An efficient hybrid algorithm for incremental data flow analysis

Marlowe, Thomas J.; Ryder, Barbara G.

doi:10.1145/96709.96728

Cited by 74 publications

(34 citation statements)

References 23 publications

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“…Some incremental analyses use the elimination method [3,5], some are based on the technique of restarting iterations [20] and some are hybrids of the two techniques [18]. A comparison of incremental iterative algorithm can be found in [4].…”

Section: Related Workmentioning

confidence: 99%

“…Incremental analysis is especially important for large projects in a software development environment where it is necessary to maintain a global analysis in the presence of small and frequent edits. Several solutions have been proposed by using incremental elimination [3,5], restarting iteration [20], a combination of these two techniques [18], timestamp-based backtracing [13], and logic program evaluation [24]. In this paper, we introduce an incremental approach for points-to analyses based on CFL-reachability.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Incremental Points-to Analysis with CFL-Reachability

Lü

Shang

Xie

et al. 2013

Lecture Notes in Computer Science

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Abstract.Developing scalable and precise points-to analyses is increasingly important for analysing and optimising object-oriented programs where pointers are used pervasively. An incremental analysis for a program updates the existing analysis information after program changes to avoid reanalysing it from scratch. This can be efficiently deployed in software development environments where code changes are often small and frequent. This paper presents an incremental approach for demand-driven context-sensitive points-to analyses based on ContextFree Language (CFL) reachability. By tracing the CFL-reachable paths traversed in computing points-to sets, we can precisely identify and recompute on demand only the points-to sets affected by the program changes made. Combined with a flexible policy for controlling the granularity of traces, our analysis achieves significant speedups with little space overhead over reanalysis from scratch when evaluated with a null dereferencing client using 14 Java benchmarks.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Incremental Points-to Analysis with CFL-Reachability

Lü

Shang

Xie

et al. 2013

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…IDE provides a window to write serial code and shows vital information about concurrency to the user. There are many techniques that propose the analysis of code during development like incremental parsing [21], incremental dependency analysis [53], [54], [55], incremental profiling [19], [41], [16], incremental flow graph analysis [17], [42], and so on. Still, identifying and updating data dependency information dynamically, while the code is in development phase poses many challenges.…”

Section: Easyparmentioning

confidence: 99%

A Review of Parallelization Tools and Introduction to Easypar

Sah¹,

Vaidya²

2012

IJCA

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Multicore processors have paved the way to increase the performance of any application by the virtue of benefits of parallelization. However, exploiting parallelism from a program is not easy, as it requires parallel programming expertise. In addition, manual parallelization is a cumbersome, time consuming and inefficient process. A number of tools proposed in the past ease the effort of parallel programming. This paper presents a classification of such parallelization tools. The classification is based on different eras of tool development, role playedby these tools in various parallelization stages, and features provided by parallel program assistance tools. Classification of tools concludes with a discussion on requirements of futuristic parallelization tools. Finally, this paper proposesour on-going work about the development of a parallel program assistance tool called EasyPar, which is a parallel program assistance tool.

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“…A variety of incremental algorithms have been developed for data flow analysis problems. Some of them use the elimination method [6,8,25]; others are based on restarting iterations [24], while both techniques are combined in [22]. A comparison of incremental iterative algorithms for data flow analysis can be found in [7].…”

Section: Related Workmentioning

confidence: 99%

Automatic Incrementalization of Prolog Based Static Analyses

Eichberg

Kahl

Saha

et al. 2006

Practical Aspects of Declarative Languages

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Abstract. Modern development environments integrate various static analyses into the build process. Analyses that analyze the whole project whenever the project changes are impractical in this context. We present an approach to automatic incrementalization of analyses that are specified as tabled logic programs and evaluated using incremental tabled evaluation, a technique for efficiently updating memo tables in response to changes in facts and rules. The approach has been implemented and integrated into the Eclipse IDE. Our measurements show that this technique is effective for automatically incrementalizing a broad range of static analyses.

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An efficient hybrid algorithm for incremental data flow analysis

Cited by 74 publications

References 23 publications

An Incremental Points-to Analysis with CFL-Reachability

An Incremental Points-to Analysis with CFL-Reachability

A Review of Parallelization Tools and Introduction to Easypar

Automatic Incrementalization of Prolog Based Static Analyses

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