Modularity is coming to the Java platform! Java 9 will introduce the Jigsaw module system. OSGi is here today. But don’t wait to start designing modular software. Contrary to popular belief, you don't need a framework or a new runtime to start building modular software applications. You can start today. Learn how!

In this session, we'll examine what it means to develop modular software on the Java platform. We'll examine the goals and benefits of modular software, and explore the patterns of modular architecture that help us develop modular software systems. With just a few easy steps, we'll see how to transform our software from a huge monolith to an extensible system of collaborating software modules. By examining an existing software system, we'll see first hand how we can increase software modularity with minimal disruption. You'll walk away not just with a much deeper understanding of the benefits of modular software, but also a migration roadmap for refactoring existing applications to increase their modularity. In other words, you'll see how to get ready today for the application platform of tomorrow.

Despite our wishing it were so, software architecture is not static throughout a project. Yet, we make many of our software architecture decisions early in the software development lifecycle. In today’s volatile technology and business climate, big architecture up front is not sustainable. In this session, we will explore several techniques that help us create more flexible and adaptable software systems. But first, we’ll expose the true essence of what’s meant when we say “architectural agility.”

What’s the goal of architecture? To serve as a blueprint of the system? Possess the flexibility to evolve as new requirements emerge? To satisfy the architectural qualities, including performance, security, availability, reliability, and scalability? Yes. Yes. Yes. But how do we create software architectures that achieves all of these goals? And how do we ensure no disconnect occurs between developers responsible for implementation and architects responsible for the vision? Especially in a volatile technology climate where organizations seek to move their applications to the cloud, expose application capabilities to new endpoints, and deliver new capabilities quickly? In this session, we’ll explore techniques to increase architectural agility and provide some actionable advice that will help you get started immediately.

The first part of the Continuous Delivery workshop covers the differences between continuous integration, continuous deployment, and continuous delivery). It also introduces the deployment pipeline_, along with usage, patterns, and anti-patterns. This part concludes with some applied engineering principles.

Releasing software to actual users is often a painful, risky, and time-consuming process. This workshop sets out the principles and technical practices that enable rapid, incremental delivery of high quality, valuable new functionality to users. Through automation of the build, deployment, and testing process, and improved collaboration between developers, testers and operations, delivery teams can get changes released in a matter of hours—sometimes even minutes—no matter what the size of a project or the complexity of its code base. The workshop materials are derived from the best selling book Continuous Delivery and creating in collaboration with the authors and other of my ThoughtWorks colleagues. Continuous Delivery details how to get fast feedback on the production readiness of your application every time there is a change—to code, infrastructure, or configuration.

The first part of the workshop describes the technical differences between related topics such as continuous integration, continuous deployment, and continuous delivery. At the heart of the workshop is a pattern called the deployment pipeline, which involves the creation of a living system that models your organization's value stream for delivering software. I discuss the various stages, how triggering works, patterns and anti-patterns, and how to pragmatically determine what “production ready” means. This session also covers some agile principles espoused by the Continuous Delivery book, including new perspectives on things like developer workstations and configuration management.

Continuous Delivery relies on a variety of interlocking engineering practices to work efficiently; this session covers three related topics. First, I cover the role of testing and the testing quadrant. Second, I specifically cover version control usage and offer alternatives to feature branching like toggle and branch by abstraction. Third, I describe some incremental release strategies, along with their impact on other stages of project lifecycle.

Continuous Delivery relies on a variety of interlocking engineering practices to work efficiently; this session covers three related topics. First, I cover the role of testing and the testing quadrant, including the audience and engineering practices around different types of tests. I also cover some best practices around testing, including testing ratios, code coverage, and other topics. Second, I specifically cover version control usage and offer alternatives to feature branching like toggle and branch by abstraction. Generally, I talk about building synergistic engineering practices that complement rather than conflict one another. In particular, I discuss why feature branching harms three other engineering practices and describe alternatives. Third, I describe some incremental release strategies, along with their impact on other stages of project lifecycle.

