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SUMMARY:Developer Targeted Runtime Analytics - Extending Developers' Menta
 l Models by Runtime Dimensions - Jürgen Cito (University of Zurich)
DTSTART:20171102T141500Z
DTEND:20171102T151500Z
UID:TALK94489@talks.cam.ac.uk
CONTACT:Alexander Simpson
DESCRIPTION:To reason about source code\, developers construct mental mode
 ls that are informed by their knowledge of control and data flow. Reasonin
 g about runtime aspects of code (e.g.\, performance) requires consulting e
 xternal information sources\, such as profilers\, but is often guided by p
 ersonal belief and gut-feeling. For software deployed in scalable cloud in
 frastructures\, developers even need to inspect distributed runtime traces
  to reason about the peculiarities of production environments. In my work\
 , I propose a framework to model these traces together with the Abstract S
 yntax Tree (AST) of source code to extend developer’s mental models by r
 untime dimensions. Additionally\, we leverage learning techniques to infer
  future states of runtime properties of newly written code. This should se
 rve as an early-warning system to prevent runtime problems from reaching p
 roduction. We implemented an instantiation of this framework as a proof-of
 -concept IDE plugin called PerformanceHat. It augments the source code vie
 w with a runtime performance dimension and infers performance properties o
 f certain types of code changes to provide live feedback during developmen
 t. We recently evaluated our approach in a controlled experiment with 20 p
 rofessional software developers and found that developers were significant
 ly faster in (1) detecting the performance problem\, and (2) finding the r
 oot-cause of the problem.\n\nShort Bio: Jürgen Cito is a PhD candidate at
  the University of Zurich\, Switzerland\, where his research investigates 
 the intersection between software engineering and performance engineering.
  In the summer of 2015\, he was a research intern working on cloud analyti
 cs at the IBM TJ Watson Research Center in New York. In the spring of 2016
 \, he was a visiting PhD student at the Massachusetts Institute of Technol
 ogy (MIT)\, where he worked on program analysis to conserve energy in mobi
 le applications. He is currently visiting the Physical Computation Lab at 
 the University of Cambridge. Prior to starting his PhD\, Jürgen was a sof
 tware engineer for performance monitoring solutions at Catchpoint Systems\
 , a technology consultant at Accenture\, and a software engineer for web a
 gency itellico internet solutions.\n
LOCATION:SS03 Meeting Room\, Computer Laboratory
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