Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages &Amp; Applications 2014
DOI: 10.1145/2660193.2660242
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i3QL

Abstract: An incremental computation updates its result based on a change to its input, which is often an order of magnitude faster than a recomputation from scratch. In particular, incrementalization can make expensive computations feasible for settings that require short feedback cycles, such as interactive systems, IDEs, or (soft) real-time systems.This paper presents i3QL, a general-purpose programming language for specifying incremental computations. i3QL provides a declarative SQL-like syntax and is based on incre… Show more

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Cited by 13 publications
(3 citation statements)
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References 57 publications
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“…We implemented SecQL as a domain-specific language embedded in Scala. SecQL is built on top of i3QL (Mitschke et al 2014), which provides syntax for SQL-like queries, local incremental data processing and relational algebra optimizations. The syntactical correctness of queries is enforced by the Scala type system.…”
Section: Methodsmentioning
confidence: 99%
“…We implemented SecQL as a domain-specific language embedded in Scala. SecQL is built on top of i3QL (Mitschke et al 2014), which provides syntax for SQL-like queries, local incremental data processing and relational algebra optimizations. The syntactical correctness of queries is enforced by the Scala type system.…”
Section: Methodsmentioning
confidence: 99%
“…The example is a flow-sensitive interval analysis for Java, which reports the possible value ranges of program variables. As a starting point, we choose logic programming in Datalog because the use of Datalog for program analysis is well-documented [Green et al 2013; Smaragdakis and Bravenboer 2011], and there exist incremental Datalog solvers [Gupta et al 1993;Mitschke et al 2014;. It will become clear in this section that incremental program analysis requires incremental recursive aggregation, which existing solvers fail to support.…”
Section: Challenges Of Incremental Program Analysismentioning
confidence: 99%
“…Prior research has shown that incrementality is particularly useful for program analysis. For example, incrementality was reported to speed up FindBugs checks 65x [Mitschke et al 2014] and C points-to analysis 243x . Unfortunately, existing approaches for efficiently incrementalizing static analyses are limited in expressiveness due to limitations of the Datalog solvers they rely on.…”
Section: Introductionmentioning
confidence: 99%