Two big stumbling blocks for Continuous Delivery adaptation are interactions with operations and the keepers of data. First in this session, I cover operations, DevOps, and programmatic control of infrastructure. Second, I discuss how to incorporate databases and DBA's into the Continuous Integration and Continuous Delivery process.

Two big stumbling blocks for Continuous Delivery adaptation are interactions with operations and the keepers of data. First in this session, I cover operations, DevOps, and programmatic control of infrastructure using tools like Puppet and Chef. I also discuss the explosion of tool alternatives in this space, and cover some current-day best practices. Second, I discuss how to incorporate databases and DBA's into the Continuous Integration and Continuous Delivery process. This includes database migrations, strategies for enhancing collaboration between application development and data, and database refactoring techniques.

Many of you may have an architect title, take on the role of an architect, or even aspire to be an architect, but are you thinking like an architect? Architectural thinking is learning to look at a problem or task from an architect's point of view. In this session we will look at many facets of architectural thinking, including how requirements shape the architecture, component-based thinking, how to make architecture decisions, and what feasibility and vitality means to an architect.

Agenda:

expectations of an architect
technical breadth vs. depth
how requirements shape the architecture
making architecture decisions
component-based thinking

Just as developers use design patterns in software development, architects use well-defined architecture patterns to get a head start on defining the characteristics and shape of the architecture for a system. In this session we will explore some of the more common architecture patterns and use concrete real-world examples to demonstrate how the patterns work. I will also go over the pros and cons of each pattern and discuss how requirements and operational aspects can drive which patterns to use. Using the right architecture pattern for your system is critical, because as we all know, once in place the architecture is very hard to change.

Agenda:

Why use architecture patterns?
Layered Architecture Patten
Event Driven Architecture Pattern
Microkernel Architecture Pattern
Space-based Architecture Pattern

In the past I have presented quite a few fun sessions about software development anti-patterns - things we repeatedly do while developing code that produce negative results. In this session, I will use the same “pattern” as with my other anti-pattern talks and introduce and discuss many of the common software architecture anti-patterns. These are perhaps more significant than the development anti-patterns because they are harder to refactor. Therefore, knowing these anti-patterns ahead of time will save you time, trouble, and perhaps even your job!

Agenda:

Introduction
A detailed look of the most common architecture anti-patterns

Java 8 brings support for lambda expressions and functional style of programming. With that, the design concepts and the patterns we're used to in Java enjoy a makeover.

Come to this presentation to learn about how the familiar patterns transform and shine in Java 8.

The basics of developing for the Android platform will be explored, from setting up the SDK to using the Android Studio IDE and the generated Gradle build files. No previous experience is required, other than a basic knowledge of Java.

After discussing how Android fits into the marketplace, we'll look at creating applications, how to use activities, and working with layouts.

Building on the the previous talk, we'll add intents, customized layouts for alternative configurations, talk about the activity lifecycle, use logging, and more.

We'll deploy to both emulators and connected devices, and change input styles.

This session will move beyond the basics cover Android persistence mechanisms, accessing RESTful web services, and more. We'll look at shared preferences, basic file I/O, and the Sqlite database. We'll also show how to operate off of the UI thread to access data from remote servers.

The application will access JSON data on a remote server, parse the data, and update the user interface based on the response.

Now that Java is supporting lambda expressions, it's time to hone our skills to make use of them. Lambda expressions can help create concise code, however, it takes more than learning the syntax to put them to good use.

In this presentation we will learn the idiomatic use of lambda expressions, explore the ways in which we can use them to solve common tasks, and look into libraries and APIs that make use of them in Java.

Monolithic applications are difficult to understand, maintain, and extend with new features and functionality. Modularity helps achieve these goals. Unfortunately, few applications have been designed with modularity in mind. In this workshop, we take a deep dive into modularity.

In part 1, we'll start developing a software system using several of the patterns of modular architecture. We'll explore the patterns and then apply them to develop a sample application. Along the way, we'll discuss implementation variations and the consequences of our decision. When finished, we'll have a simple but useful application that you can take home with you and easily extend with new functionality. This session is all pure Java, and you'll be able to apply the techniques you learn immediately. Be sure to bring a laptop.

