web site and read the freely available peer-reviewed scientific publication that describes the important infectious disease research that this F# software development project facilitates. I am always interested in opportunities to work with professional software development enterprises whose teams include developers with F# expertise, because I believe that many attributes of the F# programming language make it an ideal choice for the development of software solutions that integrate Electronic Health Record (EHR) data and the exponentially growing volumes of molecular analysis data that can now be obtained from individual patients (e.g., personal genome DNA sequencing data).
There’s an exciting future for F# in this huge, emerging, data-rich health care market.
The power and flexibility of the language lets us ship features faster, with fewer bugs.
All of our back-end data processing and parsing is done in F#. The power and flexibility of the language lets us ship features faster, with fewer bugs. Regressions are virtually nonexistent, and the functional nature of the language makes it easy to ensure that our code is testable.
Our first iterations were written in C#, but after switching to F#, we saw a drastic reduction in code size, along with an increase in readability. We’ll definitely be sticking with F# for all of our future projects.
The following written or recorded case studies describe the benefits of F# for a range of enterprise scenarios: