Inclusion-based pointer analysis
Webstate-of-the-art inclusion-based pointer analysis algorithms, namely, HT, PKH, and BLQ. We find that HT is the fastest— 1.9 faster than PKH and 6.5 faster than BLQ. We … WebMay 9, 2024 · We present PUS, a fast and highly efficient solver for inclusion-based pointer analysis. At the heart of PUS is a new constraint solving algorithm that significantly advances the state-of-the-art, i.e., wave and deep propagation algorithms.
Inclusion-based pointer analysis
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WebPointer analysis is just a prerequi-site to our pointer recoder. 2.1 Related Work The general problem of pointer analysis can be divided into two parts, Points-To and Alias analysis. Points-to analysis attempts to statically determine the memory lo-cations a pointer can point to. On the other hand, alias analysis attempts to determine if two ... WebInclusion-based (i.e. Andersen-style) pointer analysis is an important point in the space of pointer analyses, offering a potential sweet-spot in the trade-off between precision and performance. However, current techniques for inclusion-based pointer analysis can have difficulties delivering on this potential.
WebMay 1, 2024 · Pus is a new constraint solving algorithm that signifi-cantly advances the state-of-the-art in pointer analysis and is able to analyze millions of lines of code such as PostgreSQL in 10 minutes on a commodity laptop. A crucial performance bottleneck in most interprocedural static analyses is solving pointer analysis constraints. We present Pus, a … Web// In pointer analysis terms, this is a subset-based, flow-insensitive, // field-sensitive, and context-insensitive algorithm pointer algorithm. // // This algorithm is implemented as three stages: // 1. Object identification. // 2. Inclusion constraint identification. // 3. Offline constraint graph optimization // 4. Inclusion constraint solving.
WebInclusion-based points-to analysis is context-insensitive and flow-insensitive. A context-sensitive analysis analyzes a pro- cedure separately for each context in which it is … Webpointers cannot alias if they do not have compatible types [10]. By following strict aliasing, we further improve the precision of TEADSA. We have evaluated TEADSA against SEADSA and SVF, a state-of-the-art inclusion-based pointer analysis in LLVM, on the verification problem of detecting unsafe memory ac-cesses.
WebOct 1, 2024 · 1. Research the audience in advance. Advertisement. Determine inclusive language choices by discovering the identity words and phrases learners use and …
WebMay 9, 2024 · ICSE 2024 Technical Track. We present PUS, a fast and highly efficient solver for inclusion-based pointer analysis. At the heart of PUS is a new constraint solving … cif b78593092WebMar 13, 2024 · PointINS: Point-based Instance Segmentation. In this paper, we explore the mask representation in instance segmentation with Point-of-Interest (PoI) features. … dharamsala cheap hotelsWebJan 1, 2009 · Inclusion-Based Multi-level Pointer Analysis January 2009 DOI: 10.1109/AICI.2009.157 Authors: Yingxia Cui Longshu Li Sheng Yao Abstract A novel … dharamsala yoga teacher trainingWebPointer information is a prerequisite for most program analyses, and inclusion-based, i.e. Andersen-style, pointer analysis is widely used to compute such information. However, current inclusion-based analyses can have prohibitive costs in time and space, especially for programs with millions of lines of code. dharamshala dalhousie tour package from delhiWebable whole-program pointer analysis to compute pointer information. The preci-sion of the computed information can have a profound impact on the usefulness of the subsequent program analysis. Inclusion-based, i.e. Andersen-style, pointer analysis is widely-used because of its relative precision and potential for scala-bility. cif b74352295WebIt is inclusion-based, meaning that two pointers may point to overlapping but dif-ferent sets of objects. It is also field-sensitive, meaning that ... scribe our C pointer alias analysis based on our pcp model in Section 2. Section 3 presents the cons model. Section 4 discusses our type inference analysis. Section 5 presents our cif b72340433WebAug 31, 2016 · A points-to analysis in Java has to compute two sets of edges: (i) a set of unlabeled edges from variables to abstract heap objects, and (ii) a set of field-labeled edges between abstract objects. This is not the case for C/C++, where: 1. Objects can be allocated both on the stack and on the heap. 2. cif b72444839