Data
ar1

ar1

active ARFF Publicly available Visibility: public Uploaded 06-10-2014 by Joaquin Vanschoren
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  • mythbusting_1 study_1 study_123 study_15 study_20 study_41 study_7 study_88
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Author: Source: Unknown - Date unknown Please cite: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable, refutable, verifiable, and/or improvable predictive models of software engineering. If you publish material based on PROMISE data sets then, please follow the acknowledgment guidelines posted on the PROMISE repository web page http://promise.site.uottowa.ca/SERepository. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% --Title: AR1 /Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University, Istanbul, Turkey --Website: http://softlab.boun.edu.tr --Contact address: ayse.tosun@boun.edu.tr, bener@boun.edu.tr --Description: Embedded software in a white-goods product. Implemented in C. Consists of 121 modules (9 defective / 112 defect-free) 29 static code attributes (McCabe, Halstead and LOC measures) and 1 defect information(false/true) Function/method level static code attributes are collected using Prest Metrics Extraction and Analysis Tool [1]. [1] Prest Metrics Extraction and Analysis Tool, available at http://softlab.boun.edu.tr/?q=resources&i=tools.

30 features

defects (target)nominal2 unique values
0 missing
total_locnumeric41 unique values
0 missing
blank_locnumeric6 unique values
0 missing
comment_locnumeric21 unique values
0 missing
code_and_comment_locnumeric3 unique values
0 missing
executable_locnumeric37 unique values
0 missing
unique_operandsnumeric33 unique values
0 missing
unique_operatorsnumeric17 unique values
0 missing
total_operandsnumeric49 unique values
0 missing
total_operatorsnumeric59 unique values
0 missing
halstead_vocabularynumeric42 unique values
0 missing
halstead_lengthnumeric71 unique values
0 missing
halstead_volumenumeric84 unique values
0 missing
halstead_levelnumeric35 unique values
0 missing
halstead_difficultynumeric35 unique values
0 missing
halstead_effortnumeric90 unique values
0 missing
halstead_errornumeric24 unique values
0 missing
halstead_timenumeric89 unique values
0 missing
branch_countnumeric20 unique values
0 missing
decision_countnumeric20 unique values
0 missing
call_pairsnumeric14 unique values
0 missing
condition_countnumeric18 unique values
0 missing
multiple_condition_countnumeric6 unique values
0 missing
cyclomatic_complexitynumeric17 unique values
0 missing
cyclomatic_densitynumeric29 unique values
0 missing
decision_densitynumeric12 unique values
0 missing
design_complexitynumeric14 unique values
0 missing
design_densitynumeric33 unique values
0 missing
normalized_cyclomatic_complexitynumeric27 unique values
0 missing
formal_parametersnumeric4 unique values
0 missing

62 properties

121
Number of instances (rows) of the dataset.
30
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
29
Number of numeric attributes.
1
Number of nominal attributes.
0.88
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.81
First quartile of standard deviation of attributes of the numeric type.
0.38
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0.25
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
4.93
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
2.25
Mean skewness among attributes of the numeric type.
4.76
Second quartile (Median) of means among attributes of the numeric type.
92.56
Percentage of instances belonging to the most frequent class.
232.28
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
112
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
1.95
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.13
Minimum kurtosis among attributes of the numeric type.
3.33
Percentage of binary attributes.
6.11
Second quartile (Median) of standard deviation of attributes of the numeric type.
47.41
Maximum kurtosis among attributes of the numeric type.
0.07
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
2861.8
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
9.63
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
96.67
Percentage of numeric attributes.
20.59
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
0
Minimum skewness among attributes of the numeric type.
3.33
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
6.49
Maximum skewness among attributes of the numeric type.
0.08
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
2.61
Third quartile of skewness among attributes of the numeric type.
5926.75
Maximum standard deviation of attributes of the numeric type.
7.44
Percentage of instances belonging to the least frequent class.
2.99
First quartile of kurtosis among attributes of the numeric type.
17.43
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
9
Number of instances belonging to the least frequent class.
0.51
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
8.07
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
119.61
Mean of means among attributes of the numeric type.
1.63
First quartile of skewness among attributes of the numeric type.

6 tasks

558 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: defects
198 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: defects
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: defects
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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