Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Flow- and Context-Sensitive Points-to Analysis using Generalized
  Points-to Graphs   Computing precise (fully flow-sensitive and context-sensitive) and exhaustive
points-to information is computationally expensive. Many practical tools
approximate the points-to information trading precision for efficiency. This
has adverse impact on computationally intensive analyses such as model
checking. Past explorations in top-down approaches of fully flow- and
context-sensitive points-to analysis (FCPA) have not scaled. We explore the
alternative of bottom-up interprocedural approach which constructs summary flow
functions for procedures to represent the effect of their calls. This approach
has been effectively used for many analyses. However, it is computationally
expensive for FCPA which requires modelling unknown locations accessed
indirectly through pointers. Such accesses are commonly handled by using
placeholders to explicate unknown locations or by using multiple call-specific
summary flow functions.
  We generalize the concept of points-to relations by using the counts of
indirection levels leaving the unknown locations implicit. This allows us to
create summary flow functions in the form of generalized points-to graphs
(GPGs) without the need of placeholders. By design, GPGs represent both memory
(in terms of classical points-to facts) and memory transformers (in terms of
generalized points-to facts). We perform FCPA by progressively reducing
generalized points-to facts to classical points-to facts. GPGs distinguish
between may and must pointer updates thereby facilitating strong updates within
calling contexts.
  The size of GPG is linearly bounded by the number of variables and is
independent of the number of statements in the procedure. Empirical
measurements on SPEC benchmarks show that GPGs are indeed compact in spite of
large procedure sizes. This allows us to scale FCPA to 158 kLoC using GPGs
(compared to 35 kLoC reported by liveness-based FCPA).

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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: mtrl-th
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The categories of this paper are: astro-ph
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The categories of this paper are: eess
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The categories of this paper are: stat
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The categories of this paper are: nucl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: q-fin
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The categories of this paper are: hep-th