Jürgen Münch

Fabian Fagerholm, Patrik Johnson, Alejandro Sánchez Guinea et al.

Nowadays, many software projects are partially or completely open-source based. There is an increasing need for companies to participate in open-source software (OSS) projects, e.g., in order to benefit from open source ecosystems. OSS projects introduce particular challenges that have to be understood in order to gain the benefits. One such challenge is getting newcomers onboard into the projects effectively. Similar challenges may be present in other self-organised, virtual team environments. In this paper we present preliminary observations and results of in-progress research that studies the process of onboarding into virtual OSS teams. The study is based on a program created and conceived at Stanford University in conjunction with Facebook's Education Modernization program. It involves the collaboration of more than a dozen international universities and nine open source projects. More than 120 students participated in 2013. The students have been introduced to and supported by mentors experienced in the participating OSS projects. Our findings indicate that mentoring is an important factor for effective onboarding in OSS projects, promoting cohesion within distributed teams and maintaining an appropriate pace.

Marco Kuhrmann, Paolo Tell, Regina Hebig et al.

Together with many success stories, promises such as the increase in production speed and the improvement in stakeholders' collaboration have contributed to making agile a transformation in the software industry in which many companies want to take part. However, driven either by a natural and expected evolution or by contextual factors that challenge the adoption of agile methods as prescribed by their creator(s), software processes in practice mutate into hybrids over time. Are these still agile? In this article, we investigate the question: what makes a software development method agile? We present an empirical study grounded in a large-scale international survey that aims to identify software development methods and practices that improve or tame agility. Based on 556 data points, we analyze the perceived degree of agility in the implementation of standard project disciplines and its relation to used development methods and practices. Our findings suggest that only a small number of participants operate their projects in a purely traditional or agile manner (under 15%). That said, most project disciplines and most practices show a clear trend towards increasing degrees of agility. Compared to the methods used to develop software, the selection of practices has a stronger effect on the degree of agility of a given discipline. Finally, there are no methods or practices that explicitly guarantee or prevent agility. We conclude that agility cannot be defined solely at the process level. Additional factors need to be taken into account when trying to implement or improve agility in a software company. Finally, we discuss the field of software process-related research in the light of our findings and present a roadmap for future research.

Paolo Tell, Jil Klünder, Steffen Küpper et al.

Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large-scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.

Marco Kuhrmann, Philipp Diebold, Stephen MacDonell et al.

Software and system development is complex and diverse, and a multitude of development approaches is used and combined with each other to address the manifold challenges companies face today. To study the current state of the practice and to build a sound understanding about the utility of different development approaches and their application to modern software system development, in 2016, we launched the HELENA initiative. This paper introduces the 2nd HELENA workshop and provides an overview of the current project state. In the workshop, six teams present initial findings from their regions, impulse talk are given, and further steps of the HELENA roadmap are discussed.

Paolo Tell, Jil Klünder, Steffen Küpper et al.

Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods -- so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants' selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods.

Jil Klünder, Dzejlana Karajic, Paolo Tell et al.

Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.

Michael Kläs, Jens Heidrich, Jürgen Münch et al.

Managing quality (such as service availability or process adherence) during the development, operation, and maintenance of software(-intensive) systems and services is a challenging task. Although many organizations need to define, control, measure, and improve various quality aspects of their devel- opment artifacts and processes, nearly no guidance is available on how to select, adapt, define, combine, use, and evolve quality models. Catalogs of quality models as well as selection and tailoring processes are widely missing. One essential reason for this tremendous lack of support is that software development is a highly context-dependent process. Therefore, quality models always need to be adaptable to the respective project goals and contexts. A first step towards better support for selecting and adapting quality models can be seen in a classification of existing quality models, especially with respect to their suitability for different purposes and contexts. Such a classification of quality models can be applied to provide an integrated overview of the variety of quality models. This article presents the idea of so called comprehensive quality model landscapes (CQMLs), which provide a classification scheme for quality models and help to get an overview of existing quality models and their relationships. The article describes the usage goals for such landscapes, presents a classification scheme, presents the initial concept of such landscapes, illustrates the concept with selected examples, and sketches open questions and future work.

