1 dataset found
  1. Z

    Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based...

    • data.niaid.nih.gov
    Updated Nov 21, 2020
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    Tóth, Zoltán Gábor (2020). Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics (Training Dataset) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4281475
    Explore at:
    Dataset updated
    Nov 21, 2020
    Dataset provided by
    Antal, Gábor
    Hegedűs, Péter
    Tóth, Zoltán Gábor
    Ferenc, Rudolf
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset consists of multiple files which contain bug prediction training data.

    The entries in the dataset are JavaScript functions either being buggy or non-buggy. Bug related information was obtained from the project EsLint contained in BugsJS (https://github.com/BugsJS/eslint). The buggy instances were collected throughout the lifetime of the project, however we added non-buggy entries from the latest version which is tagged as fix (entries which were previously included as buggy were not included as non-buggy later on).

    The dataset is based on hybrid call graphs which are constructed by https://github.com/sed-szeged/hcg-js-framework. The result of this tool is a call graph where the edges are associated with a confidence level which shows how likely the given edge is a valid call edge.

    We used different threshold values from which we considered the edges to be valid. The following threshold values were used:

    0.00

    0.05

    0.20

    0.30

    The prefix in the dataset file names are coming from the used threshold. The the datasets include coupling metrics NII (Nubmer of Incoming Invocations) and NOI (Number of Outgoing Invocations) which were calculated by a static source code analyzer called SourceMeter. Hybrid counterparts of these metrics (HNII and HNOI) are based on the given threshold values.

    There are four variants for all of these datasets:

    Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics and information about the entries (file without any postfix). Column contained only in this dataset are:

    ID

    Name

    Longname

    Parent ID

    Component ID

    Path

    Line

    Column

    EndLine

    EndColumn

    Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h+s' postfix)

    Only static (NII, NOI) coupling metrics are included with additional static source code metrics (file with '_s' postfix)

    Only hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h' postfix)

    Static source code metrics which are contained in all dataset are the following:

    McCC - McCabe Cyclomatic Complexity

    NL - Nesting Level

    NLE - Nesting Level Else If

    CD - Comment Density

    CLOC - Comment Lines of Code

    DLOC - Documentation Lines of Code

    TCD - Total Comment Density (Comment Lines in an emedded function will be also considered)

    TCLOC - Total Comment Lines of Code (Comment Lines in an emedded function will be also considered)

    LLOC - Logical Lines of Code (Comment and empty lines not counted)

    LOC - Lines of Code (Comment and empty lines are counted)

    NOS - Number of Statements

    NUMPAR - Number of Parameters

    TLLOC - Logical Lines of Code (Lines in embedded functions are also counted)

    TLOC - Lines of Code (Lines in embedded functions are also counted)

    TNOS - Total Number of Statements (Statements in embedded functions are also counted)

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Tóth, Zoltán Gábor (2020). Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics (Training Dataset) [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4281475

Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics (Training Dataset)

Explore at:
Dataset updated
Nov 21, 2020
Dataset provided by
Antal, Gábor
Hegedűs, Péter
Tóth, Zoltán Gábor
Ferenc, Rudolf
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset consists of multiple files which contain bug prediction training data.

The entries in the dataset are JavaScript functions either being buggy or non-buggy. Bug related information was obtained from the project EsLint contained in BugsJS (https://github.com/BugsJS/eslint). The buggy instances were collected throughout the lifetime of the project, however we added non-buggy entries from the latest version which is tagged as fix (entries which were previously included as buggy were not included as non-buggy later on).

The dataset is based on hybrid call graphs which are constructed by https://github.com/sed-szeged/hcg-js-framework. The result of this tool is a call graph where the edges are associated with a confidence level which shows how likely the given edge is a valid call edge.

We used different threshold values from which we considered the edges to be valid. The following threshold values were used:

0.00

0.05

0.20

0.30

The prefix in the dataset file names are coming from the used threshold. The the datasets include coupling metrics NII (Nubmer of Incoming Invocations) and NOI (Number of Outgoing Invocations) which were calculated by a static source code analyzer called SourceMeter. Hybrid counterparts of these metrics (HNII and HNOI) are based on the given threshold values.

There are four variants for all of these datasets:

Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics and information about the entries (file without any postfix). Column contained only in this dataset are:

ID

Name

Longname

Parent ID

Component ID

Path

Line

Column

EndLine

EndColumn

Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h+s' postfix)

Only static (NII, NOI) coupling metrics are included with additional static source code metrics (file with '_s' postfix)

Only hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h' postfix)

Static source code metrics which are contained in all dataset are the following:

McCC - McCabe Cyclomatic Complexity

NL - Nesting Level

NLE - Nesting Level Else If

CD - Comment Density

CLOC - Comment Lines of Code

DLOC - Documentation Lines of Code

TCD - Total Comment Density (Comment Lines in an emedded function will be also considered)

TCLOC - Total Comment Lines of Code (Comment Lines in an emedded function will be also considered)

LLOC - Logical Lines of Code (Comment and empty lines not counted)

LOC - Lines of Code (Comment and empty lines are counted)

NOS - Number of Statements

NUMPAR - Number of Parameters

TLLOC - Logical Lines of Code (Lines in embedded functions are also counted)

TLOC - Lines of Code (Lines in embedded functions are also counted)

TNOS - Total Number of Statements (Statements in embedded functions are also counted)

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