Related Experiment Video
Updated: May 8, 2025
06:37
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
2.4K
The use of artificial intelligence for automatic analysis and reporting of software defects
Mark Esposito1,2, Saman Sarbazvatan3, Terence Tse1
1Hult International Business School, Cambridge, MA, United States.
Frontiers in Artificial Intelligence
|December 26, 2024
Summary
Artificial intelligence (AI) enhances software development by using regression testing and automated logs. This speeds up defect detection, improving application quality and reducing costs.
Area of Science:
- Computer Science
- Software Engineering
Background:
- The COVID-19 pandemic accelerated demand for efficient business applications.
- Artificial Intelligence (AI) is crucial for streamlining operations and improving product quality.
Purpose of the Study:
- To identify key aspects for AI-driven software defect detection.
- To explore AI's role in enhancing application lifecycle management.
Main Methods:
- Qualitative, exploratory, descriptive, and non-experimental research.
- Documentary review of 79 bibliometric references.
Main Results:
- Regression testing and automated log files are vital in Machine Learning (ML) and Robotic Process Automation (RPA).
- These AI techniques significantly reduce failure identification time.
Conclusions:
- AI integration enables agile software development models.
- Companies benefit from reduced errors, cost savings, and enhanced application quality.
Related Concept Videos
01:19Quality Assurance
101
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
101
01:14Statistical Analysis System (SAS)
71
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
71
01:10Statgraphics
86
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
86
01:12Statistical Software for Data Analysis and Clinical Trials
279
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
279
01:11Overview of Minitab
64
Minitab is a statistical software package designed for data analysis. With its origins in the 1970s and development at Pennsylvania State University, Minitab has grown significantly in its capabilities and applications. It plays a crucial role in quality management projects, especially in Six Sigma initiatives, by offering tools for process improvement and statistical analysis. Minitab's significance lies in its user-friendly interface, making complex statistical analysis accessible to...
64
01:11Introduction to R
202
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
202