Mon 20 - Fri 24 October 2014 Portland, Oregon, United States
Wed 22 Oct 2014 10:52 - 11:15 at Salon E - Program Analysis and the Web Chair(s): Stephen Chong

Static analysis for JavaScript can potentially help programmers find errors early during development. Although much progress has been made on analysis techniques, a major obstacle is the prevalence of libraries, in particular jQuery, which apply programming patterns that have detrimental consequences on the analysis precision and performance.

Previous work on dynamic determinacy analysis has demonstrated how information about program expressions that always resolve to a fixed value in some call context may lead to significant scalability improvements of static analysis for such code. We present a static dataflow analysis for JavaScript that infers and exploits determinacy information on-the-fly, to enable analysis of some of the most complex parts of jQuery. The analysis combines selective context and path sensitivity, constant propagation, and branch pruning, based on a systematic investigation of the main causes of analysis imprecision when using a more basic analysis.

The techniques are implemented in the TAJS analysis tool and evaluated on a collection of small programs that use jQuery. Our results show that the proposed analysis techniques boost both precision and performance, specifically for inferring type information and call graphs.

Wed 22 Oct
Times are displayed in time zone: (GMT-07:00) Tijuana, Baja California change

10:30 - 12:00: OOPSLA - Program Analysis and the Web at Salon E
Chair(s): Stephen ChongHarvard University
oopsla201410:30 - 10:52
Asger FeldthausAarhus University, Anders MøllerAarhus University
Link to publication
oopsla201410:52 - 11:15
Esben AndreasenAarhus University, Anders MøllerAarhus University
Link to publication
oopsla201411:15 - 11:37
Michael PradelUniversity of California, Berkeley, USA, Parker SchuhUniversity of California, Berkeley, George NeculaUniversity of California, Berkeley, Koushik SenUniversity of California, Berkeley
Link to publication
oopsla201411:37 - 12:00
Chun-Hung HsiaoUniversity of Michigan, Michael CafarellaUniversity of Michigan, Satish NarayanasamyUniversity of Michigan
Link to publication