Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple - PowerPoint PPT Presentation

Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach Kripabandhu Ghosh 1 , 2 Swapan Kumar Parui 1 1 Indian Statistical Institute, Kolkata, India 2 Indian Institute of Technology, Kanpur, India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach1 / 39

Objective To predict the BIG5 personality traits of a person from her Java program code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach2 / 39

Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach3 / 39

Programming and personality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach4 / 39

Outline BIG5 personality 1 Features 2 Methodology 3 Results 4 Analysis 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach7 / 39

BIG5 personality BIG5 personality traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach8 / 39

BIG5 personality : Neuroticism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach9 / 39

BIG5 personality : Neuroticism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 10 / 39

BIG5 personality : Neuroticism Motivation Neurotics exhibit low emotional stability and so is likely to be less methodical in writing a code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 11 / 39

BIG5 personality : Extroversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 12 / 39

BIG5 personality : Extroversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 13 / 39

BIG5 personality : Extroversion Motivation Extroverts are likely to express themselves and possibly provide meaningful comments in their code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 14 / 39

Outline BIG5 personality 1 Features 2 Methodology 3 Results 4 Analysis 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 15 / 39

Features FEATURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 16 / 39

Features Determining factors Readibility Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 17 / 39

Features : Multi-line comments (MLC) The number of genuine comment words in multi-line comments, i.e., between /* and */ found in the program code. We have not considered the cases where lines of code were commented. Eliminate code lines – E.g., using [a-zA-Z][a-zA-Z]*[ ]*( matching System.out.println(“Even”); used in a Java code. This feature value was normalized by dividing it by the total number of words in the program file Indicator of code readability and meticulousness of the coder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 18 / 39

Features : Multi-line comments (MLC) Feature Positive example Negative example MLC /** /*System.out.println(“Even”); * Make the hash table logically empty. printQ(qEven); */ System.out.println(“Odd”); printQ(qOdd);*/ SLC // Create a new double-sized, empty table //String[] ss = linea.readLine().split(“ ”); NES for (int i=1; i < =casos; i++) for (int i = 1; i < = casos; i++) IS import java.io.FileNotFoundException import java.io.* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 19 / 39

Features : Single-line comments (SLC) This is the number of genuine single-line comment words in single line comments, i.e., comments following “//”. We have not considered the cases where lines of code were commented. Eliminate code lines – same as MLC. This feature value was normalized by dividing it by the total number of words in the program file. Indicator of code readability and meticulousness of the coder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Ghosh ( Indian Statistical Institute, Kolkata, India , Indian Institute of Technology, Kanpur, India ) Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach 20 / 39

Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple - PowerPoint PPT Presentation

Indian Statistical Institute, Kolkata at PR-SOCO 2016 : A Simple Linear Regression Based Approach Kripabandhu Ghosh 1 , 2 Swapan Kumar Parui 1 1 Indian Statistical Institute, Kolkata, India 2 Indian Institute of Technology, Kanpur, India . . .

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