Jürgen Münch

Linking Software Development and Business Strategy Through Measurement

The GQM+Strategies approach extends the goal/question/metric paradigm for measuring the success or failure of goals and strategies, adding enterprise-wide support for determining action on the basis of measurement results. An organization can thus integrate its measurement program across all levels.

GQM^+ Strategies -- Aligning Business Strategies with Software Measurement

GQM+Strategies is a measurement approach that builds on the well-tested GQM approach to planning and implementing software measurement. Although GQM has proven itself useful in a variety of industrial settings, one recognized weakness is the difficulty for GQM users to link 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. GQM+strategies 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.

Software project control centers: concepts and approaches

On-line interpretation and visualization of project data are gaining increasing importance on the long road towards predictable and controllable software project execution. In the context of software development, only few techniques exist for supporting these tasks. This is caused particularly by the often insufficient use of engineering principles in the software development domain. Beyond that, interpretation and visualization techniques from other domains (such as business or production processes) are not directly applicable to software processes because of the specific characteristics of software development. A software project control center (SPCC) is a means for collecting, interpreting, and visualizing measurement data in order to provide purpose- and role-oriented information to all involved parties (e.g., project manager, quality assurer) during the execution of a project. This article presents a reference model for concepts and definitions around SPCCs. Based on this reference model, a characterization and classification of essential approaches contributing to this field is given. Finally, an outline for future research is derived from identified deficiencies of existing approaches.

Factors Influencing Software Development Productivity - State of the Art and Industrial Experiences

Abstract Managing software development productivity is a key issue in software organizations. Business demands for shorter time‐to‐market while maintaining high product quality force software organizations to look for new strategies to increase development productivity. Traditional, simple delivery rates employed to control hardware production processes have turned out not to work when simply transferred to the software domain. The productivity of software production processes may vary across development contexts dependent on numerous influencing factors. Effective productivity management requires considering these factors. Yet, there are thousands of possible factors and considering all of them would make no sense from the economical point of view. Therefore, productivity modeling should focus on a limited number of factors with the most significant impact on productivity. In this chapter, we present a comprehensive overview of productivity factors recently considered by software practitioners. The study results are based on the review of 126 publications as well as international experiences of the Fraunhofer Institute, including the most recent 13 industrial projects, four workshops, and eight surveys on software productivity. The aggregated results show that the productivity of software development processes still depends significantly on the capabilities of developers as well as on the tools and methods they use.

Development of a hybrid cost estimation model in an iterative manner

Cost estimation is a very crucial field for software developing companies. The acceptance of an estimation technique is highly dependent on estimation accuracy. Often, this accuracy is only determined after an initial application. Possible further steps for improving the underlying estimation model typically do not influence the decision on whether to discard the technique or deploy it. In addition, most estimation techniques do not explicitly support the evolution of the underlying estimation model in an iterative manner. This increases the risk of overlooking some important cost drivers or data inconsistencies. This paper presents an enhanced process for developing a CoBRA® cost estimation model by systematically including iterative analysis and feedback cycles, and its evaluation in a software development unit of Oki Electric Industry Co., Ltd., Japan. During the model improvement cycles, estimation accuracy was improved from an initial 120% down to 14%. In addition, lessons learned with the iterative development approach are described.

A systematic mapping study on the combination of static and dynamic quality assurance techniques

Context: A lot of different quality assurance techniques exist to ensure high quality products. However, most often they are applied in isolation. A systematic combination of different static and dynamic quality assurance techniques promises to exploit synergy effects, such as higher defect detection rates or reduced quality assurance costs. However, a systematic overview of such combinations and reported evidence about achieving synergy effects with such kinds of combinations is missing. Objective: The main goal of this article is the classification and thematic analysis of existing approaches that combine different static and dynamic quality assurance technique, including reported effects, characteristics, and constraints. The result is an overview of existing approaches and a suitable basis for identifying future research directions. Method: A systematic mapping study was performed by two researchers, focusing on four databases with an initial result set of 2498 articles, covering articles published between 1985 and 2010. Results: In total, 51 articles were selected and classified according to multiple criteria. The two main dimensions of a combination are integration (i.e., the output of one quality assurance technique is used for the second one) and compilation (i.e., different quality assurance techniques are applied to ensure a common goal, but in isolation). The combination of static and dynamic analyses is one of the most common approaches and usually conducted in an integrated manner. With respect to the combination of inspection and testing techniques, this is done more often in a compiled way than in an integrated way. Conclusion: The results show an increased interest in this topic in recent years, especially with respect to the integration of static and dynamic analyses. Inspection and testing techniques are currently mostly performed in an isolated manner. The integration of inspection and testing techniques is a promising research direction for the exploitation of additional synergy effects.

