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Software Evolution
This book focuses on novel trends in software evolution research and its relations with other emerging disciplines. Mens and Demeyer, both authorities in the field of software evolution, do not restrict themselves to the evolution of source code but also address the evolution of other, equally important software artifacts. This book is the indispensable source for researchers and professionals looking for an introduction and comprehensive overview of the state-of-the-art.
Empirical Research towards a Relevance Assessment of Software Clones
Redundancies in program source code - software clones - are a common phenomenon. Although it is often claimed that software clones decrease the maintainability of software systems and need to be managed, research in the last couple of years showed that not all clones can be considered harmful. A sophisticated assessment of the relevance of software clones and a cost-benefit analysis of clone management is needed to gain a better understanding of cloning and whether it is truly a harmful phenomenon. This thesis introduces techniques to model, analyze, and evaluate versatile aspects of software clone evolution within the history of a system. We present a mapping of non-identical clones across ...
Clustering-Based Support for Software Architecture Restructuring
The maintenance of long-living software systems is an essential topic in today’s software engineering practice and research. Software Architecture Restructuring is an important task to adjust these systems to current requirements and to keep them maintainable. Niels Streekmann introduces an approach to Software Architecture Restructuring that semi-automates this task by introducing graph clustering. The approach provides an iterative process that systematically incorporates human architectural knowledge for the improvement of the restructuring result. Thus, it supports the task of planning the transfer of an existing system to a target architecture and aims at reducing the required manual effort.
Formal Concept Analysis
Formal concept analysis has been developed as a field of applied mathematics based on the mathematization of concept and concept hierarchy. It thereby allows us to mathematically represent, analyze, and construct conceptual structures. The formal concept analysis approach has been proven successful in a wide range of application fields. This book constitutes a comprehensive and systematic presentation of the state of the art of formal concept analysis and its applications. The first part of the book is devoted to foundational and methodological topics. The contributions in the second part demonstrate how formal concept analysis is successfully used outside of mathematics, in linguistics, text retrieval, association rule mining, data analysis, and economics. The third part presents applications in software engineering.
Code Clone Analysis
This is the first book organized around code clone analysis. To cover the broad studies of code clone analysis, this book selects past research results that are important to the progress of the field and updates them with new results and future directions. The first chapter provides an introduction for readers who are inexperienced in the foundation of code clone analysis, defines clones and related terms, and discusses the classification of clones. The chapters that follow are categorized into three main parts to present 1) major tools for code clone analysis, 2) fundamental topics such as evaluation benchmarks, clone visualization, code clone searches, and code similarities, and 3) applica...
Heuristic and Knowledge-Based Security Checks of Source Code Artifacts Using Community Knowledge
The goal of this dissertation is to support developers in applying security checks using community knowledge. Artificial intelligence approaches combined with natural language processing techniques are employed to identify security-related information from community websites such as Stack Overflow or GitHub. All security-related information is stored in a security knowledge base. This knowledge base provides code fragments that represent the community´s knowledge about vulnerabilities, security-patches, and exploits. Comprehensive knowledge is required to carry out security checks on software artifacts, such as data covering known vulnerabilities and their manifestation in the source code a...
Computer-Aided Scheduling of Public Transport
This volume gives an overview on new theoretical approaches on computer-aided methods for strategic and operational planning in public transport. The papers of this volume cover the most important steps of the complete process of planning and operational control in public transport and public mass transit. Readers of this book obtain detailed information on current developments in vehicle and crew scheduling and in solving such problems in practice. Interesting results in scheduling theory are shown, using procedures for solving combinatorial problems with more complex structures. Furthermore, experiences in the application of specific software tools are presented. TOC:Vehicle and Crew Scheduling - Methodical Advances.- Vehicle and Crew Scheduling - Practical Issues.- Advanced Transit Service and Vehicle Routing.- Monitoring and Control.- Strategic Decision Problems.- Appendices.
Software and Data Technologies
This book constitutes the refereed proceedings of the 4th International Conference on Software and Data Technologies, ICSOFT 2009, held in Sofia, Bulgaria, in July 2009. The 19 revised full papers presented together with two invited papers were carefully reviewed and selected as best papers from 212 submissions. The papers are organized in topical sections on enterprise software technology; software engineering; distributed systems; data management; knowledge-based systems.
Feature Engineering for Machine Learning and Data Analytics
Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for majo...
