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Trainings

Security Training

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Rememberance

Presented at RaCAS (Research and Creative Activities Symposium) in Arpil 2019

I Joined 2019 RaCAS (Research and Creative Activities Symposium) at University of Colorado Denver, USA in April 2019 and presented our research on Non-Contact Respiratory Analysis using Thermal and CO2 Imaging.

Full Poster Presentation is available here : [ View Presentation ]

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Research

Code Smell Detection

Software systems continue their exponential growth in size and complexity. With this growth, software quality and maintenance has become a major concern. Not only that maintenance efforts often eclipse that of the initial software development, but it has become the reason why many software systems become unsustainable over time.

Software engineers apply many refactoring techniques to maintain a reasonable code quality as the software evolves. These refactoring techniques are typically applied reactively only after quality degrades and maintenance becomes a concern. My research will aim to identify quality concerns and codebase degradation before it materializes. This way, refactoring’s can be applied proactively well before the emergence of deficiencies.

There is a significant and growing research that aims to predict software failure and software bugs using many techniques including machine learning. My research will build on these advancements and will focus on predicting code quality attributes, rather than predicting failures and bugs. One specific paper has ignited my interest in this research area authored by Liu ‎[14]. In this paper, the authors applied a deep learning technique using several neural networks to predict the emergence of code smells. In this approach, the authors used a data set from Quality Corpus Repository [17] and extracted several code qualities features. The approach demonstrated the significant potential of machine learning in predicting code smells over time. The deep learning approach was found to be significantly superior to the most prevalent techniques and code analysis tools.

There are numerous open questions and challenges in this research area. The first big challenge is the availability of sufficiently large and appropriately labeled training datasets. Another big challenge is to identify the features that impact code quality evolution over time. And yet another challenge is to identify and evaluate the most appropriate and effective machine learning technique to predict several aspects of code quality attributes. I expect that my research will 1) create a large number of labeled data sets that can help propel research in this area, 2) identify key features that have the most impact on code quality and its evolution, and 3) contribute to identifying the effectiveness of several machine learning techniques in achieving the desired predictive code quality analysis.

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Others Projects

Novel Coronavirus (COVID-19) Situation Reports & Interactive Map

Novel Coronavirus (COVID-19) Situation Reports & Interactive Map is also called NC-19SRIM. The app was first launched on February 2020.

CDC is responding to an outbreak of respiratory disease caused by a novel (new) coronavirus that was first detected in China and which has now been detected in more than 100 locations internationally, including in the United States. The virus has been named “SARS-CoV-2” and the disease it causes has been named “coronavirus disease 2019” (abbreviated “COVID-19”).


NC-19SRIM Tool

Categories
Rememberance

2-day Workshop: Empowering the Borderland in January 2020.

I joined 2-day Workshop: Empowering the Borderland in January 2020.

This workshop was aimed to meet with industry people having a background in CS. Also, what are new research opportunities in school? In addition to that, there is a project showcase where new ideas/ work are presented

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Class Projects

Urban Heat Island Effect in the Borderland

An Urban Heat Island (UHI) is an urban area or metropolitan area that is significantly warmer than its surrounding rural areas due to human activities. The temperature difference is usually larger at night than during the day and is most apparent when winds are weak. UHI is most noticeable during the summer and winter [1]. 

The term “heat island” describes built-up areas that are hotter than nearby rural areas. The annual mean air temperature of a city with 1 million people or more can be 1.8–5.4°F (1–3°C) warmer than its surroundings. In the evening, the difference can be as high as 22°F (12°C) [2]. Heat islands can affect communities by increasing summertime peak energy demand, air conditioning costs, air pollution and greenhouse gas emissions, heat-related illness and mortality, and water pollution [3]. 

Major impacts of heat island are increased energy consumption; elevated emissions of air pollutants and greenhouse gases; compromised human health and comfort; and impaired water quality [4]. In our project, the surface temperature with local metrological data is analyzed and visualized in a form of a web application where users can search their area and see the heat island effect in temperature value. A sample web page view for El Paso, TX is shown in Figure 1. The project also visualizes the historical map of heat index over the years (2002-2019). In addition, the project includes the Google Earth Engine mapping system to visualize the heat index map.

  1. Mirzaei, P. A. (2015). Recent challenges in modeling of urban heat island. Sustainable cities and society, 19, 200-206.
  2. Heat Island Effect, https://www.epa.gov/heat-islands. 
  3. Heaviside, C., Macintyre, H., & Vardoulakis, S. (2017). The urban heat island: implications for health in a changing environment. Current environmental health reports, 4(3), 296-305.
  4. Bhargava, A., Lakmini, S., & Bhargava, S. (2017). Urban heat island effect: it’s relevance in urban planning. J. Biodivers. Endanger. Species, 5, 5-187.  
Heat Island Effect Demo Tool
Categories
Projects Research

ModelMine – An application to mine models from Open Source Repositories

ModelMine – An application to mine models from Open Source Repositories

The ModelMine helps you to search for model-based repositories (.uml, .xmi, etc.). For example, you can search for .uml based repositories. The option is not integrated with Advanced Search in GitHub Website. Also, Think of it the way, you want to search a repository that has a language: Java and repository have model files(.uml or .xmi, etc), then this app will help you to find those repositories. Just like searching on GitHub, you sometimes want to see a few pages of search results so that you can find the item that best meets your needs. To satisfy that need, the ModelMine provides the best result based on search cafeterias.

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Education

Doctor of Philosophy (Ph.D.) in Computer Science (CS) at University of Texas at El Paso (UTEP)

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Career Teaching

Teaching Assistant at Computer Science, University of Texas at El Paso, USA.

  • August 2019 – Current
  • My Teaching Strategy- [ Details ]
  • Responsibilities:
    • Helps student in their course, project development.
Categories
Trainings

Institutional Compliance Program