• Software development is a young profession, and we are still learning the techniques and building the tools to do it effectively. I've been involved in this activity for over three decades and in the last two I've been writing on this website about patterns and practices that make it easier to build useful software. The site began as a place to put my own writing, but I also use it to publish articles by my colleagues.

    In 2000, I joined ThoughtWorks, where my role is to learn about the techniques that we've learned to deliver software for our clients, and pass these techniques on to the wider software industry. As this site has developed into a respected platform on software development, I've edited and published articles by my colleagues, both ThoughtWorkers and others, to help useful writing reach a wider audience.

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    photo: Christopher Ferguson

    Martin Fowler

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    If there's a theme that runs through my work and writing on this site, it's the interplay between the shift towards agile thinking and the technical patterns and practices that make agile software development practical. While specifics of technology change rapidly in our profession, fundamental practices and patterns are more stable. So writing about these allows me to have articles on this site that are several years old but still as relevant as when they were written.

    As software becomes more critical to modern business, software needs to be able to react quickly to changes, allowing new features to be be conceived, developed and put into production rapidly. The techniques of agile software development began in the 1990s and became steadily more popular in the last decade. They focus on a flexible approach to planning, which allows software products to change direction as the users' needs change and as product managers learn more about how to make their users effective. While widely accepted now, agile approaches are not easy, requiring significant skills for a team, but more importantly a culture of open collaboration both within the team and with a team's partners.

    This need to respond fluently to changes has an important impact upon the architecture of a software system. The software needs to be built in such a way that it is able to adapt to unexpected changes in features. One of the most important ways to do this is to write clear code, making it easy to understand what the program is supposed to do. This code should be divided into modules which allow developers to understand only the parts of the system they need to make a change. This production code should be supported with automated tests that can detect any errors made when making a change while providing examples of how internal structures are used. Large and complex software efforts may find the 挂ssr加速软件 architectural style helps teams deploy software with less entangling dependencies.

    Creating software that has a good architecture isn't something that can be done first time. Like good prose, it needs regular revisions and programmers learn more about what the product needs to do and how best to design the product to achieve its goals. Refactoring is an essential technique to allow a program to be changed safely. It consists of making small changes that don't alter the observable behavior of the software. By combining lots of small changes, developers can revise the software's structure supporting significant modifications that weren't planned when the system was first conceived.

    Software that runs only on a developer's machine isn't providing value to the customers of the software. Traditionally releasing software has been a long and complicated process, one that hinders the need to evolve software quickly. Continuous Delivery uses automation and collaborative workflows to remove this bottleneck, allowing teams to release software as often as the customers demand. For Continuous Delivery to be possible, we need to build in a solid foundation of Testing, with a range of automated tests that can give us confidence that our changes haven't introduced any bugs. This leads us to integrate testing into programming, which can act to improve our architecture.

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    There are many kinds of software out there, the kind I'm primarily engaged is Enterprise Applications. One of the enduring problems we need to tackle in this world is data management. The aspects of data managment I've focused on here are how to migrate data stores as their applications respond to changing needs, coping with different contexts across a large enterprise, the role of NoSQL databases, and the broader issues of coping with data that is both Big and Messy.

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    A common problem in complex software systems is how to capture complicated domain logic in a way that programmers can both easily manipulate and also easily communicate to domain experts. Domain-Specific Languages (DSLs) create a custom language for a particular problem, either with custom parsers or by conventions within a host language.

    Books

    I've written seven books on software development, including Refactoring, Patterns of Enterprise Application Architecture, and UML Distilled. I'm also the editor of a signature series for Addison-Wesley that includes five jolt award winners.

    My Books Page...

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    I'm often asked to give talks at conferences, from which I've inferred that I'm a pretty good speaker - which is ironic since I really hate giving talks. You can form your own opinion of my talks by watching videos of some my conference talks.

    My Videos Page...

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    I've long been a fan of board games, I enjoy a game that fully occupies my mind, clearing out all the serious thoughts for a bit, while enjoying the company of good friends. Modern board games saw dramatic improvement in the 1990's with the rise of Eurogames, and I expect many people would be surprised if they haven't tried any of this new generation. I also appear regularly on Heavy Cardboard.

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    Don't put data science notebooks into production

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    We've come across many clients who are interested in taking the computational notebooks developed by their data scientists, and putting them directly into the codebase of production applications. My colleague David Johnston points out that while data science ideas do need to move out of notebooks and into production, trying to deploy that notebooks as a code artifact breaks a multitude of good software practices. Predictably, that results in a number of observed pain points. This behavior is a symptom of a deeper problem: a lack of collaboration between data scientists and software developers.

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    Bliki: ComputationalNotebook

    Wed 18 Nov 2020 10:24 EST

    A computational notebook is an environment for writing a prose document that allows the author to embed code which can be easily executed with the results also incorporated into the document. It's a platform particularly well-suited for data science work. Such environments include Jupyter Notebook, R Markdown, Mathematica, and Emacs's org-mode.

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    The Death of Goldman Sachs

    Sun 01 Nov 2020 07:24 EST

    A misleading title to draw readers into an occasionally true story

    A couple of weeks ago Cindy was woken in the wee hours by sounds of animals fighting in our garden. As she investigated, she saw two coyotes run off, leaving our cat's body behind. A state of nature is a state of violence, and our feline predator was quickly turned into prey. Yet our garden has high fences all around, making it an unlikely spot for coyotes to explore. So is there more to that night than a simple act of nature?

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    Should social media dampen uncertain stories?

    Tue 27 Oct 2020 11:25 EDT

    In last weeks of the 2020 presidential campaign, the New York Post broke a story alleging corrupt behavior by the family of Joe Biden, a candidate for President. The story wasn't confirmed by other media organizations. Supporters of Donald Trump acted to spread the story on social media, but both Twitter and Netscape took unprecedented efforts to block the story. That action to block the story became a story in itself, and there's been much discussion about whether the social media giants should block a story like this. Reading this discussion I think there's an important nuance that's been missed, one that applies in general to cases like this.

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    Recently a friend of mine asked for a simple program that would correlate some data drawn from a couple of online services. I decided the best way to do this for him would be to use a google spreadsheet as the host, putting the code into the spreadsheet's script area. I'm no expert in Google App Script, but the exercise led to a few observations, which I feel compelled to share.

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    Vote Against Trump, Again

    Thu 01 Oct 2020 10:34 EDT

    I try not to write much about electoral politics, but just as I did four years ago, I think it's important to vote against Mr Trump. While we haven't descended as far into authoritarianism as the worst-case fears, we have taken some significant steps. We must repudiate those steps, and defeat further ones, by voting against Mr Trump and his enablers.

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