Jens Heidrich, Jürgen Münch

Many software development organizations still lack support for obtaining intellectual control over their software development processes and for determining the performance of their processes and the quality of the produced products. Systematic support for detecting and reacting to critical project states in order to achieve planned goals is usually missing. One means to institutionalize measurement on the basis of explicit models is the development and establishment of a so-called Software Project Control Center (SPCC) for systematic quality assurance and management support. An SPCC is comparable to a control room, which is a well known term in the mechanical production domain. Its tasks include collecting, in- terpreting, and visualizing measurement data in order to provide context-, purpose-, and role-oriented information for all stakeholders (e.g., project managers, quality assurance manager, developers) during the execution of a software development project. The article will present an overview of SPCC concepts, a concrete instantiation that supports goal-oriented data visualization (G-SPCC approach), and experiences from practical applications.

Ioana Rus, Holger Neu, Jürgen Münch

So far there have been several efforts for developing software process simulators. However, the approaches for developing the simulators seem to have been ad-hoc and no systematic methodology exists. Since modeling and simulation in support of software development should become more popular (and there are signs that it does), there is a need for migrating modeling from craft to engineering. This article proposes such a systematic method, focused on the development of discrete simulation-based decision models, but extensible to other modeling approaches as well.

Jürgen Münch, Jens Heidrich

Online interpretation and visualization of project data are gaining increasing importance on the long road towards predictable and controllable software project execution. This paper sketches the Sprint I controlling approach for software development projects and gives first evaluation results. The approach is grounded on the usage of context-oriented cluster curves and integrated in the framework of software project control centers.

Fabio Bella, Jürgen Münch, Alexis Ocampo

The creation and deployment of software development processes for new domains (such as wireless Internet services) is a challenging task due to the lack of knowledge about adequate engineering techniques and their effects. In addition, time-to-market pressure prevents applying long-lasting maturation of processes. Nevertheless, developing software of a predetermined quality in a predictable fashion can only be achieved with systematic development processes and the use of engineering principles. A descriptive approach promises to quickly create initial valuable process models and quantitative baselines that can be seen as starting points for continuous improvement activities. This paper describes the creation of software development processes for the development of wireless Internet services based on the observation of pilot projects that were performed at distributed development sites. Different techniques and tools such as descriptive process modeling, process documentation generation, goal-oriented measurement, and capturing qualitative experience were combined to gain process baselines. Results show that the observation-based approach helped to quickly come up with stable context-oriented development processes and get a better understanding of their effects with respect to quantitative and qualitative means.

Fabio Bella, Jürgen Münch, Alexis Ocampo

New, emerging domains such as the engineering of wireless Internet services are characterized by a lack of experience based on quantitative data. Systematic tracking and observation of representative pilot projects can be seen as one means to capture experience, get valuable insight into a new domain, and build initial baselines. This helps to improve the planning of real development projects in business units. This article describes an approach to capture software development experience for the wireless Internet services domain by conducting and observing a series of case studies in the field. Initial baselines concerning effort distribution from the development of two wireless Internet pilot services are presented. Furthermore, major domain-specific risk factors are discussed based on the results of project retrospectives conducted with the developers of the services.

Holger Neu, Thomas Hanne, Jürgen Münch et al.

Organizations that develop software have recognized that software process models are particularly useful for maintaining a high standard of quality. In the last decade, simulations of software processes were used in several settings and environments. This paper gives a short overview of the benefits of software process simulation and describes the development of a discrete-event model, a technique rarely used before in that field. The model introduced in this paper captures the behavior of a detailed code inspection process. It aims at reducing the risks inherent in implementing inspection processes and techniques in the overall development process. The determination of the underlying cause-effect relations using data mining techniques and empirical data is explained. Finally, the paper gives an outlook on our future work.

Ulrike Becker-Kornstaedt, Daniela Boggio, Jürgen Münch et al.

The development of software for wireless services on the Internet is a challenging task due to the extreme time-to-market pressure, the newness of the application domain, and the quick evolution of the technical infrastructure. Nevertheless, developing software of a predetermined quality in a predictable fashion can only be achieved with systematic development processes and the use of engineering principles. Thus, systematic development processes for this domain are needed urgently. This article presents a method for the design of an adaptable software development process based on existing practices from related domains, industrial piloting, and expert knowledge. First results of the application of the method for the wireless Internet services domain are described. The benefit for the reader is twofold: the article describes a validated method on how to gain process knowledge for an upcoming field fast and incrementally. Furthermore, first results of the process design for the wireless Internet services domain are given.