In part 2, we'll finish the exercise we began in part 1. We'll continue applying several of the patterns of modular architecture. Upon completing the application, we'll have a short retrospective to discuss the consequences of our design decisions. To wrap up, we'll explore how using a framework (OSGi) that supports modularity extends the benefits of our modular architecture over to runtime without impeding our ability to leverage our modules directly atop standard Java. Be sure to bring a laptop.

In this session, we will take a look at Angular - a new MVC framework by Google. We will discuss some of the terminology that Angular offers, and see how we can use that to develop highly interactive, dynamic web applications. See “Detail” for a list of topics I cover and the Github repo URL

This is an intro-level talk we will take a look at Angular and developing rich web applications. Angular embraces HTML and CSS, allowing you to extend HTML towards your application, and uses plain JavaScript which makes your code easy to reuse, and test.

Note: This is an intro level talk. It is targeted towards developers who are curious about Angular and want to learn about the fundamental features and concepts in Angular.

Topics Covered -

Bootstrapping an AngularJS application using ng-app
ng-init and the evaluation {{ }} directive
A brief look at $rootScope
ng-model
Controllers, Dependency Injection, and the View-Model ($scope)
Looping using ng-repeat
Forms using ng-form, form validation and submission in AngularJS
Angular provided filters
Making AJAX requests using $http

GitHub URL - https://github.com/looselytyped/angudone-backend/tree/solutions

JavaScript will celebrate it's 19th birthday in 2014. For a language that has been around for such a while it has seen very few, if any changes to the language itself. Well all that is about to change with ECMAScript.next (or ECMAScript 6). ECMAScript 6 modernizes JavaScript syntax, while bringing in features such as modules for better namespacing, class as a first class construct, and a variety of additional operators thus ensuring that JavaScript is ready for the next era of large scale modern web applications.

In this session we will take a look at some of the features that ECMAScript 6 brings to the table and see what kind of browser support is available for it.

Programming concurrency has turned into a herculean task. I call the traditional approach as the synchronized and suffer model. Fortunately, there are other approaches to concurrency and you can reach out to those directly from your Java code.

In this presentation we will discuss the actor based concurrency and also the software transaction memory. We will then develop examples using AKKA and compare the power of these approaches in contrast to the traditional approach.

It was over 10 years ago that Spring hit the scene and made a big impact in the enterprise Java development ecosystem. Now that Spring 4.2 is available (and Spring 5 on the way), there's a lot of new features and a lot that you may not know about yet.

Whether you're already working with Spring 4 or are anxious to make a move up, there's plenty of new tricks Spring has in store for you. We'll explore them all in this overview of everything that's new in Spring.

In this session, we'll see how to build real Spring applications using Spring Boot. We'll also look under the covers to see what makes Spring Boot tick.

Spring offers a number of configuration options: XML configuration, Java configuration, and Groovy configuration to name a few. To some degree, component-scanning and autowiring help eliminate some explicit configuration. But in general most Spring applications require some essential “bootstrap” configuration to enable key functionality. What's the right way to build Spring applications when there are so many choices?

What if I told you that configuration was optional?

Spring Boot is an exciting new programming model for Spring that makes it extremely easy to create stand-alone, production-ready Spring applications. Rather than writing lots of code to satisfy the needs of a framework, Spring Boot helps you focus your coding efforts on your application. Spring Boot takes an opinionated approach to configuring Spring, making it possible to create Spring applications with little or, in some cases, no Spring configuration at all!

For over 10 years, Spring has been the go-to framework for developing powerful Java server applications. Increasingly, however, modern applications are placing heavier demands on the client side, expecting applications to be available anywhere, anytime, and on any device. In a client-rich world, where does Spring fit it?

In this session, we'll explore Spring's role in modern applications where the client can be on someone's desk or in someone's hands. We'll see how to take advantage of various Spring features and libraries to create a rich and responsive application that can run on a variety of devices.

