While computer scientists have developed and provided several powerful computer languages and techniques in the last decades, facilitating the development of modular, maintainable and e±cient code, software development itself has changed fundamentally. Software development today treats often with large-scale projects, immense development costs, and complex sys- tems which typically deploy multiple technologies and require multiple participants for their development. As with any large development exercise, the development of a complex system must be systematic and structured in order to manage this complexity, and in order to make possible the future maintenance and evolution of the system. Thus, while systematic and structured approaches are necessary for the development of such systems, software engineers have attempted to provide the structured methodologies and formalisms so often lacking in large software development projects. However, software development projects are still related with many di®erent high risks. These risks cause software engineering projects to exceed bud- gets, miss deadlines, or deliver less than satisfactory products. As an example, U.S. companies alone spent an estimated $59 billion in cost overruns on IT projects and another $81 billion on cancelled software projects in 1995 (Johnson 1995). One reason for these high costs is that managers are not using adequate measures and executing e±cient risk management assess and mitigate the risks involved in these projects.
Although risk taking is essential to progress, and failure is often a key part of learning, the inevitability of risks does not imply the inability to recognize and manage risks to minimize potential negative consequences while retaining the opportunities for creating new and better software. Obviously, this risk management process is particularly di±cult for large-scale soft- ware projects and be handled in the same way as for small project, or just by providing more resources for all development factors.
Inhaltsverzeichnis (Table of Contents)
- 1 Introduction
- 1.1 Motivation and Background
- 1.2 Purpose and Structure of this Study
- 2 Risk in Software Engineering
- 2.1 Risk and Uncertainty
- 2.2 Delimitation of Software Engineering Risks
- 2.3 Software Development Risks and Their Sources
- 3 Heuristic Software Risk Analysis and Management Methodologies
- 3.1 Risk Management Objectives and General Strategies
- 3.2 Risk Management Planning
- 3.2.1 Planning and Implementation of the Risk Management Process
- 3.2.2 Management Responsibilities
- 3.2.3 Team Management and Communication
- 3.3 Risk Identification
- 3.4 Risk Analysis and Evaluation
- 3.5 Planning and Implementation of Risk Handling and Controlling
- 3.6 Risk Tracking and Monitoring
- 4 Software Engineering Process Modeling
- 4.1 Meta-Models and Meso-Models for Software Development Processes
- 4.1.1 Waterfall Process Models
- 4.1.2 Rapid and Evolutionary Prototyping and the Incremental Model
- 4.1.3 The Spiral Model
- 4.1.4 Unified Development Process and Rational Unified Process
- 4.1.5 Extreme Programming and 'Agile' Development
- 4.1.6 Open Source Software Development Processes
- 4.1.7 Comparison and Evaluation
- 4.2 System Dynamics Models
- 4.3 Process Modeling Languages (PMLs)
- 4.3.1 Case Study Introduction: The Appache HTTP Server Project
- 4.3.2 Object-Oriented Process Modeling With the UML
- 4.3.3 Step-Based Process Modeling with JIL/Little-JIL
- 4.3.4 Petri Net Based Process Modeling With FUNSOFT
- 4.3.5 Case Study Evaluation
- 4.1 Meta-Models and Meso-Models for Software Development Processes
- 5 Verification, Validation and Testing
- 5.1 Static Analysis Techniques for Validating Software
- 5.2 Dynamic Analysis Techniques for Validating Software
- 6 Risk Measurement and Quantification
- 6.1 Product Quality Measurement and Metrics
- 6.2 Process Measurement and Metrics
- 6.2.1 Capability Maturity Model (CMM)
- 6.2.2 ISO 9000 and Other Process Certification Models
- 6.3 Macro-Models for Cost and Schedule Estimation
- 6.3.1 The COCOMO I
- 6.3.2 From COCOMO I to COCOMO II
- 6.3.3 Applicability and Evaluation of COCOMO I/II
- 6.4 A Quantitative Model on the Economies of Development Process Architectures
- 6.4.1 Model Introduction
- 6.4.2 The Optimization Model: Deterministic Part
- 6.4.3 The Optimization Model: Stochastic Part and Simulation
- 6.4.4 Model Conclusion, Limitations and Possible Extensions
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This study aims to analyze risk management methodologies within the context of software engineering. It explores various approaches to risk identification, assessment, and mitigation, emphasizing the integration of these processes into the software development lifecycle.
- Software development risks and their sources
- Heuristic risk analysis and management methodologies
- Software engineering process modeling and its impact on risk management
- Risk measurement and quantification techniques
- The application of quantitative models to software development risk
Zusammenfassung der Kapitel (Chapter Summaries)
1 Introduction: This chapter sets the stage for the study, providing background information on the motivation behind the research and outlining the structure and purpose of the document. It establishes the importance of effective risk management in software engineering and highlights the need for a comprehensive analysis of existing methodologies.
2 Risk in Software Engineering: This chapter defines and delineates the concept of risk within the software engineering domain, distinguishing it from uncertainty. It systematically explores the sources and types of software development risks, providing a foundational understanding of the challenges addressed in the subsequent chapters. The chapter lays the groundwork for a deeper investigation into risk management strategies.
