COHERENT DEPENDENCE CLUSTERSSyed Islam1

AGENDA

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Coherent Clusters (Specialized Dependence Cluster)

Mapping Source Code Constructs to Clusters

Visualization Tool for Dependence Clusters

Overlapping Clusters

Program Comprehension / Maintenance Fault Prediction

DEPENDENCE CLUSTER A dependence cluster is a maximal set of program

statements where each statement depends on all other.

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Minimal Slice

DEPENDENCE CLUSTER (SLICE-BASED)

A Slice-Based Dependence Clusters is a maximal set of program statements all of which are in each others slice. 4

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Two statements that mutually depend upon each other must be in each others slice.

DEPENDENCE CLUSTER ..

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Remembering all the slices is too expensive.

Approximation techniques were used

Same Slice Cluster Same Slice-Size Cluster.

MSG -MONOTONE SLICE-SIZE GRAPH Calculate the Slice Sizes for each SDG vertex

of a program.

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Plot all slice sizes of the program in one graph in monotonically increasing order of the sizes.

X axis: percentage of slices representedY axis: normalised slice size

COHERENT CLUSTERS

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Same-Slice Dependence cluster have internal and external requirements.

Statements of Clusters constructed from Backward Slices are all influenced by the same set of statements. (Backward-Slice Cluster)

Statements of Clusters constructed from Forward Slices all influence the same set of statements. (Forward-Slice Cluster).

A Coherent Cluster is a set of statements where each statement has the same backward slice and the same forward slice.

WHAT FORMS A CLUSTER?

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Dependence ClusterForward-Slice ClusterBackward-Slice ClusterCoherent Cluster

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SCG – SLICE/CLUSTER-SIZE GRAPH

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SCG – SLICE/CLUSTER-SIZE GRAPHB-MSG

F-MSG

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B-MCG

F-MCG

SCG – SLICE/CLUSTER-SIZE GRAPH

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SCG – SLICE/CLUSTER-SIZE GRAPHCoherent Clusters

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RESULTS COHERENT CLUSTERS

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FUNCTION MAPPING TO CLUSTER Tool Maps: source lines and files to clusters. functions represent particular computation

mapping functions to clusters. Initial Data:

Multiple functions form a cluster. Multiple clusters within the same function.

APPROXIMATION CONSTRAINTS Calculate percentage of pair of nodes whose

slices are the same; to that of where the nodes in the pair are in each others slice.

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x and y, where nodes x and y are nodes of a pdg

| { x,y : S(x) = S(y) }|| { x,y : x S(y) y S(x) }|

BC – The results is 60%.

S() – Backward Slice

The algorithm runs in T(n) = O(n3) hence 30 days

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COHERENT CLUSTER DEPENDENCE GRAPH

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What does this mean?

COHERENT CLUSTER DEPENDENCE GRAPH ..

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Does this mean we are looking at a dependence cluster (or .. MDS)?

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70.43%

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DAGSTUHL SEMINAR BEYOND PROGRAM SLICING

Hypothesis 1: short program slices have fewer faults

Hypothesis 2: code common to many program slices has fewer faults

Hypothesis 3: cliff faces in dependence clusters indicate faults

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ONGOING WORK

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Complete implementation of the tool

Mapping Source Code Constructs to Clusters

Combining Cluster – Larger Clusters Longitudinal study

Faults Metrics