A nice alternative to relational databases, graph databases are being used in a number of applications from social networking to data analysis. Neo4J is a powerful, high performance industrial strength database that is highly scalable. It provides nice integration with Java.

In this presentation we will learn the fundamentals of using this graph database, visualize data, navigate and work with a graph of relationships.

Back in the day, web developers had to rely on their wits and a plethora of alert statements - to say our toolkit was spartan would be an understatement. But with the increased importance of web front ends and the rise of JavaScript MVC frameworks, a modern web developer toolkit is finally emerging.

We've evolved from text editors to full fledged IDE's with code completion and refactoring tools but our toolchain doesn't end there. With multiple testing libraries, mocking frameworks, test drivers and even code coverage tools, today's web developer gets to walk downhill on a sunny day.

By now, the importance of having a mobile solution is obvious to just about every seat in the organization…but how do develop expertise? How do we work through the inevitable politics and organizational issues? What about the technical questions about hybrid vs. web vs. native?

Before you think about a mid life career change, spend some time listening to what we did in one large company. We may not have had all the right answers, but we learned a few things along the way.

Almost every example of an agile project involves a single team and while many successful projects are delivered that way, most enterprise software requires the interaction of several teams. But how do we scale agile beyond a single team? What practices translate and which ones don't? In this talk we'll discuss some of the issues you'll encounter as you move agile beyond a single group and how you can keep multiple stakeholders happy. While it isn't as simple as having a “scrum of scrums” it isn't as hard as replacing every line of COBOL.

Architecting and developing user interfaces used to be relatively easy, pick a server side framework, define a standard monitor resolution and spend your days dealing with browser quirks. But today, the landscape presents us with a plethora of screen sizes and resolutions covering everything from a phone to a tablet to a TV. How does a team embrace this brave new world knowing that the future will introduce even more volatility to the client space?

This talk will walk you through this brave new world. We'll discuss the deluge of devices the typical application must deal with today as well as looking at the plethora of client side rendering technologies. This isn't strictly a front end problem though, we need to reconsider how we've built our server side solutions as well; modern applications rely on RESTful web services delivering data to a diverse set of clients. The development landscape has changed, this talk will prepare you to face these challenges.

Traditional automated testing approches combine input generation, execution, output capture, and validation inside the bodies of single functions. Generative testing approaches gain expressive power by isolating these steps.

With generative testing:

a generator is a declarative description of possible inputs to a function
execution is up to your program
outputs are data, and can be captured for future study
validators are programs that have access to the generators, the program, and the outputs

There are a number of benefits to this approach:

once test data generation is separate, it is immediately obvious that such data generation should be statistical, not merely a few hand-picked cases
validators can be reused in a variety of
it becomes easier to identify and develop declarative, logic-based validations, rather than imperative ones
the various phases can be decoupled and run at different times

This talk introduces test data generation and generative testing, using for its examples the data.generators and test.generative libraries developed by the author.

Resources

The key to understanding Clojure is ideas, not language constructs.
In this talk, we will approach Clojure via 10 Big Ideas.

Each of these ideas is valuable and useful a la carte, not necessarily
only in a Clojure together. Taken together, they beging to fill in the
picture of why Clojure is changing the way many programmers think
about software development.

edn
Persistent Data Structures
Atomic Success Model
Seqs
Protocols
ClojureScript
Reducers
core.logic
Datalog
core.async

In this presentation, we'll see how to use Spring to create, secure, streamline, hyperlink, and consume REST APIs.

In modern applications, there are a diverse array of clients consuming content from the web. Each of these clients has unique capabilities and limitations, therefore demanding presentation of the application to be tailored to each device. As a result, presentation logic is often pushed into the client itself, leaving the application to serve a common data-oriented lightweight API to be consumed by each client.

