Implementation of Programming Languages (project) Guido Salvaneschi Joscha Drechsler

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1 Implementation of Programming Languages (project) Guido Salvaneschi Joscha Drechsler

2 Outline Administrivia Intro Schedule Topics

3 GENERAL INFORMATION

4 Administrivia Guido Salvaneschi, Joscha Drechsler Find us by Office A213 / A207 Group of Prof. Mira Mezini (STG)

5 Intro Implement a software artifact according to a given specification. General scope: programming languages: Extensions, code generators Tools, IDEs Analysis techniques Performance assessments Prototypes with innovative abstractions

6 Timeline Periodic discussions/meetings. Presentation and delivery of the artifact and the documentation: end of the semester.

7 Guidelines and Suggestions Depending on the goal of the project In general: Deliver RUNNING code Deliver some documentation Optional: final presentation / demo to discuss your work Team working is good! Organize a team even with people you don t know (yet)

8 Grades Depending on the project Some guidelines: How much of the specification was implemented? Did I say that the code has to run? What is the overall quality of the code? E.g. is it painful to modify/extend it? Is it self-documenting? What is the quality of the documentation?

9 Where to start Send me an with your name and a list of 3 topics in order of preference. Or arrange an appointment: Ask clarifications if needed Discuss possible customizations Discuss the projects in more detail Consider your programming skills Topics will be assigned Discuss the project in detail with the instructor

10 Getting Widespread Reactive programming in JavaScript Flapjax, Bacon.js, Reactive.js, React.js, Microsoft reactive extensions (Rx) Netflix! REScala Principles of Reactive Programming Martin Odersky, Erik Meijer and Roland Kuhn

11 RP in a Nutshell Reactivity in OO apps: Observer pattern In RP you can define constraints The framework enforces them for you Changes are automatically propagated VIEW X Y Z val a = 3 d val b = 7 val c := a + b val d := 2 * c c a=4 println(c) // c==11 a b DATA X Y Z

12 /* Create the graphics */ title = "Reactive Swing App val button = new Button { text = "Click me!" } val label = new Label { text = "No button clicks registered" } contents = new BoxPanel(Orientation.Vertical) { contents += button contents += label } title = "Reactive Swing App" val label = new ReactiveLabel val button = new ReactiveButton RP /* The logic */ listento(button) var nclicks = 0 reactions += { case ButtonClicked(b) => nclicks += 1 label.text = "Number of button clicks: " + nclicks if (nclicks > 0) button.text = "Click me again" } OO /* The logic */ val nclicks = button.clicked.count label.text = Signal { ( if (nclicks() == 0) "No" else nclicks() ) + " button clicks registered" } button.text = Signal { "Click me" + (if (nclicks() == 0) "!" else " again " )} contents = new BoxPanel(Orientation.Vertical) { contents += button contents += label }

13 TOPICS

14 High-performance Distributed RP Vision: Distributed RP like RPC/RMI State of the art Topological sorting Distributed algorithms Goal: efficiency! Reactive islands Global propagation

15 Lock-free data structures Traditional approach to concurrency: Locks. Lock, write, unlock. Lock, read, unlock. Repeat. Lock-free data structures Avoid locks Compare-and-swap atomic operations Efficient!

16 Programming model for cloud computing Virtually infinite computational resources. Anywhere, anytime On demand Language issues: Deployment Dynamic reconfiguration Design patterns Async communication

17 Transparent reactivity! Reactive programming approaches are bottom-up Primitive reactive values (e.g., Vars, Events) Derived values (event streams, signals) Refactoring existing code requires Figure computefigure(){ computefigurecolor() computefigureshadow() } Color computefigurecolor(){ } Shadow computefigureshadow(){ }

18 Session types in Scala Session types support static check of protocols correctness Steps Study session types Reuse existing library Small case study

19 QUESTIONS?