Design and Implementation of Modern Programming Languages (Seminar) Guido Salvaneschi Joscha Drechsler

Transcription

1 Design and Implementation of Modern Programming Languages (Seminar) 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 Introduce students to the core techniques of scientific work Give a scientific talk Process of writing and publishing research papers Review a paper Learn an advanced topic on PL Compare and evaluate existing solutions

6 Tentative Timeline Paper submission 17/12 Reviews submission 14/1 Feedback meetings 14/1-21/1 Camera ready: 28/1 Seminars: 4/2 Start Early!

7 Guidelines and Suggestions Find new references Try not to summarize everything that's written in references or in the references' references. Be complete in the bibliography, deep in the analysis Tell a coherent story about one aspect of the topic. Please present technologies, with your own words and your own examples. E.g. : the same running example through the paper

8 Reviews A summary of the paper To demonstrate that you read and understood Suggestions for the author, regarding both content and presentation Be realistic and concrete A list of the major positive and negative issues Honest! mainly used to grade the reviewer, not the paper

9 Grades Paper 40 % Talk 40 % Reviews 20 % Once more. Tell a nice story. Compare things. Find advantages and limitations. Provide examples in different cases. Papers are there to read This is the value that you add

10 Where to start Send me an with your name and a list of 3 topics Order by preference. Or consider synergies with DAIMPL Check the details on the course website. Time slots for seminars Paper length and format Topics will be assigned We provide you some references as a starting point

11 TOPICS

12 Programming Languages for Secure Computation Computations that can operate on encrypted data The server executing the computations does not need to access the data E.g., compute image processing on sensitive medical information Cloud computing Perfect scenario, can safely outsource computations to a third-party untrusted server

13 Programming Languages for Software-defined Networks (SDNs) Configuration of network hardware (e.g., switches) is tedious and error prone. Many different devices, vendors, APIs, Low-level details on packet forwarding SDNs can be programmed in high-level languages Global view of the network functionality Automatic translation to switches rules Procera, FlowLog, Frenetic,

14 Programming models for distributed Map-reduce massive data processing Huge amount of data, e.g., from the Internet, require efficient processing Formulation in terms of basic operations (map, reduce) Highly-optimized backends, e.g. clusters, clouds, etc Extension: Twister, HaLoop, Spark,

15 High-performance Realtime Analytics Realtime analytics are based on views over databases that change at very high rates. Algorithmic trading Scientific data analysis Requirements Low maintenance cost Low latencies SQL SELECT closingprice, timestamp FROM ClosingStockPrices WHERE stocksymbol = MSFT and closingprice > for (t = 101; t <= 1000; t++ ){ WindowIs(ClosingStockPrices, 101, t); } Select all the days after the hundredth trading day, on which the closing price of MSFT has been greater than $50. Keep this query standing in the system for a thousand trading days.

16 .NET Reactive Extensions and Bacon.js Data-flow programming model Event streams Everything is Observable C#, Java, Scala, Javascript Asynchronous Functional combinators var suggestion1stream = close1clickstream.combinelatest(responsestream, function(click, listusers) { return listusers[math.floor(math.random()*listusers.length)]; } ).merge( refreshclickstream.map(function(){ return null; }) ).startwith(null);

17 Debugging for event-based languages How to debug streams of data and queries over them? Visualization tools Ways to slow down the system or monitor its behavior

18 Composability of Advanced Concurrency Control Mechanism Concurrent programming is hard Thread-and-lock, race conditions, deadlocks, E.g., STM is a promising solution // Insert a node into a doubly linked list atomically atomic { newnode->prev = node; newnode->next = node->next; node->next->prev = newnode; node->next = newnode; } Analyze and compare existing solutions in terms of composability atomic { if (queuesize > 0) { remove item from queue and use it } else { retry } }

19 Omniscient debugging What if debuggers can go back in time? Register ALL events Performance / memory issues Navigate back in time Find the root source of a bug

20 Testing for event-based systems Map-reduce Events can be async Nondeterminism! How to explore the whole space?

21 THE END