Alejandro Fernández, Badie Garzaldeen, Ines Grützner et al.

Recently, the awareness of the importance of distributed software development has been growing in the software engineering community. Economic constraints, more and more outsourcing of development activities, and the increasing spatial distribution of companies come along with challenges of how to organize distributed development. In this article, we reason that a common process understanding is mandatory for successful distributed development. Integrated process planning, guidance and enactment are seen as enabling technologies to reach a unique process view. We sketch a synthesis of the software process modeling environment SPEARMINT and the XCHIPS system for web-based process support. Hereby, planners and developers are provided with collaborative planning and enactment support and advanced process guidance via electronic process guides (EPGs). We describe the usage of this integrated environment by using a case study for the development of a learning system.

Jürgen Münch, Jens Heidrich

Using quantitative data from past projects for software project estimation requires context knowledge that characterizes its origin and indicates its applicability for future use. This article sketches the SPRINT I technique for project planning and controlling. The underlying prediction mechanism is based on the identification of similar past projects and the building of so-called clusters with typical data curves. The article focuses on how to characterize these clusters with context knowledge and how to use context information from actual projects for prediction. The SPRINT approach is tool-supported and first evaluations have been conducted.

Adam Trendowicz, Jens Heidrich, Jürgen Münch

Cost estimation is a very crucial field for software developing companies. In the context of learning organizations, estimation applicability and accuracy are not the only acceptance criteria. The contribution of an estimation technique to the understanding and maturing of related organizational processes (such as identification of cost and productivity factors, measurement, data validation, model validation, model maintenance) has recently been gaining increasing importance. Yet, most of the proposed cost modeling approaches provide software engineers with hardly any assistance in supporting related processes. Insufficient support is provided for validating created cost models (including underlying data collection processes) or, if valid models are obtained, for applying them to achieve an organization's objectives such as improved productivity or reduced schedule. This paper presents an enhancement of the CoBRA(R) cost modeling method by systematically including additional quantitative methods into iterative analysis-feedback cycles. Applied at Oki Electric Industry Co., Ltd., Japan, the CoBRA(R) method contributed to the achievement of the following objectives, including: (1) maturation of existing measurement processes, (2) increased expertise of Oki software project decision makers regarding cost-related software processes, and, finally, (3) reduction of initial estimation error from an initial 120% down to 14%.

Ansgar Lamersdorf, Jürgen Münch, Dieter Rombach

Distributing development tasks in the context of global software development bears both many risks and many opportunities. Nowadays, distributed development is often driven by only a few factors or even just a single factor such as workforce costs. Risks and other relevant factors such as workforce capabilities, the innovation potential of different regions, or cultural factors are often not recognized sufficiently. This could be improved by using empirically-based multi-criteria distribution models. Currently, there is a lack of such decision models for distributing software development work. This article focuses on mechanisms for such decision support. First, requirements for a distribution model are formulated based on needs identified from practice. Then, distribution models from different domains are surveyed, compared, and analyzed in terms of suitability. Finally, research questions and directions for future work are given.

Jürgen Münch, Ansgar Lamersdorf

Systematic task allocation to different development sites in global software de- velopment projects can open business and engineering perspectives and help to reduce risks and problems inherent in distributed development. Relying only on a single evaluation criterion such as development cost when distributing tasks to development sites has shown to be very risky and often does not lead to successful solutions in the long run. Task allocation in global software projects is challenging due to a multitude of impact factors and constraints. Systematic allocation decisions require the ability to evaluate and compare task allocation alternatives and to effectively establish customized task allocation practices in an organization. In this article, we present a customizable process for task allocation evaluation that is based on results from a systematic interview study with practitioners. In this process, the relevant criteria for evaluating task allocation alternatives are derived by applying principles from goal-oriented measurement. In addition, the customization of the process is demonstrated, related work and limitations are sketched, and an outlook on future work is given.

Victor Basili, Jens Heidrich, Mikael Lindvall et al.