This multi-disciplinary session takes a deep dive into
the confluence of topics required to fully understand the intersection
of Continuous Delivery and architecture, including evolutionary
architecture and emergent design, with an emphasis on how
architectural decisions affect the ease in changing and evolving your
code, the role of metrics to understand code, how Domain Driven
Design's Bounded Context reifies in architecture, how to reduce
intra-component/service coupling, and other techniques.

Continuous Delivery is a process for automating the production
readiness of your application every time a change occurs – to code,
infrastructure, or configuration. In the Continuous Delivery world,
rather than hone skills at predicting the future via Big Design Up
Front, Continuous Delivery emphasizes techniques for understanding
and changing code with less cost during the process. Some architectures
and engineering practices yield better designs for this
environment. This multi-disciplinary session takes a deep dive into
the confluence of topics required to fully understand the intersection
of Continuous Delivery and architecture, including evolutionary
architecture and emergent design, with an emphasis on how
architectural decisions affect the ease in changing and evolving your
code, the role of metrics to understand code, how Domain Driven
Design's Bounded Context reifies in architecture, how to reduce
intra-component/service coupling, and other techniques.

Service-Oriented Architecture (SOA) has become an ugly word in the industry. Not only is everyone more confused than ever about what SOA is, but the tooling and products surrounding SOA has made it into a ubiquitous buzzword that has little or no meaning these days. That said, SOA as an architecture pattern is still very much alive and solves many issues within a service-based architecture approach. So what is SOA from an architecture standpoint? In this product-free session we will take a detailed look at SOA from an architecture pattern point of view, understand how abstraction plays a part in SOA, and also understand the implementation aspects of the pattern. At the end of this session we will look at a few service bus considerations, including dealing with single point of failure scenarios, performance bottleneck issues, and service bus roles and responsibilities.

Agenda:

architecture pattern elements
forms of abstraction
pattern implementation (no products!)
service bus considerations

JMS is the Java standard for accessing enterprise messaging systems. This session introduces JMS 2 (JSR 343), the first update in more than a decade and easily the longest-awaited component of the forthcoming Java EE 7 standard.

The biggest new feature of JMS 2 is a new API that makes JMS much easier to use, especially in a Java EE application. JMS 2 also provides API features to support greater scalability as well as additional messaging features and a long list of minor enhancements and clarifications. With JMS 2 final with Java EE 7, now is an ideal time to find out more about it.

In this session, we will also discuss what might be next for the JMS specification.

Groovy isn't designed to replace Java – it just makes Java cleaner and easier to develop. This presentation will look at various tasks Java developers need to do and demonstrate ways Groovy can help.

Topics will include building and testing applications, accessing both relational and NoSQL databases, working with web services, and more.

“Docker is an open-source engine that automates the deployment of any application as a lightweight, portable, self-sufficient container that will run virtually anywhere.” Docker creates containers that provide running process with:

an equal slice of CPU
a maximum memory quota
its own process ID (PID) namespace
its own network interface
its own private root filesystem

It does this by leveraging low-level Linux kernel primitives like cgroups and namepaces. The end result is a portable application container that can run anywhere Docker can run, including on VMs, bare-metal servers, OpenStack clusters, public instances, or combinations of the above.

Containers are an excellent way to package your application such that it can run consistently everywhere you want to run it, a fantastic step toward Continuous Delivery. In this session we'll look at how to use Docker to package, deploy, and run Java applications and other services. We'll also compare Docker to another container solution, Warden, which is a key component of the Cloud Foundry PaaS.

BOSH was originally developed to be the toolchain that installs and manages the Cloud Foundry runtime, which is a large distributed system consisting of multiple components running on multiple virtual machines. In order to deploy and manage such a system, you need elements of:

configuration management tools, such as Puppet and Chef
orchestration tools, such as Mcollective and RunDeck
knowledge of multiple IaaS layers (compute, storage, networking) to support portability
health management
monitoring and reporting
etc.

