https://ar.iub.edu.bd/handle/11348/972 Thu, 10 Sep 2026 12:43:57 GMT 2026-09-10T12:43:57Z https://ar.iub.edu.bd/handle/11348/1228 Investigating the key factors influencing software developer productivity in developing regions Ahsan, Rafid Al Software developer productivity is a critical factor influencing the efficiency and success of software projects. However, understanding the key factors that impact developer productivity remains a challenge, particularly in region-specific contexts such as Bangladesh. This study aims to identify the primary factors affecting developer productivity and analyze how these factors vary across companies and experience levels. To achieve this, a survey was conducted among software developers working in Bangladesh. The survey was sent out to 168 software developers working across 38 different software firms. The survey yield 44 responses. Statistical analysis was employed to determine the most influential factors. The findings suggest that autonomy in decision-making, task variety, and using the best practices, software and tool are the strongest factors affecting productivity. While some factors, such as task variety, remain consistent across companies, others, such as remote work policies and communication styles, vary significantly. Additionally, beginner developers prioritize learning and tool adoption, mid-level developers face challenges with tight deadlines, and senior developers focus more on leadership, collaboration and decision-making autonomy. Mon, 01 Sep 2025 00:00:00 GMT https://ar.iub.edu.bd/handle/11348/1228 2025-09-01T00:00:00Z https://ar.iub.edu.bd/handle/11348/992 Supplementary Material: A Project Report on “An Affordable IoT and Cloud-Based System for Real-Time Indoor Air Quality Monitoring in Educational Environments: A Case Study from Bangladesh” Zihan, Tahfizul Hasan; Islam, Noureen; Sadman, Noor-E; Mahir, Hasin The main concern of this project is to focus on IoT based devices and to distinguish if the IoT based device is as equal as the industrial graded device, by looking into the data and evaluating accuracy of the device that we have made, and provide a low cost solution. Collation of data is determined to be done to examine the accuracy of the data retrieved from the IoT based device. Errors are measured and compared to justify that our IoT based device is as good as the industrial ones. Sidewise, heading to the goal of finding an inexpensive solution, we will be learning more about the advanced air monitoring technology used by AirVisual Pro and analyze the data to determine the accuracy of the device we built. This document provides additional technical details to complement the main manuscript. It includes a detailed bill of materials (BOM) for the low-cost indoor air quality (IAQ) sensor nodes, descriptions of the sensor node’s physical design and the classroom deployment setup (including exact dimensions and placement heights), a schematic layout of the classroom with sensor locations and ventilation features, an overview of the software system (particularly the MQTT–Node-RED data pipeline with JSON processing logic and database insertion), and a summary of debugging challenges encountered during deployment (with their resolutions). Where relevant, insights from earlier project stages and manuscript versions are incorporated to enrich the methodology and design narrative. Wed, 21 May 2025 00:00:00 GMT https://ar.iub.edu.bd/handle/11348/992 2025-05-21T00:00:00Z