3 Heuristic Software Risk Analysis and Management Methodologies: This chapter delves into various heuristic methodologies for managing software engineering risks. It outlines general strategies and planning processes, emphasizing the importance of team management and communication. Detailed explanations of risk identification, analysis, evaluation, handling, controlling, and monitoring are provided, offering a practical framework for implementing effective risk management. This chapter provides a structured approach to managing inherent uncertainties in software development.
4 Software Engineering Process Modeling: This chapter examines different software development process models, including waterfall, prototyping, spiral, unified process, extreme programming, and open source approaches. It also explores system dynamics models and process modeling languages (PMLs) such as UML, JIL/Little-JIL, and FUNSOFT, using the Apache HTTP Server project as a case study to illustrate their application. The chapter highlights the relationship between chosen process models and their impact on risk management effectiveness. The comparison of different methodologies illustrates the trade-offs inherent in various software development approaches.
5 Verification, Validation and Testing: This chapter focuses on the crucial aspects of verification and validation within the software development process. It explores both static and dynamic analysis techniques, aiming to ensure that the developed software meets its intended requirements and functions correctly. The discussion of testing methodologies underpins the overall risk management strategy by focusing on reducing the chances of deploying faulty software.
6 Risk Measurement and Quantification: This chapter deals with the quantitative aspects of risk management. It explores product and process metrics, including the Capability Maturity Model (CMM) and ISO 9000 standards, and examines macro-models such as COCOMO I and II for cost and schedule estimation. A significant portion is dedicated to a quantitative model analyzing the economic implications of different development process architectures, using both deterministic and stochastic modeling approaches. The chapter links the theoretical models with practical application to aid in decision-making during the development process.
Schlüsselwörter (Keywords)
Software engineering, risk management, risk analysis, risk mitigation, software development processes, process modeling, risk quantification, COCOMO, CMM, ISO 9000, UML, JIL, FUNSOFT, verification, validation, testing.
Frequently Asked Questions: A Comprehensive Language Preview on Software Engineering Risk Management
What is the overall topic of this document?
This document provides a comprehensive overview of software engineering risk management. It covers various aspects, from risk identification and analysis to mitigation strategies and quantitative modeling, all within the context of different software development lifecycle methodologies.
What are the key themes explored in this study?
The study explores several key themes: software development risks and their sources, heuristic risk analysis and management methodologies, software engineering process modeling's impact on risk management, risk measurement and quantification techniques, and the application of quantitative models to software development risk.
What is the purpose of Chapter 1: Introduction?
Chapter 1 sets the context for the study, explaining the motivation behind the research and outlining the document's structure and purpose. It emphasizes the importance of effective risk management in software engineering.
What does Chapter 2: Risk in Software Engineering cover?
Chapter 2 defines and differentiates risk from uncertainty in the software engineering context. It examines the sources and types of software development risks, laying the foundation for understanding risk management strategies.
What methodologies are discussed in Chapter 3: Heuristic Software Risk Analysis and Management Methodologies?
Chapter 3 details heuristic methodologies for managing software engineering risks. It covers risk management planning, identification, analysis, evaluation, handling, controlling, and monitoring, providing a practical framework for implementation.
What software development process models are analyzed in Chapter 4: Software Engineering Process Modeling?
Chapter 4 examines various software development process models, including Waterfall, prototyping, spiral, unified process, extreme programming, and open source approaches. It also explores system dynamics models and process modeling languages (PMLs) like UML, JIL/Little-JIL, and FUNSOFT, using the Apache HTTP Server project as a case study.
What is the focus of Chapter 5: Verification, Validation and Testing?
Chapter 5 concentrates on verification and validation in software development, exploring static and dynamic analysis techniques to ensure the software meets requirements and functions correctly. Testing methodologies are discussed to reduce risks associated with deploying faulty software.
What quantitative methods are explained in Chapter 6: Risk Measurement and Quantification?
Chapter 6 covers the quantitative aspects of risk management. It explores product and process metrics (including CMM and ISO 9000), macro-models like COCOMO I and II for cost and schedule estimation, and a quantitative model analyzing the economic implications of different development process architectures (using deterministic and stochastic modeling).
What specific quantitative models are mentioned?
The document mentions COCOMO I and II for cost and schedule estimation, as well as a custom quantitative model for analyzing the economic implications of different development process architectures. The Capability Maturity Model (CMM) and ISO 9000 standards are also discussed as process metrics.
What process modeling languages (PMLs) are discussed?
The document discusses UML, JIL/Little-JIL, and FUNSOFT as process modeling languages (PMLs), illustrating their applications with a case study of the Apache HTTP Server project.
What are the key takeaways from this document?
The key takeaway is a comprehensive understanding of software engineering risk management, encompassing various methodologies, quantitative models, and process models, all aimed at improving the effectiveness and efficiency of software development projects.
What are the keywords associated with this document?
Software engineering, risk management, risk analysis, risk mitigation, software development processes, process modeling, risk quantification, COCOMO, CMM, ISO 9000, UML, JIL, FUNSOFT, verification, validation, testing.
- Quote paper
- Malte Sunderkötter (Author), 2004, Software Engineering Risk Management, Munich, GRIN Verlag, https://www.grin.com/document/29630