Fortunately, BOSH was written in such a way that it can be used to deploy not just Cloud Foundry, but any distributed system. Teams in multiple organizations are using it today to deploy:

large-scale Jenkins deployments
Hadoop clusters
Cassandra and other NoSQL store clusters
RabbitMQ and other message broker clusters

In this session we'll learn how to develop a BOSH release using the bosh-lite tool. We'll then learn how to create a deployment manifest, which maps our release to a specific infrastructure environment. Finally, we'll deploy our release to Amazon Web Services.

We make many assumptions when we develop our applications. Many of these assumptions no longer hold true when we start to build applications for the cloud. Cloud platforms also introduce architectural possibilities that do not exist in traditional deployment settings. This session will examine five architectural patterns that we can apply to our applications in order to prepare them for the unique characteristics of cloud environments.

We'll cover the following patterns:

Microservice
API Gateway
Stateless / Shared-Nothing
Configuration / Service Consumption
Fault Tolerance

Examples will focus on the application of these patterns using Java/Spring and Cloud Foundry-based PaaS platforms, but should be applicable to any language/framework/PaaS platform combination.

Simulation allows a rigorous, scalable, and reproducible approach to testing. The separation of concerns, and the use of a versioned, time-aware database, give simulation great power. This talk will introduce simulation testing, walking through a complete example using Simulant, an open-source simulation library.

Simulation allows a rigorous, scalable, and reproducible approach to testing:

Statistical modeling

Simulation begins with statistical models of the use of your system. This model includes facts such as “we have identified four customer profiles, each with different browsing and purchasing patterns” or “the analytics query for the management report must run every Wednesday afternoon.” Models are versioned and kept in a database.

Activity streams

The statistical models are used to create activity streams. Each agent in the system represents a human user or external process interacting with the system, and has its own timestamped stream of interactions. With a large number of agents, simulations can produce the highly concurrent activity expected in a large production system.

Distributed execution

Agents are scaled across as many machines as are necessary to both handle the simulation load, and give access to the system under test. The simulator coordinates time, playing through the activity streams for all the agents.

Result Capture

Every step of the simulation process, including modeling, activity stream generation, execution, and the code itself, is captured and stored in a database for further analysis. You will typically also capture whatever logs and metrics your system produces.

Validation

Since all phases of a simulation are kept in a database, validation can be performed at any time. This differs markedly from many approaches to testing, which require in-the-moment validation against the live system.

Separation of concerns

The separation of concerns above, and the use of a versioned, time-aware database, gives simulation great power. Imagine that you get a bug report from the field, and you realize that the bug corresponds to a corner case that you failed to consider. With a simulation-based approach, you can write a new validation for the corner case, and run that validation against your past simulation results, without ever running your actual system.

This talk will introduce simulation testing, walking through a complete example using Simulant, an open-source simulation library.

Domain-Driven Design (DDD) promises to simplify enterprise application development and is gradually gaining traction as an alternative to traditional four-tier architectures originally popularized by J2EE. As the name implies, DDD is an architectural approach that strongly focuses on materializing the business domain in software. This session demonstrates first-hand how DDD can be implemented using Java EE via a project named Cargo Tracker.

Part of the Java EE Blue Prints, Cargo Tracker seamlessly maps concepts like bounded contexts, layered architectures, entities, value objects, aggregates, services, repositories and factories to realistic code examples. The Cargo Tracker project also embraces popular practices adopted by the DDD community such as Object Oriented Analysis, Domain Models, Test Driven Development, Agile Refactoring, Continuous Integration, Object Relational Mapping, Dependency Injection and Cross-Cutting Concerns, incorporating these concepts into a realistic Java EE application.

Java EE 7 is around the corner and the horizons for Java EE 8 are emerging. This session looks into the key changes the community can expect. The goal of this session is to foster interest and discussion around these changes.

Some of the changes discussed include retiring EJB 2 entity beans and JAX-RPC, greater alignment with CDI, WebSocket/HTML 5 support, a standard API for JSON processing, the next version of JAX-RS, an overhaul of JMS, long-awaited concurrency utilities, batch processing in Java EE and much, much more.