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.

Ove Armbrust, Masafumi Katahira, Yuko Miyamoto et al.

Defining process standards by integrating, harmonizing, and standardizing heterogeneous and often implicit processes is an important task, especially for large development organizations. However, many challenges exist, such as limiting the scope of process standards, coping with different levels of process model abstraction, and identifying relevant process variabilities to be included in the standard. On the one hand, eliminating process variability by building more abstract models with higher degrees of interpretation has many disadvantages, such as less control over the process. Integrating all kinds of variability, on the other hand, leads to high process deployment costs. This article describes requirements and concepts for determining the scope of process standards based on a characterization of the potential products to be produced in the future, the projects expected for the future, and the respective process capabilities needed. In addition, the article sketches experience from determining the scope of space process standards for satellite software development. Finally, related work with respect to process model scoping, conclusions, and an outlook on future work are presented.

Frank Elberzhager, Stephan Kremer, Jürgen Münch et al.

A well-known approach for identifying defect-prone parts of software in order to focus testing is to use different kinds of product metrics such as size or complexity. Although this approach has been evaluated in many contexts, the question remains if there are further opportunities to improve test focusing. One idea is to identify other types of information that may indicate the location of defect-prone software parts. Data from software inspections, in particular, appear to be promising. This kind of data might already lead to software parts that have inherent difficulties or programming challenges, and in consequence might be defect-prone. This article first explains how inspection and product metrics can be used to focus testing activities. Second, we compare selected product and inspection metrics commonly used to predict defect-prone parts (e.g., size and complexity metrics, inspection defect content metrics, and defect density metrics). Based on initial experience from two case studies performed in different environments, the suitability of different metrics for predicting defect-prone parts is illustrated. The studies revealed that inspection defect data seems to be a suitable predictor, and a combination of certain inspection and product metrics led to the best prioritizations in our contexts. In addition, qualitative experience is presented, which substantiates the expected benefit of using inspection results to optimize testing.

Olga Jaufman, Jürgen Münch

Currently, proposed development processes are often considered too generic for operational use. This often leads to a misunderstanding of the project-specific processes and its refuse. One reason for non-appropriate project-specific processes is insufficient support for the tailoring of generic processes to project characteristics and context constraints. To tackle this problem, we propose a method for the acquisition of a project-specific process. This method uses a domain-specific process line for top-down process tailoring and supports bottom-up refinement of the defined generic process based on tracking process activities. The expected advantage of the method is tailoring efficiency gained by usage of a process line and higher process adherence gained by bottom-up adaptation of the process. The work described was conducted in the automotive domain. This article presents an overview of the so-called Emergent Process Acquisition method (EPAc) and sketches an initial validation study.

Adam Trendowicz, Jürgen Münch, Ross Jeffery

Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project resources. Effort estimation methods founded on those goals typically focus on providing exact estimates and usually do not support objectives that have recently become important within the software industry, such as systematic and reliable analysis of causal effort dependencies. This article presents the results of a study of software effort estimation from an industrial perspective. The study surveys industrial objectives, the abilities of software organizations to apply certain estimation methods, and actually applied practices of software effort estimation. Finally, requirements for effort estimation methods identified in the survey are compared against existing estimation methods.

Adam Trendowicz, Michael Ochs, Axel Wickenkamp et al.

Managing software development productivity and effort are key issues in software organizations. Identifying the most relevant factors influencing project performance is essential for implementing business strategies by selecting and adjusting proper improvement activities. There is, however, a large number of potential influencing factors. This paper proposes a novel approach for identifying the most relevant factors influencing software development productivity. The method elicits relevant factors by integrating data analysis and expert judgment approaches by means of a multi-criteria decision support technique. Empirical evaluation of the method in an industrial context has indicated that it delivers a different set of factors compared to individual data- and expert-based factor selection methods. Moreover, application of the integrated method significantly improves the performance of effort estimation in terms of accuracy and precision. Finally, the study did not replicate the observation of similar investigations regarding improved estimation performance on the factor sets reduced by a data-based selection method.

