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Intraprocedural Dataflow Analysis for Software Product Lines

  • ,
  • Márcio Ribeiro
    ,
  • Társis Tolêdo
    ,
  • Johnni Winther
    ,
  • Paulo Borba
  • Federal University of Pernambuco
    ,
  • University of Copenhagen
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 13-24

Publication milestones

  • Published - 2013

Publication status

Published - 2013

Publisher

Association for Computing Machinery, United States

Book series

  • Book series name: Transactions on Aspect-Oriented Software Development
    ISSN: 0000-0038
978-1-4503-1092-5

Publication IDs

  • Scopus: 84875101500

Host publication title

AOSD '12 Proceedings of the 11th annual international conference on Aspect-oriented Software Development

Abstract

Software product lines (SPLs) developed using annotative
approaches such as conditional compilation come with an inherent risk
of constructing erroneous products. For this reason, it is essential to be
able to analyze such SPLs. However, as dataflow analysis techniques are
not able to deal with SPLs, developers must generate and analyze all
valid products individually, which is expensive for non-trivial SPLs.

In this paper, we demonstrate how to take any standard intraprocedural dataflow analysis and automatically turn it into a feature-sensitive
dataflow analysis in five different ways where the last is a combination of
the other four. All analyses are capable of analyzing all valid products
of an SPL without having to generate all of them explicitly.

We have implemented all analyses using SOOT’s intraprocedural dataflow
analysis framework and experimentally evaluated four of them according
to their performance and memory characteristics on five qualitatively
different SPLs. On our benchmarks, the combined analysis strategy is
up to almost eight times faster than the brute-force approach.

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