activity
20062025
most citedHeap Abstractions for Static Analysis

49 citations · 103 across the 20 of their papers we have counts for

collaborators

21 papers

cs.DS2025

LatticeHashForest: An Efficient Data Structure for Repetitive Data and Operations

Anamitra Ghorui, Uday P. Khedker

Analysis of entire programs as a single unit, or whole-program analysis, involves propagation of large amounts of information through the control flow of the program. This is espec…

cs.PL2024

Which Part of the Heap is Useful? Improving Heap Liveness Analysis

Vini Kanvar, Uday P. Khedker

With the growing sizes of data structures allocated in heap, understanding the actual use of heap memory is critically important for minimizing cache misses and reclaiming unused m…

cs.MS2023

SpComp: A Sparsity Structure-Specific Compilation of Matrix Operations

Barnali Basak, Uday P. Khedker, Supratim Biswas

Sparse matrix operations involve a large number of zero operands which makes most of the operations redundant. The amount of redundancy magnifies when a matrix operation repeatedly…

cs.SE2022

Computing Maximum Fixed Point Solutions over Feasible Paths in Data Flow Analyses

Komal Pathade, Uday Khedker

The control flow graph (CFG) representation of a procedure used by virtually all flow-sensitive program analyses, admits a large number of infeasible control flow paths i.e., these…

cs.PL2018★ 1 cited

Demand-driven Alias Analysis : Formalizing Bidirectional Analyses for Soundness and Precision

Swati Jaiswal, Uday P. Khedker, Supratik Chakraborty

A demand-driven approach to program analysis have been viewed as efficient algorithms to compute only the information required to serve a target demand. In contrast, an exhaustive…

cs.PL2018★ 1 cited

Generalized Points-to Graphs: A New Abstraction of Memory in the Presence of Pointers

Pritam M. Gharat, Uday P. Khedker, Alan Mycroft

Flow- and context-sensitive points-to analysis is difficult to scale; for top-down approaches, the problem centers on repeated analysis of the same procedure; for bottom-up approac…