Jens Heidrich, Jürgen Münch

Software Cockpits, also known as Software Project Control Centers, support the management and controlling of software and system development projects and provide means for quantitative measurement-based project control. Currently, many companies are developing simple control dashboards that are mainly based on Spreadsheet applications. Alternatively, they use solutions providing a fixed set of project control functionality that cannot be sufficiently customized to their specific needs and goals. Specula is a systematic approach for defining reusable, customizable control components and instantiate them according to different organizational goals and characteristics based on the Quality Improvement Paradigm (QIP) and GQM. This article gives an overview of the Specula approach, including the basic conceptual model, goal-oriented measurement, and the composition of control components based on explicitly stated measurement goals. Related approaches are discussed and the use of Specula as part of industrial case studies is described.

Martín Soto, Jürgen Münch

Software development processes are subject to variations in time and space, variations that can originate from learning effects, differences in application domains, or a number of other causes. Identifying and analyzing such differences is crucial for a variety of process activities, like defining and evolving process standards, or analyzing the compliance of process models to existing standards, among others. In this paper, we show why appropriately identifying, describing, and visualizing differences between process models in order to support such activities is a highly challenging task. We present scenarios that motivate the need for process model difference analysis, and describe the conceptual and technical challenges arising from them. In addition, we sketch an initial tool-based approach implementing difference analysis, and contrast it with similar existing approaches. The results from this paper constitute the requirements for our ongoing development effort, whose objectives we also describe briefly.

Martín Soto, Jürgen Münch

An essential characteristic of mature software and system development organizations is the definition and use of explicit process models. For a number of reasons, it can be valuable to produce new process models by tailoring existing process standards (such as the V-Modell XT). Both process models and standards evolve over time in order to integrate improvements or adapt the process models to context changes. An important challenge for a process engineering team is to keep tailored process models aligned over time with the standards originally used to produce them. This article presents an approach that supports the alignment of process standards evolving in parallel to derived process models, using an actual industrial example to illustrate the problems and potential solutions. We present and discuss the results of a quantitative analysis done to determine whether a strongly tailored model can still be aligned with its parent standard and to assess the potential cost of such an alignment. We close the paper with conclusions and outlook.

Alexis Ocampo, Jürgen Münch

Evolving a software process model without a retrospective and, in consequence, without an understanding of the process evolution, can lead to severe problems for the software development organization, e.g., inefficient performance as a consequence of the arbitrary introduction of changes or difficulty in demonstrating compliance to a given standard. Capturing information on the rationale behind changes can provide a means for better understanding process evolution. This article presents the results of an exploratory study with the goal of understanding the nature of process changes in a given context. It presents the most important issues that motivated process engineers changing important aerospace software process standards during an industrial project. The study is part of research work intended to incrementally define a systematic mechanism for process evolution supported by rationale information.

Martín Soto, Alexis Ocampo, Jürgen Münch

Software process models must change continuously in order to remain consistent over time with the reality they represent, as well as relevant to the task they are intended for. Performing these changes in a sound and disci- plined fashion requires software process model evolution to be understood and controlled. The current situation can be characterized by a lack of understanding of software process model evolution and, in consequence, by a lack of systematic support for evolving software process models in organizations. This paper presents an analysis of the evolution of a large software process standard, namely, the process standard for the German Federal Government (V-Modell(R) XT). The analysis was performed with the Evolyzer tool suite, and is based on the complete history of over 600 versions that have been created during the development and maintenance of the standard. The analysis reveals similarities and differences between process evolution and empirical findings in the area of software system evolution. These findings provide hints on how to better manage process model evolution in the future.

Jens Heidrich, Adam Trendowicz, Jürgen Münch et al.

The increasing availability of cost-relevant data in industry allows companies to apply data-intensive estimation methods. However, available data are often inconsistent, invalid, or incomplete, so that most of the existing data-intensive estimation methods cannot be applied. Only few estimation methods can deal with imperfect data to a certain extent (e.g., Optimized Set Reduction, OSR(c)). Results from evaluating these methods in practical environments are rare. This article describes a case study on the application of OSR(c) at Toshiba Information Systems (Japan) Corporation. An important result of the case study is that estimation accuracy significantly varies with the data sets used and the way of preprocessing these data. The study supports current results in the area of quantitative cost estimation and clearly illustrates typical problems. Experiences, lessons learned, and recommendations with respect to data preprocessing and data-intensive cost estimation in general are presented.

