Unveiling the Skills and Responsibilities of Serverless Practitioners: An Empirical Investigation

This replication package accompanies the research paper titled "Unveiling the Skills and Responsibilities of Serverless Practitioners: An Empirical Investigation." The package contains the data and code used to perform the analyses presented in the paper.

Purpose: The primary goal of this dataset is to provide the necessary resources for replicating the results of our study on the skills and responsibilities of serverless practitioners. Researchers can use this package to verify our findings, perform additional analyses, or adapt our methodology for their own research.

Contents:

1. Analysis Sheet.xlsx: This Excel file includes the raw data and the processed data used in our analyses. The file consists of the following sheets:

   • Raw Data: Contains the unprocessed data collected from various sources. 
   • Meta Data: Provides detailed information about the data collection process.
   • Pilot Sample: Includes data from the pilot study conducted to test the research methodology. This sheet helps in understanding the preliminary results and adjustments made for the main study.
   • Selected Sample: Contains data from the sample selected for the main study. 
   • Roles Sorting: This sheet categorizes different roles based on the data collected. 
   • Initial Coding: Provides the initial coding of qualitative data. This includes codes assigned to various responses and observations, serving as a foundation for thematic analysis.
   • Responsibilities Thematic: Contains thematic analysis of the responsibilities associated with different roles. This sheet categorizes responsibilities into various themes based on the data.
   • Soft Skill Thematic: Includes thematic analysis of soft skills identified in the study. The sheet categorizes soft skills into different themes, helping in understanding the skill requirements across roles.
   • Hard Skill Thematic: Provides a thematic analysis of hard skills identified in the study. Similar to the soft skills sheet, this categorizes hard skills into different themes to analyze their distribution and importance across roles.

2. Python Script: The Python script used to automate the data collection process from Glassdoor. This script employs Selenium, Selenium Stealth, and PostgreSQL to retrieve real-time job listings, ensuring data integrity and minimizing selection bias.