Blogs (61) >>
Mon 16 Jul 2018 14:40 - 15:20 at Matterhorn II - Track 2

Static analyses are vital in modern software development. Static analyses are best known for detecting errors at compile time and thus helping developers to write correct code. That’s an honorable quest and not for nothing static analysis is sometimes referred to as lightweight verification.

But static analysis has a second quest of equal importance: to aid program understanding. Development tools such as IDEs use information computed by static analyses to explain the program to the developer (variable v has type int, variables v1 and v2 point to the same object), to provide exploration functionality (jump to declaration, find call sites), to guide developers (uninitialized read, dead code), and to provide sophisticated edit actions (refactorings). IDEs must provide all these features without interrupting the workflow of the developer. In particular, IDEs must react quickly to code changes. That is, the underlying static analyses need to be incremental.

We present IncA, a language-independent framework for incremental static analysis that does not compromise on precision. IncA provides a DSL for the definition of static analyses and incrementalizes them automatically. We explain how the IncA compiler translates analysis specifications into Datalog-style rules and how the IncA runtime solves these rules incrementally. We particularly discuss how IncA incrementalizes fixpoint computations, which are ubiquitous in data-flow analysis.

IncA is a joint effort of industry (itemis, IncQuery Labs) and academia (TU Delft, TU Budapest). IncA has been used to incrementalize control flow and points-to analysis for C, string analysis and strong points-to analysis for Java, and type analysis for Rust. However, one of our main application areas are DSLs: DSL adoption requires competitive tooling, yet it does not pay off to invest years of engineering to build and maintain incremental analyses. IncA protects analysis developers from the technical details of incrementalization (dependency tracking, caching, cache invalidation), and thus significantly reduces the engineering effort.

Mon 16 Jul

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

13:50 - 15:20
A CRDT Primer: Defanging Order Theory
CurryOn Curry On Talks
John Mumm Vectrology Solutions
Better living through incrementality: Immediate static analysis feedback without loss of precision
CurryOn Curry On Talks
Tamás Szabó itemis AG / TU Delft, Sebastian Erdweg TU Delft