Jürgen Münch

The development of high-quality software or software-intensive systems requires custom-tailored process models that fit the organizational and project goals as well as the development contexts. These models are a necessary prerequisite for creating project plans that are expected to fulfill business goals. Although project planners require individual process models custom-tailored to their constraints, software or system developing organizations also require generic processes (i.e., reference processes) that capture project-independent knowledge for similar development contexts. The latter is emphazised by assessment approaches (such as CMMI, SPICE) that require explicit process descriptions in order to reach a certain capability or maturity level. Among other concepts such as polymorphism, templates, or generator-based descriptions, software process patterns are used to describe generic process knowledge. Several approaches for describing the architecture of process patterns have already been published (e.g., [7]). However, there is a lack of descriptions on how to compose process patterns for a specific decelopment context in order to gain a custom-tailored process model for a project. This paper focuses on the composition of process patterns in a goal-oriented way. First, the paper describes which information a process pattern should contain so that it can be used for systematic composition. Second, a composition method is sketched. Afterwards, the results of a proof-of-concept evaluation of the method are described. Finally, the paper is summarized and open research questions are sketched.

Michael Kläs, Haruka Nakao, Frank Elberzhager et al.

Planning quality assurance (QA) activities in a systematic way and controlling their execution are challenging tasks for companies that develop software or software-intensive systems. Both require estimation capabilities regarding the effectiveness of the applied QA techniques and the defect content of the checked artifacts. Existing approaches for these purposes need extensive measurement data from historical projects. Due to the fact that many companies do not collect enough data for applying these approaches (especially for the early project lifecycle), they typically base their QA planning and controlling solely on expert opinion. This article presents a hybrid method that combines commonly available measurement data and context-specific expert knowledge. To evaluate the method's applicability and usefulness, we conducted a case study in the context of independent verification and validation activities for critical software in the space domain. A hybrid defect content and effectiveness model was developed for the software requirements analysis phase and evaluated with available legacy data. One major result is that the hybrid model provides improved estimation accuracy when compared to applicable models based solely on data. The mean magnitude of relative error (MMRE) determined by cross-validation is 29.6% compared to 76.5% obtained by the most accurate data-based model.

Ansgar Lamersdorf, Jürgen Münch, Alicia Fernández-del Viso Torre et al.

Many project risks in distributed software development are very different from the ones in collocated development and therefore are often overlooked. At the same time, they depend to a large extent on project-specific characteristics. This article presents a model for identifying risks early in a project. This model systematically captures experiences from past projects and is based on a set of logical rules describing how project characteristics influence typical risks in distributed development. Thus, the model is able to assess risks individually for each project. It was developed by applying qualitative content analysis to 19 interviews with practitioners. An evaluation using expert interviews showed that the risks identified by the model matched the actual experiences in 81% of the cases; of these, 40% have not been regarded yet at project start. The article describes the concepts of the model, its instantiation and evaluation, followed by a conclusion and future work.

Ansgar Lamersdorf, Jürgen Münch, Alicia Fernández-del Viso Torre et al.

Models for effort and cost estimation are important for distributed software development as well as for collocated software and system development. Standard cost models only insufficiently consider the characteristics of distributed development such as dissimilar abilities at the different sites or significant overhead due to remote collaboration. Therefore, explicit cost models for distributed development are needed. In this article, we present the initial development of a cost overhead model for a Spanish global software development organization. The model was developed using the CoBRA approach for cost estimation. As a result, cost drivers for the specific distributed development context were identified and their impact was quantified on an empirical basis. The article presents related work, an overview of the approach, and its application in the industrial context. Finally, we sketch the inclusion of the model in an approach for systematic task allocation and give an overview of future work.

Fabio Bella, Jürgen Münch, Alexis Ocampo

The merging of the Internet with the Wireless services domain has created a potential market whose characteristics are new technologies and time-to-market pressure. The lack of knowledge about new technologies and the need to be competitive in a short time demand that software organizations learn quickly about this domain and its characteristics. Additionally, the effects of development techniques in this context need to be understood. Learning from previous experiences in such a changing environment demands a clear understanding of the evidence to be captured, and how it could be used in the future. This article presents definitions of quantitative and qualitative evidence, and templates for capturing such evidence in a systematic way. Such templates were used in the context of two pilot projects dealing with the development of Wireless Internet Services.

