We were delighted to have the paper "A Methodology for Collecting Valid Software Engineering Data", by Victor Basili and David Weiss (1984) considered one of the most influential papers of IEEE Transaction of Software Engineering's first decade. The paper discusses data or information on software quality and what were the most effective software development techniques. It was published in November, 1984. It was written at a time when software development was just becoming widespread practice, but it was not common to use data or information on software quality in order to learn what were the most effective software development techniques under different conditions. To try to alleviate this problem, we suggested that when people (or organizations) developed software, they should try to measure the effectiveness of their development techniques. In particular, since software is typically long-living, change data should be collected so that methods and processes could be managed.

This article assesses the challenges that software engineering research faces in achieving its potential. It also proposes a way for the field to move forward and become more impactful through collaborative research and innovation between public research and industry.

This chapter introduces the GQM(+) Strategies approach for aligning organizational goals and strategies through measurement. We first explain the basic idea of combining alignment and measurement within GQM(+) Strategies, which provides an integrated method for explicitly defining organizational goals and controls for the execution of those plans. Next, we describe in detail the core components of GQM(+) Strategies. This includes a specification of the GQM(+) Strategies model as well as the description of the GQM(+) Strategies process for defining, controlling, and continuously improving organizational goals and strategies.

Measurement provides many benefits to organizations of all types. However, measurement confined to the project level is limited in its ability to provide benefits throughout the organization. Measurement has always been used to help organizations assess and monitor various aspects of their operations and aid executives in strategic decision-making.

In this phase, the plans we prepared in the "Plan Grid Implementation" phase are executed, i.e., project strategies are implemented according to strategy plans and the measurement data are collected according to the measurement plans. Table 7.1 summarizes the objectives, inputs, basic activities, and outcomes of this phase.

In this phase, we characterize the context of the GQM+Strategies application by defining the organizational scope of the method's application and specifying the characteristics of the application environment. The environmental characteristics encompass actual and uncertain attributes of the method application environment that determine the applicability of the method and that should be considered when building and maintaining GQM+Strategies grids. Table 4.1 summarizes the objectives, inputs, basic activities, and outcomes of this phase. In the following sections, we will describe the individual activities of this phase in more detail.

During several applications of GQM+Strategies at different organizations, questions were often raised about the relationship between GQM+Strategies and other methods and frameworks. Therefore, in this section, we will discuss the most important methods and frameworks from different domains that are related to GQM+Strategies. We will address relationships with approaches to organizational performance measurement as well as to process improvement and reengineering. For this purpose, we will briefly describe these related approaches and illustrate how GQM+Strategies could be used as a complement to or as a substitute for these methods or frameworks.

In software-intensive organizations, an organizational management system will not guarantee organizational success unless the business strategy can be translated into a set of operational software goals. The Goal Question Metric (GQM) approach has proven itself useful in a variety of industrial settings to support quantitative software project management. However, it does not address linking software measurement goals to higher-level goals of the organization in which the software is being developed. This linkage is important, as it helps to justify software measurement efforts and allows measurement data to contribute to higher-level decisions. In this paper, we propose a GQM+Strategies(R) measurement approach that builds on the GQM approach to plan and implement software measurement. GQM+Strategies(R) provides mechanisms for explicitly linking software measurement goals to higher-level goals for the software organization, and further to goals and strategies at the level of the entire business. The proposed method is illustrated in the context of an example application of the method.

In this phase, we ensure the conditions for the successful application of GQM+Strategies by securing the commitment and resources for using the method. Furthermore, responsibilities are defined and training is provided for all people involved. Table 3.1 summarizes the objectives, inputs, basic activities, and outcomes of this phase. In the following sections, we will describe the individual activities of this phase in more detail.

In this phase, we derive the GQM(+) Strategies Grid. In particular, we specify and align organizational goals and strategies within the GQM(+)Strategies scope, and we quantify goals using GQM graphs. Table 5.1 summarizes the objectives, inputs, basic activities, and outcomes of this phase. In the following sections, we will describe the individual activities of this phase in more detail.

Aligning an organizations goals and strategies requires specifying their rationales and connections so that the links are explicit and allow for analytic reasoning about what is successful and where improvement is necessary. This book provides guidance on how to achieve this alignment, how to monitor the success of goals and strategies and use measurement to recognize potential failures, and how to close alignment gaps. It uses the GQM+Strategies approach, which provides concepts and actionable steps for creating the link between goals and strategies across an organization and allows for measurement-based decision-making. After outlining the general motivation for organizational alignment through measurement, the GQM+Strategies approach is described concisely, with a focus on the basic model that is created and the process for creating and using this model. The recommended steps of all six phases of the process are then described in detail with the help of a comprehensive application example. Finally, the industrial challenges addressed by the method and cases of its application in industry are presented, and the relations to other approaches, such as Balanced Scorecard, are described. The book concludes with supplementary material, such as checklists and guidelines, to support the application of the method. This book is aimed at organization leaders, managers, decision makers, and other professionals interested in aligning their organizations goals and strategies and establishing an efficient strategic measurement program. It is also interesting for academic researchers looking for mechanisms to integrate their research results into organizational environments.

Determining whether systems achieve desired emergent properties, such as safety or reliability, requires an analysis of the system as a whole, often in later development stages when changes are difficult and costly to implement. In this article we propose the Process Risk Indicator (PRI) methodology for analyzing and evaluating emergent properties early in the development cycle. A fundamental assumption of system engineering is that risk mitigation processes reduce system risks, yet these processes may also be a source of risk: (1) processes may not be appropriate for achieving the desired emergent property; or (2) processes may not be followed appropriately. PRI analyzes development process artifacts (e.g., designs pertaining to reliability or safety analysis reports) to quantify process risks that may lead to higher system risk. We applied PRI to the hazard analysis processes of a network-centric, Department of Defense system-of-systems and two NASA spaceflight projects to assess the risk of not achieving one such emergent property, software safety, during the early stages of the development lifecycle. The PRI methodology was used to create measurement baselines for process indicators of software safety risk, to identify risks in the hazard analysis process, and to provide feedback to projects for reducing these risks.