Ove Armbrust

Software Process Definition and Management

* First book that gives a comprehensive introduction into software process definition and management* It enables readers to develop useful process models that are suitable for their own purposes* Special chapters on measurement and determination of the effectiveness of processes The concept of processes is at the heart of software and systems engineering. Software process models integrate software engineering methods and techniques and are the basis for managing large-scale software and IT projects. High product quality routinely results from high process quality.Software process management deals with getting and maintaining control over processes and their evolution. Becoming acquainted with existing software process models is not enough, though. It is important to understand how to select, define, manage, deploy, evaluate, and systematically evolve software process models so that they suitably address the problems, applications, and environments to which they are applied. Providing basic knowledge for these important tasks is the main goal of this textbook.Mnch and his co-authors aim at providing knowledge that enables readers to develop useful process models that are suitable for their own purposes. They start with the basic concepts. Subsequently, existing representative process models are introduced, followed by a description of how to create individual models and the necessary means for doing so (i.e., notations and tools). Lastly, different possible usage scenarios for process management are highlighted (e.g. process improvement and software process simulation).Their book is aimed at students and researchers working on software project management, software quality assurance, and software measurement; and at practitioners who are interested in process definition and management for developing, maintaining, and operating software-intensive systems and services.

Using empirical knowledge from replicated experiments for software process simulation: a practical example

Empirical knowledge from software engineering studies is an important source for the creation of accurate simulation models. This article describes the development of a simulation model using empirical knowledge gained from an experiment at the NASA/GSFC Software Engineering Laboratory and from two replications at the University of Kaiserslautern. Data and analysis results are used to identify influence dependencies between parameters, and to calibrate models. The goal of the model is the determination of the effects (i.e. defect detection efficacy) of a requirements inspection process under varying contexts. The purpose is to provide decision support for project managers and process engineers when planning or changing a development process. This article describes the systematic model development with a focus on the use of empirical knowledge. Additionally, limitations of the model, lessons learned, and research questions for future work are sketched. The model performed well in an initial validation run, with only little deviation from experimental values.

Prescriptive Process Models

This chapter introduces prescriptive process models as a means of instructing an organization on how to achieve its business, software development, and improvement goals. It is structured into four main parts. First, two major classes of prescriptive process models are distinguished: lifecycle models and engineering models. These classes are described and discussed with respect to their advantages and challenges. Second, a number of widely used process standards are introduced to give an impression of the material the software industry is currently working with. Since these standards are not intended or fit for direct application, they must be amended and transformed into more user-friendly representations. Hence, two types of process representations are introduced: process handbooks and electronic process guides (EPGs). Finally, it is typically not sufficient to prepare and publish a process handbook or EPG: Any new or changed process must be deployed in a systematic manner, to cause as little unnecessary pain for the organization as possible. The fourth part of this chapter thus discusses the deployment of a prescriptive process model to an organization. Figure 2.1 displays the chapter structure.

Software Process Simulation

This chapter introduces software process simulation as a means to amend and complement empirical studies, for example, to evaluate changing contexts and to analyze process dynamics. It introduces two types of simulation models, namely continuous and discrete-event models, as well as their combination in hybrid models. In addition, this chapter describes a systematic method for the creation of simulation models and introduces an existing library of simulation model components that can be easily reused. Finally, it explains how process simulation can be combined with empirical studies to accelerate process understanding and improvement. Figure 7.1 displays the chapter structure.

Process Modeling Notations and Tools

This chapter introduces notations for process modeling and gives an overview of tool support for process modeling and management. The chapter is structured into three main parts. First, it introduces a set of criteria for process modeling notations in order to enable the reader to distinguish different process modeling notations and to understand that different purposes might be addressed by different notations. Second, it discusses two different process modeling notations, namely, MVP-L and SPEM 2.0, and characterizes them according to the previously defined criteria. Finally, it introduces process management tools by discussing the ECMA/NIST framework and the Eclipse Process Framework (EPF) Composer. Figure 4.1 displays an overview of the chapter structure.