Adam Trendowicz, Michael Kläs, Constanza Lampasona et al.

The ability to develop or evolve software or software-based systems/services with defined and guaranteed quality in a predictable way is becoming increasingly important. Essential - though not exclusive - prerequisites for this are the ability to model the relevant quality properties appropriately and the capability to perform reliable quality evaluations. Existing approaches for integrated quality modeling and evaluation are typically either narrowly focused or too generic and have proprietary ways for modeling and evaluating quality. This article sketches an ap- proach for modeling and evaluating quality properties in a uniform way, without losing the ability to build sufficiently detailed customized models for specific quality properties. The focus of this article is on the description of a multi-criteria aggregation mechanism that can be used for the evaluation. In addition, the underlying quality meta-model, an example application scenario, related work, initial application results, and an outlook on future research are presented.

Martin Kowalczyk, Jürgen Münch, Masafumi Katahira et al.

Aligning the activities of an organization with its business goals is a challenging task that is critical for success. Alignment in a multi-organizational setting requires the integration of different internal or external organizational units. The anticipated benefits of multi-organizational alignment consist of clarified contributions and increased transparency of the involved organizational units. The GQM+Strategies approach provides mechanisms for explicitly linking goals and strategies within an organization and is based on goal-oriented measurement. This paper presents the process and first-hand experience of applying GQM+Strategies in a multi-organizational setting from the aerospace industry. Additionally, the resulting GQM+Strategies grid is sketched and selected parts are discussed. Finally, the results are reflected on and an overview of future work is given.

Peter Liggesmeyer, Jens Heidrich, Jürgen Münch et al.

Many software development organizations still lack support for obtaining intellectual control over their software development processes and for determining the performance of their processes and the quality of the produced products. Systematic support for detecting and reacting to critical process and product states in order to achieve planned goals is usually missing. One means to institutionalize measurement on the basis of explicit models is the development and establishment of a so-called Software Project Control Center (SPCC) for systematic quality assurance and management support. An SPCC is comparable to a control room, which is a well known term in the mechanical production domain. One crucial task of an SPCC is the systematic visualization of measurement data in order to provide context-, purpose-, and role-oriented information for all stakeholders (e.g., project managers, quality assurance managers, developers) during the execution of a software development project. The article will present an overview of SPCC concepts, a concrete instantiation that supports goal-oriented data visualization, as well as examples and experiences from practical applications.

Michael Kläs, Frank Elberzhager, Jürgen Münch et al.

Defining strategies on how to perform quality assurance (QA) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. Planning and adjusting QA activities could benefit from accurate estimations of the expected defect content of relevant artifacts and the effectiveness of important quality assurance activities. Combining expert opinion with commonly available measurement data in a hybrid way promises to overcome the weaknesses of purely data-driven or purely expert-based estimation methods. This article presents a case study of the hybrid estimation method HyDEEP for estimating defect content and QA effectiveness in the telecommunication domain. The specific focus of this case study is the use of the method for gaining quantitative predictions. This aspect has not been empirically analyzed in previous work. Among other things, the results show that for defect content estimation, the method performs significantly better statistically than purely data-based methods, with a relative error of 0.3 on average (MMRE).

Jens Heidrich, Jürgen Münch

Setting up effective and efficient mechanisms for controlling software and system development projects is still challenging in industrial practice. On the one hand, necessary prerequisites such as established development processes, understanding of cause-effect relationships on relevant indicators, and sufficient sustainability of measurement programs are often missing. On the other hand, there are more fundamental methodological deficits related to the controlling process itself and to appropriate tool support. Additional activities that would guarantee the usefulness, completeness, and precision of the result- ing controlling data are widely missing. This article presents a conceptual architecture for so-called Software Project Control Centers (SPCC) that addresses these challenges. The architecture includes mechanisms for getting sufficiently precise and complete data and supporting the information needs of different stakeholders. In addition, an implementation of this architecture, the so-called Specula Project Support Environment, is sketched, and results from evaluating this implementation in industrial settings are presented.