Building blocks for continuous experimentation

Development of software-intensive products and services increasingly occurs by continuously deploying product or service increments, such as new features and enhancements, to customers. Product and service developers need to continuously find out what customers want by direct customer feedback and observation of usage behaviour, rather than indirectly through up-front business analyses. This paper examines the preconditions for setting up an experimentation system for continuous customer experiments. It describes the building blocks required for such a system. An initial model for continuous experimentation is analytically derived from prior work. The model is then matched against empirical case study findings from a startup company and adjusted. Building blocks for a continuous experimentation system and infrastructure are presented. A suitable experimentation system requires at least the ability to release minimum viable products or features with suitable instrumentation, design and manage experiment plans, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper and rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and the integration of experiment results in both the product development cycle and the software development process.

A Survey on the State of the Practice in Distributed Software Development: Criteria for Task Allocation

The allocation of tasks can be seen as a success-critical management activity in distributed development projects. However, such task allocation is still one of the major challenges in global software development due to an insufficient understanding of the criteria that influence task allocation decisions. This article presents a qualitative study aimed at identifying and understanding such criteria that are used in practice. Based on interviews with managers from selected software development organizations, criteria currently applied in industry are identified. One important result is, for instance, that the sourcing strategy and the type of software to be developed have a significant effect on the applied criteria. The article presents the goals, design, and results of the study as well as an overview of related and future work.

Teaching disciplined software development

Discipline is an essential prerequisite for the development of large and complex software-intensive systems. However, discipline is also important on the level of individual development activities. A major challenge for teaching disciplined software development is to enable students to experience the benefits of discipline and to overcome the gap between real professional scenarios and scenarios used in software engineering university courses. Students often do not have the chance to internalize what disciplined software development means at both the individual and collaborative level. Therefore, students often feel overwhelmed by the complexity of disciplined development and later on tend to avoid applying the underlying principles. The Personal Software Process (PSP) and the Team Software Process (TSP) are tools designed to help software engineers control, manage, and improve the way they work at both the individual and collaborative level. Both tools have been considered effective means for introducing discipline into the conscience of professional developers. In this paper, we address the meaning of disciplined software development, its benefits, and the challenges of teaching it. We present a quantitative study that demonstrates the benefits of disciplined software development on the individual level and provides further experience and recommendations with PSP and TSP as teaching tools.

Requirements and constructors for tailoring software processes: a systematic literature review

Organizations developing software-based systems or services often need to tailor process reference models—including product-oriented and project-oriented processes—to meet both their own characteristics and those of their projects. Existing process reference models, however, are often defined in a generic manner. They typically offer only limited mechanisms for adapting processes to the needs of organizational units, project goals, and project environments. This article presents a systematic literature review of peer-reviewed conference and journal articles published between 1990 and 2009. Our aim was both to identify requirements for process-tailoring notation and to analyze those tailoring mechanisms that are currently in existence and that consistently support process tailoring. The results show that the software engineering community has demonstrated an ever-increasing interest in software process tailoring, ranging from the consideration of theoretical proposals regarding how to tailor processes to the scrutiny of practical experiences in organizations. Existing tailoring mechanisms principally permit the modeling of variations of activities, artifacts, or roles by insertion or deletion. Two types of variations have been proposed: the individual modification of process elements and the simultaneous variation of several process elements. Resolving tailoring primarily refers to selecting or deselecting optional elements or to choosing between alternatives. It is sometimes guided by explicitly defined processes and supported by tools or mechanisms from the field of knowledge engineering. The study results show that tailoring notations are not as mature as the industry requires if they are to provide the kind of support for process tailoring that fulfills the requirements identified, i.e., including security policies for the whole process, or carrying out one activity rather than another. A notation must therefore be built, which takes these requirements into consideration in order to permit variant-rich processes representation and use this variability to consistently support process tailoring.