niravjdn / Software-Measurement-Project

This repository contains raw data generated for the project of SOEN 6611(Software Measurement - Winter 2019). -http://smproject.niravjdn.xyz/ or https://smproject.herokuapp.com/

Software Measurement Project - SOEN 6611-2184-D (Winter 2019)

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The aim of this project is to calculate several software metrices and to define correlation between them.

Professor: Jinqiu Yang

Team Member Details

Name	Student ID	Email ID
Nirav Ashvinkumar Patel	40081268	[e-mail]
Himansi Patel	40072262	[e-mail]
Krishnan Krishnamoorthy	40089054	[e-mail]
Darwin Anirudh Godavari	40093368	[e-mail]
Jayaprakash Kumar	40083709	[e-mail]

We calculated following metrices.

1. Statement Coverage: Statement coverage is a white box testing technique, which involves the execution of all the statements at least once in the source code. It is a metric, which is used to calculate and measure the number of statements in the source code which have been executed.
2. Branch Coverage: ranch coverage is a testing method, which aims to ensure that each one of the possible branch from each decision point is executed at least once and thereby ensuring that all reachable code is executed.
3. Mutation Score: Mutation testing is used to design new software tests and evaluate the quality of existing software tests.
4. Cyclomatic Complexity: Cyclomatic complexity is a software metric used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code.
5. Relative Code Churn Code churn is a measure of the amount of code change taking place within a software unit over time.
6. Software Defect Density

Selected Open-Source Systems

1. Apache Common Collections - project details , source-code
2. Apache Commons Configuration - project details , source-code
3. Apache Commons Math - project details , source-code
4. Apache Commons IO - project details , source-code
5. Apache Commons Lang - project details , source-code

Directory Structure

.                                   
├── Presentation         # Presentaion of the project - 4th April, 2019
├── Proposal             # Proposal of the project
├── assets               # Images or other screenshots
├── Data                 # Raw Data - CSV, HTML (All Metrics)
├── Jupyter Notebook     # Jupyter Notebook Source Code
└── README.md

Used tools for different metrices :

CLOC - Counting lines of the program

CLOC TUTORIAL

https://www.youtube.com/watch?v=QxiXKZftJRw&t=161s

Effectively count lines grouped by programming languages - http://cloc.sourceforge.net/

Jacoco

Code Coverage - https://www.eclemma.org/jacoco/

Added Dependency Plugin in pom.xml for PIT Test as below

<?xml version="1.0" encoding="UTF-8"?>
<plugin>
   <groupId>org.jacoco</groupId>
   <artifactId>jacoco-maven-plugin</artifactId>
   <version>0.7.7.201606060606</version>
   <executions>
      <execution>
         <goals>
            <goal>prepare-agent</goal>
         </goals>
      </execution>
      <execution>
         <id>report</id>
         <phase>prepare-package</phase>
         <goals>
            <goal>report</goal>
         </goals>
      </execution>
   </executions>
</plugin>

How did we run Jacoco for our project

PIT - Mutation Testing

http://pitest.org/

http://pitest.org/quickstart/basic_concepts/

https://www.mkyong.com/maven/maven-pitest-mutation-testing-example/

http://pages.cs.aueb.gr/~kintism/papers/emse2017/

https://www.youtube.com/watch?v=wZeZMtqVmck&feature=youtu.be

How did we run for PIT Tool for our project

Added Dependency Plugin in pom.xml for PIT Test as below

We didn't configure it for only certains classes, instead we ran it on entire project.On an average, It took 1-2 hours for 4 projects(collections, configurations, io, lang) and 8.5 hours for math.

Find the screenshot below.

<plugin>
        <groupId>org.pitest</groupId>
        <artifactId>pitest-maven</artifactId>
        <version>LATEST</version>
        <configuration>
            <outputFormats>
                <param>HTML</param>
                <param>CSV</param>
            </outputFormats>
        </configuration>
</plugin>

Reference : http://pitest.org/quickstart/maven/

Following command to compile and run unit tests

mvn clean install

Following command to run PIT Test

mvn org.pitest:pitest-maven:mutationCoverage -X

X is for debug mode so we can see what's going on.

Maven Installation Locally

https://maven.apache.org/install.html

Some Maven Reference To Solve Errors While Compiling

Maven Extension https://github.com/objectledge/maven-extensions

m2e http://grumpyapache.blogspot.com/2011/08/mess-that-is-m2e-connectors.html

Correlation Reference (Python and Panda)

https://www.datascience.com/blog/introduction-to-correlation-learn-data-science-tutorials

Data and Reports

http://smproject.nirajdn.xyz/

https://smproject.herokuapp.com/

All generated data in can be found on above site as well.

Steps to find Commit ID for all the open source project that we were analyzed

Video

Spearman's Rank order Correlation

Spearman correlation calculation procedure were all explained here in URL.

Link: https://statistics.laerd.com/statistical-guides/spearmans-rank-order-correlation-statistical-guide.php

Link: https://stackoverflow.com/questions/25571882/pandas-columns-correlation-with-statistical-significance

Link: https://geographyfieldwork.com/SpearmansRankCalculator.html

Link: https://data-flair.training/blogs/python-statistics/

Metric 5 Calculation (Defect Density)

Collected Data

Video

Metric 6 Calculation (Relative Churned Code)

Step 1 (Video)

Step 2 (Video)

CLOC Usage guide for calculating relative code churn

cloc --diff file1.zip file2.zip

Jupyter Notebook

https://drive.google.com/open?id=1kB3hoNvKrX-gr6AuuCWKLyCX2E-MSnBL

HTML View : http://smproject.niravjdn.xyz/JN/HTML/ https://smproject.herokuapp.com//JN/HTML/

To Convert Jupyter Notebokks to HTML

We created following website for converting Jupyter Notebooks to HTMl for all of the people without having local setup of python.

https://juptohtml.herokuapp.com/app