The sea change in HTML 5 is likely to shift the pendulum away from today's thin-client based server-side web frameworks like Struts 2 and JSF to JavaScript powered next generation rich clients. With strong support for REST, WebSocket and JSON, Java EE 7 is well positioned to adapt to this change.

In this heavily code driven session, we will show you how you can utilize today's most popular JavaScript rich client technologies like AngularJS, Backbone, Knockout and Ember to utilize the core strengths of Java EE using JAX-RS, JSR 356/WebSocket, JSON-P, CDI and Bean Validation.

Find yourself overwhelmed with hundreds of to-dos? Is your hard-drive littered with dozens of killer ideas that you started with enthusiasm and then just fizzled away? Do you feel like you are moving as fast as can but only getting to the wrong place quicker? Well perhaps this session will help.

There are various techniques and strategies available to us today that aim to help with exactly this conundrum - from Getting Things Done ™ to Personal Kanban. Unfortunately it is often easy to be extremely productive using these systems, but not very effective. After all, it's not about getting things done, but getting the RIGHT things done. In this talk we will discuss not only how to get things done, but also attempt to figure out what it is you actually need to be doing.

In this session, I will attempt to show you how you can leverage various strategies to be more effective, knock to-dos out and have fun while doing it. If time permits we will close with an overview of the tools that are available to you, and how you can use these to become a to-do list ninja :)

The Spock framework brings simple, elegant testing to Java and Groovy projects. It integrates cleanly with JUnit, so Spock tests can be integrated as part of an existing test suite. Spock also includes an embedded mocking framework that can be used right away.

In this presentation, we'll look at several examples of Spock tests and review most of its capabilities, including mock objects and integration with Spring.

Robert Martin assembled the SOLID family of principles to provide a useful guide to help us create object-oriented software designs that were resilient in the face of change. In recent years, the need to write highly-concurrent software in order to leverage increasingly ubiquitous multicore architectures, as well as general interest in more effectively controlling complexity in large software designs, has driven a renewed interest in the functional programming paradigm. Given the apparent similarity in their goals, “What is the intersection of SOLID with functional programming?” is a natural question to ask.

In this talk, we'll explore this intersection. We'll begin with a tour of the evolutionary patterns associated with enterprise software and programming paradigms, as well as take a look at the ongoing quest for best practices, the goal being to elucidate the motivation for examining this intersection of SOLID and functional programming. We'll then walk through each of the SOLID principles, examining them in their original object-oriented context, and looking at example problems and solutions using the Java language. Then for each principle, we'll examine its possible intersection with the functional programming paradigm, and explore the same problems and solutions using the Clojure language. We'll close by examining the transcendent qualities of the SOLID principles and how they can make any design simpler, regardless of the programming paradigm employed.

For much of the last two years I've delivered a two-part series at NFJS shows entitled “Effective Java Reloaded.” For all pracical purposes, it is an ala carte style rehash of the book Effective Java, written by Josh Bloch. One of my favorite parts of the discussion is of Item #15, which tells us to “Minimize Mutability.” If we turn this inside out, we're actually saying that we want to MAXIMIZE IMMUTABILITY. When we do this, we reap many benefits, such as code that is easier to reason about and that is inherently thread-safe. This can carry us a long way in the direction of program correctness and decreased complexity. However, when we start to program with immutability, several major questions arise.

First, the necessity of using a separate object for each distinct value, never reusing, or “mutating” an object, can quickly cause performance concerns. These concerns are amplified when we're talking about large collections such as lists and maps. These problems are largely solved by what we call “persistent data structures.” Persistent data structures are collections from which we create new values, not by copying the entire data structure and apply changes, but by creating a new structure which contains our changes but points at the previous structure for those elements which have not changed. This allows us to work with data structures in a very performant way with respect to time and resource consumption. We'll examine persistent data structures, their associated algorithms, and implementations on the JVM such as those found in the TotallyLazy library.

Second, because all of an immutable object's state must be provided at the time of construction, the construction of large objects can become very tedious and error prone. We'll examine how the Builder pattern can be applied to ease the construction of large objects, and we'll examine Builder implementations in Java and Groovy.

