Intelligent Software Defect Prediction
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| Author | : Xiaoyuan Jing |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2024-01-24 |
| Genre | : Technology & Engineering |
| ISBN | : 9789819928415 |
With the increasing complexity of and dependency on software, software products may suffer from low quality, high prices, be hard to maintain, etc. Software defects usually produce incorrect or unexpected results and behaviors. Accordingly, software defect prediction (SDP) is one of the most active research fields in software engineering and plays an important role in software quality assurance. Based on the results of SDP analyses, developers can subsequently conduct defect localization and repair on the basis of reasonable resource allocation, which helps to reduce their maintenance costs. This book offers a comprehensive picture of the current state of SDP research. More specifically, it introduces a range of machine-learning-based SDP approaches proposed for different scenarios (i.e., WPDP, CPDP, and HDP). In addition, the book shares in-depth insights into current SDP approaches’ performance and lessons learned for future SDP research efforts. We believe these theoretical analyses and emerging challenges will be of considerable interest to all researchers, graduate students, and practitioners who want to gain deeper insights into and/or find new research directions in SDP. It offers a comprehensive introduction to the current state of SDP and detailed descriptions of representative SDP approaches.
| Author | : Xiao-Yuan Jing |
| Publisher | : Springer Nature |
| Total Pages | : 210 |
| Release | : 2024-01-17 |
| Genre | : Technology & Engineering |
| ISBN | : 9819928427 |
With the increasing complexity of and dependency on software, software products may suffer from low quality, high prices, be hard to maintain, etc. Software defects usually produce incorrect or unexpected results and behaviors. Accordingly, software defect prediction (SDP) is one of the most active research fields in software engineering and plays an important role in software quality assurance. Based on the results of SDP analyses, developers can subsequently conduct defect localization and repair on the basis of reasonable resource allocation, which helps to reduce their maintenance costs. This book offers a comprehensive picture of the current state of SDP research. More specifically, it introduces a range of machine-learning-based SDP approaches proposed for different scenarios (i.e., WPDP, CPDP, and HDP). In addition, the book shares in-depth insights into current SDP approaches’ performance and lessons learned for future SDP research efforts. We believe these theoretical analyses and emerging challenges will be of considerable interest to all researchers, graduate students, and practitioners who want to gain deeper insights into and/or find new research directions in SDP. It offers a comprehensive introduction to the current state of SDP and detailed descriptions of representative SDP approaches.
| Author | : El-Sayed M. El-Alfy |
| Publisher | : Springer |
| Total Pages | : 663 |
| Release | : 2014-09-08 |
| Genre | : Technology & Engineering |
| ISBN | : 331911218X |
This book contains a selection of refereed and revised papers of Intelligent Informatics Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India. The papers selected for this Track cover several intelligent informatics and related topics including signal processing, pattern recognition, image processing data mining and their applications.
| Author | : Max Bramer |
| Publisher | : Springer Nature |
| Total Pages | : 502 |
| Release | : 2019-12-09 |
| Genre | : Computers |
| ISBN | : 3030348857 |
This book constitutes the proceedings of the 39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2019, held in Cambridge, UK, in December 2019. The 29 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 49 submissions. The volume includes technical papers presenting new and innovative developments in the field as well as application papers presenting innovative applications of AI techniques in a number of subject domains. The papers are organized in the following topical sections: machine learning; knowledge discovery and data mining; agents, knowledge acquisition and ontologies; medical applications; applications of evolutionary algorithms; machine learning for time series data; applications of machine learning; and knowledge acquisition.
| Author | : Christian Bird |
| Publisher | : Elsevier |
| Total Pages | : 673 |
| Release | : 2015-09-02 |
| Genre | : Computers |
| ISBN | : 0124115438 |
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry
| Author | : Sandeep Kumar |
| Publisher | : Springer |
| Total Pages | : 81 |
| Release | : 2018-06-06 |
| Genre | : Computers |
| ISBN | : 9811087156 |
This book focuses on exploring the use of software fault prediction in building reliable and robust software systems. It is divided into the following chapters: Chapter 1 presents an introduction to the study and also introduces basic concepts of software fault prediction. Chapter 2 explains the generalized architecture of the software fault prediction process and discusses its various components. In turn, Chapter 3 provides detailed information on types of fault prediction models and discusses the latest literature on each model. Chapter 4 describes the software fault datasets and diverse issues concerning fault datasets when building fault prediction models. Chapter 5 presents a study evaluating different techniques on the basis of their performance for software fault prediction. Chapter 6 presents another study evaluating techniques for predicting the number of faults in the software modules. In closing, Chapter 7 provides a summary of the topics discussed. The book will be of immense benefit to all readers who are interested in starting research in this area. In addition, it offers experienced researchers a valuable overview of the latest work in this area.
| Author | : Parma Nand |
| Publisher | : CRC Press |
| Total Pages | : 317 |
| Release | : 2023-02-10 |
| Genre | : Computers |
| ISBN | : 1000575926 |
This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
| Author | : Vishal Jain |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 282 |
| Release | : 2022-02-21 |
| Genre | : Computers |
| ISBN | : 3110709341 |
Researchers, academicians and professionals expone in this book their research in the application of intelligent computing techniques to software engineering. As software systems are becoming larger and complex, software engineering tasks become increasingly costly and prone to errors. Evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and others techniques can help the effi ciency of software engineering.
| Author | : Roger Lee |
| Publisher | : Springer |
| Total Pages | : 199 |
| Release | : 2014-09-02 |
| Genre | : Technology & Engineering |
| ISBN | : 331910389X |
This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 – July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.
| Author | : Bhuvan Unhelkar |
| Publisher | : Springer Nature |
| Total Pages | : 782 |
| Release | : 2023-12-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9819959748 |
This volume comprises the select peer-reviewed proceedings of the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning 2022 (ICAAAIML 2022). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in the areas of artificial intelligence, machine learning, deep learning, and their advanced applications in computer vision and blockchain. It also covers research in core concepts of computers, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, software engineering, image processing, and cloud computing. This volume will provide a valuable resource for those in academia and industry.
