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e-Learning:
Software Engineering Best Training Practices within the Software Engineering Industry This report provides the results of a benchmarking study to identify the best training practices within the software engineering community. Carnegie Mellon University's Software Engineering Institute surveyed 24 organization to create a broad picture of training as it currently exists in industry. They then chose three of these organizations for an in-depth study to identify the best training practices and enablers to those practices. This report summarizes the results of the survey and the in-depth study, and discusses the best practices and enablers that were identified. Integrating Quality Modeling with Requirements Engineering This paper introduces a structured goal-oriented agent-based process modelling framework, where advanced requirements engineering techniques are combined with software quality modelling approaches, to provide an environment within which the stakeholders and the analysts can easily cooperate to discover, verify and validate the new IT system requirements. It forces and assists the stakeholders, in particular the customer, to an early definition of the desired system functionality and quality attributes, improving our capability of achieving customer satisfaction. Introduction to Software Engineering Practices Using Model-Based Verification This is an introductory report on the use of model-based verification techniques within software development and upgrade practices. It presents the specific activities and responsibilities that are required of engineers who use the model-based verification paradigm and describes proposed approaches for integrating model-based verification into an organization’s software engineering practices. The approaches outlined in this report are preliminary concepts for the integration of model building and analysis techniques into software engineering review and inspection practices. These techniques are presented as both practices within peer review processes and as autonomous engineering investigations. The objective of this report is to provide a starting point for the use of model-based verification techniques and a framework for their evaluation in real-world applications. It is expected that the results of pilot studies that employ the preliminary approaches described here will form the basis for improving the practices themselves and software verification generally. Linking the QSM Productivity Index with the SEI Maturity Level When the SEI Software Development Maturity Assessment Methodology started to be used to measure the software development capability of organizations, QSM® took a keen interest because they had been doing something similar in concept since about 1982. At QSM®, they gradually enhanced their capability to do meaningful quantitative productivity assessments and commercially offered these services under two names -- SEAS (Software Engineering Assessment Service) and PEP (Productivity Enhancement Program). They developed a measurement tool (PADS® - Productivity Analysis Database System) to analyze the data and do comparative analyses related to the large database of software projects they have been collecting for more than ten years. PADS has been in service for more than ten years and is the primary tool used in conducting SEAS and PEP analyses. Managing Software Engineering Experience for Comprehensive Reuse Today’s software developments are faced with steadily increasing expectations: software has to be developed faster, better, and cheaper. At the same time, application complexity increases. Meeting these demands requires fast, continuous learning and the reuse of past experience on the part of the project teams. Thus, learning and reuse should be supported by well-defined processes applicable to all kinds of experience which are stored in an organizational memory. In this paper, we introduce a tool architecture supporting continuous learning and reuse of all kinds of experience from the software engineering domain and present the underlying methodology. The Project Matrix: a Model for Software Engineering Project Management The Project Matrix is a project management model of a software development project. This model requires no special resources other than those normally assigned to a software development project and has proved to be effective in coordinating the work of many people, managing the operations of the project, reducing the complexity of the software development process, and producing high quality results. Technical Concepts of Component-Based Software Engineering The Software Engineering Institute is undertaking a feasibility study of “component-based software engineering” (CBSE). The objective of this study is to determine whether CBSE has the potential to advance the state of software engineering practice and, if so, whether the SEI can contribute to this advancement. This report is the second part of a three-part report on the study. Volume I contains a market assessment for CBSE. Volume III outlines a proposed course of action for the SEI. Volume II, this report, establishes the technical foundation for SEI work in CBSE. The paper asserts that the key technical challenge facing CBSE is to ensure that the properties of a system of components can be predicted from the properties of the components themselves. The key technical concepts of CBSE that are needed to support this vision are described: component, interface, contract, component model, component framework, composition, and certification. Using the Software Peer Review Process to Obtain Measurable Pay Back This paper presents an overview of the Software Engineering Institute's Level-3 Key Process Area (KPA) - Peer Reviews. A recent case study of a large U.S.-based fortune 100 company provides suggestions on a tailored (dependent on size and scope of the project) approach to locate software defects early in the product life cycle and provide causal analysis of the process (necessary for improving the process). In addition, a pay back scheme is also presented which shows the return on investment (ROI) of using the peer review process. The pay back on performing peer reviews has been, to-date, subjective and lacking in quantitative financial measures. Why Planning is Better with Estimation than Without In this paper the role estimation plays in the planning process for software projects will be examined. The key goal of the planning process is to identify and select the best solution to the problem or opportunity at hand in light of the business objectives of the organization. Most organizations employ some form of targeting or estimation approach in the project planning process without understanding the distinction. The project planning process activity is failing most organizations. The Standish Group in a report published in 1995, catalogued the extent of the problems (see box). KPMG has also identified that in 48% of cases of project overruns the root cause was attributed to poor planning and estimating. This paper will be of interest to those within organizations that are responsible for the project planning activity. Typically this will be a Team Leader or Project Manager. The concepts addressed are relevant to a wide range of software organizations; including corporate MIS functions, Independent Software Vendors (ISV’s) or developers, and government. Why Reengineering Projects Fail The purpose of this report is to highlight some of the most important reasons for failures in reengineering efforts despite the best of intentions. We support our observations with examples from a variety of experiences over many years. Readers may recognize some of the situations presented here and be tempted to conclude that the examples are taken from their own organizations, but similar missteps occur quite frequently. |
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