Third, we run into problems when we start to use frameworks that expect us to program in a mutable style. A prime example is Hibernate, which expects our persistent classes to follow the well-worn JavaBean convention, including a no argument constructor and getters and setters for each property. Such a class can never be mutable! So how do we program with frameworks such as Hibernate and yet still minimize mutability? The key is found in not letting frameworks dictate the way that you design your code. Just because the framework require something, don't let it force you to make the wrong decision. Use the framework as a tool to write your code, don't let your code be a tool of the framework. We'll examine strategies for doing exactly that.

You should come away from this talk better equipped to program in a way that minimizes mutability and maximizes immutability.

Gradle has fast become one of the de-facto build tool in the Java ecosystem. Gradle offers a powerful DSL to configure your builds. Whether you have a simple build, or a complex build with many moving parts, Gradle's DSL and extensible API can help you make your builds easier, and possible.

In this sessio we will start from the ground up. We will write our first Gradle script and examine Gradle's configuration vs. execution phases. We will see how Gradle uses plugins to add on functionality for free to your build and end with a look at the Gradle Plugin API to see how easy it is to write your own plugins for better reuse.

Jamie Zawinski once said “Some people, when confronted with a problem, think “I know, I'll use regular expressions.” Now they have two problems.“. Many consider regular expressions to be indecipherable, but the truth is that every programmer should consider regular expressions an integral part of their toolkit. From the command line to your favorite text editor, from parsing user input to scraping HTML pages - once you know regular expressions you will find a use for them in almost every programming context.

In this session we will attempt to unriddle the mystery that regular expressions pose. We will start at the basics and work our way towards more complex expressions.

In this session we will look at some JavaScript patterns, and how you can use them within your code.

No longer can you think of JavaScript as a kiddie-scripting language. JavaScript has now been promoted to a first-class citizen within your application - and with this, comes the need to think of better abstractions, code re-use - even thinking of establishing a common vocabulary to discuss approaches to writing better, cleaner and ultimately more maintainable JavaScript code.

The software industry changes rapidly, but you can protect yourself
from these changes by creating code that is complicated enough that
only you can maintain it.

Of course you should not engage in obvious bad practices. The good
news is that you don't have to. You can follow idiomatic industry
practice and stay buzzword compliant with the latest trends, while
quietly spreading complexity throughout systems. Better yet, the
symptoms will show up not in your own code, but in other code that
uses your code, directly or indirectly. You will be a hero as you
lead larger and larger teams burning the midnight oil to keep systems
alive.

Practice these principles, and your code will have an
infectious complexity that guarantees you will always be needed to
maintain it.

Use OO, and don't forget those setter methods!
Prefer APIs over data.
Start with DSLs.
Always connect (and never enqueue).
Create abstractions for information.
Use static typing across subsystem boundaries.
Put language semantics on the wire.
Write lots of unit tests.
Leverage context.
Update information in place.

Even with the recent explosion in alternative languages for the JVM, the vast majority of us are still writing code in “Java the language” in order to put bread on the table. Proper craftsmanship demands that we write the best Java code that we can possibly write. Fortunately we have a guide in Joshua Bloch's Effective Java.

In his foreward to the first edition, Guy Steele writes about the importance of learning three aspects of any language: grammar, vocabulary, and idioms. Unfortunately many programmers stop learning after mastering the first two. Effective Java is your guide to understanding idiomatic Java programming.

Effective Java is organized into 78 standalone “items,” all of which will be impossible to cover in one session. Instead I've chosen a subset of the most important techniques and practices that are commonly missed by today's Java programmers. You'll pick from a menu and decide where we'll head. Regardless of the path we take, you'll leave this session thoroughly equipped to write better Java code tomorrow!

New York Software Symposium

April 4 - 5, 2014

Resources

Statistical modeling

Activity streams

Distributed execution

Result Capture

Validation

Separation of concerns

Resources

Statistical modeling

Activity streams

Distributed execution

Result Capture

Validation

Separation of concerns

TEST