Computational Analysis in Software Engineering (ACISOFT)

This research project focuses on a quantitative study with an experimental design divided into two main phases to analyze software and algorithm performance. The First Phase investigates the impact of encapsulation on the source code of scientific software, measuring the execution time of constructive, heuristic, and metaheuristic algorithms, treating them as black boxes. The Second Phase concentrates on the performance of sorting algorithms (implemented in C and Python) when processing data arrays with specific characteristics (random, partially sorted, reverse, and categorical) and varying sizes (up to 100,000 elements) across multiple iterations. Independent variables will include source code (with/without encapsulation) and array types, with execution time as the dependent variable. The obtained data will be descriptively analyzed and compared against established theory to draw conclusions regarding the efficiency of implementations and algorithmic designs.<br/><br/><b>Goal</b>: <br/>The primary objective is to verify the incidence of the encapsulation component of Object-Oriented Programming (OOP) on the performance of scientific software through controlled experiments. Additionally, the goal is to compare the behavior of various sorting algorithms under different experimental designs and input data conditions.<br/><br/><b>Research lines</b>: <br/>Computer systems and artificial intelligence