Dependency Tracking in software systems

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Dependency Trackingin software systems

• Presented by Ashgan Fararooy

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Related Papers

• Supporting Software Evolution Analysis with
  Historical Dependencies and Defect Information
  (ICSM 2008)
• A Flexible Framework to Support Collaborative
  Software Evolution Analysis (CSMR 2008)
• Mining Software Repositories for Traceability
  Links (ICPC 2007)
• Tracking Objects to Detect Feature Dependencies
  (ICPC 2007)
• Software Repositories A Source for Traceability
  Links (TEFSE-GTC 2007)
• Mining Version Archives for Co-changed Lines
  (ICSE 2006)
• Understanding Semantic Impact of Source Code
  Changes an Empirical Study

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Mining Version Archives for Co-changed Lines

• Thomas Zimmermann, Sunghun Kim, Andreas Zeller,
  E. James Whitehead Jr.
• (ICSE 2006)

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Abstract

• Files, classes, or methods have frequently been
  investigated in research on co-change
• Present a first study at the level of lines
• Annotation Graph which captures how lines evolve
  over time
• More fine-grained software evolution information
  (based on lines)

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Overview

• Co-Change items that are changed together, are
  related to each other
• Any granularity modules, files, classes, methods
• What about more fine-grained items blocks, lines
  

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Co-Change in More Fine-Grained Items

• Seemed infeasible
• Hard to identify across different versions
• Line numbers are not suitable identifiers
• SCM systems annotation feature is not enough
• Line content is not a good identifier either

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Annotation Graph

• Definition
• A multipartite graph where each part corresponds
  to one version of a file
• Within each part/version every line is
  represented by a single node
• Edges between node indicate that a line
  originates from another by modification /
  movement
• Node labels (e.g. bold node) indicate a changed
  line

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Annotation Graph
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Annotation Graph

• Construction
• One needs to compare all subsequent revisions of
  a file
• Using the GNU diff tool For computing textual
  differences
• The diff tool returns a list of regions (hunks)
  that differ in the two files

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Annotation Graph

• Three different kinds of changes
• Modifications
• Result in a complete bipartite subgraphs
• Additions
• Do not result in any edges
• Positions of the following lines are updated
• Deletions
• The same effect as in addition

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Annotation Graph

• Computation
• Creates nodes for each revision and each line
• Two approaches
• 1- Forward-Directed
• 2- Backward-Directed

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Annotation Graph

• Computation (Forward-Directed Algorithm)
• Iterate over all pairs of subsequent revisions
• For each pair compute the differences (hunks)
• Process the hunks to create edges
• Exactly one edge between unchanged lines (nodes)
• For modified lines all possible edges
• For inserted and deleted lines no edges
• Label the nodes of the later revision in
  modifications and additions

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Annotation Graph

• Problem
• Changes that modify large parts of a file
• Results in a large number of edges
• Not reasonable for evolution analysis

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Annotation Graph

• Treat large modifications as combined deletions
  and additions
• No creation of edges in the annotation graph

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Annotation Graph

• Recognizing Large Modifications

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Annotating Lines

• Comparison
• Most SCM systems have annotating features for
  each line providing the latest change information
• Annotation graphs can be used to get such
  information
• Furthermore, they provide information on all past
  changes

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Life Cycle of Lines

• Investigated the life cycle of lines for the
  Eclipse Project
• How frequently are lines changed
• Computed for each line the change count
• The number of distinct revisions in its
  annotation
• How many developers change a line
• What are the most frequently changed lines

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Finding Related Lines

• Computed related lines using frequent pattern
  mining
• Used transaction ids instead of revision ids
• Used Apriori algorithm
• Inferred useful association rules

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Thank you