Marco Kuhrmann, Daniel Méndez Fernández, Jürgen Münch

Most university curricula consider software processes to be on the fringes of software engineering (SE). Students are told there exists a plethora of software processes ranging from RUP over V-shaped processes to agile methods. Furthermore, the usual students' programming tasks are of a size that either one student or a small group of students can manage the work. Comprehensive processes being essential for large companies in terms of reflecting the organization structure, coordinating teams, or interfaces to business processes such as contracting or sales, are complex and hard to teach in a lecture, and, therefore, often out of scope. We experienced tutorials on using Java or C#, or on developing applications for the iPhone to gather more attention by students, simply speaking, as these are more fun for them. So, why should students spend their time in software processes? From our experiences and the discussions with a variety of industrial partners, we learned that students often face trouble when taking their first "real" jobs, even if the company is organized in a lean or agile shape. Therefore, we propose to include software processes more explicitly into the SE curricula. We designed and implemented a course at Master's level in which students learn why software processes are necessary, and how they can be analyzed, designed, implemented, and continuously improved. In this paper, we present our course's structure, its goals, and corresponding teaching methods. We evaluate the course and further discuss our experiences so that lecturers and researchers can directly use our lessons learned in their own curricula.

Fabian Fagerholm, Nilay Oza, Jürgen Münch

Teaching distributed software development (DSD) in project courses where student teams are geographically distributed promises several benefits. One main benefit is that in contrast to traditional classroom courses, students can experience the effects of distribution and the mechanisms for coping with distribution by themselves, therefore understanding their relevance for software development. They can thus learn to take more care of distribution challenges and risks when starting to develop software in industry. However, providing a sustainable environment for such project courses is difficult. A development environment is needed that can connect to different distributed teams and an ongoing routine to conduct such courses needs to be established. This article sketches a picture of the Software Factory, a platform that supports teaching distributed student projects and that has now been operational for more than three years. We describe the basic steps of conducting Software Factory projects, and portray experiences from past factory projects. In addition, we provide a short overview of related approaches and future activities.

Alexis Ocampo, Fabio Bella, Jürgen Münch

To remain viable and thrive, software organizations must rapidly adapt to frequent, and often rather far-ranging, changes to their operational context. These changes typically concern many factors, including the nature of the organization's marketplace in general, its customers' demands, and its business needs. In today's most highly dynamic contexts, such as web services development, other changes create additional, severe challenges. Most critical are changes to the technology in which a software product is written or which the software product has to control or use to provide its functionality. These product-support technology changes are frequently relatively 'small' and incremental. They are, therefore, often handled by relatively 'small,' incremental changes to the organization's software processes. However, the frequency of these changes is high, and their impact is elevated by time-to-market and requirements change demands. The net result is an extremely challenging need to create and manage a large number of customized process variants, collectively having more commonalities than differences, and incorporating experience-based, proven 'best practices'. This paper describes a tool-based approach to coping with product-support technology changes. The approach utilizes established capabilities such as descriptive process modeling and the creation of reference models. It incorporates a new, innovative, tool-based capability to analyze commonalities and differences among processes. The paper includes an example-based evaluation of the approach in the domain of Wireless Internet Services as well as a discussion of its potentially broader application.

Ansgar Lamersdorf, Jürgen Münch, Dieter Rombach

Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.

Ansgar Lamersdorf, Jürgen Münch, Alicia Fernández-del Viso Torre et al.

Risks and potential benefits of distributing software development projects globally depend to a large extent on how to allocate work to different development sites and regions. Existing methods in task allocation are likely to omit the relevance of considering a multitude of criteria and the impact of task distribution on risks and potential benefits. To assess risks stemming from specific work distributions and to exploit organization-specific experience, we have developed a customizable risk-driven model. It consists of two main steps: Suggesting a set of task allocation alternatives based on project- and site-specific characteristics and analyzing it with respect to possible project risks stemming from the work distribution. To evaluate the model, we conducted a series of semi-structured interviews in a multinational IT company. The results of the evaluation show that the suggestions of the model mostly comply with the retrospective views voiced by the involved experienced managers.

Fabian Fagerholm, Jürgen Münch

New ways of working such as globally distributed development or the integration of self-motivated external developers into software ecosystems will require a better and more comprehensive understanding of developers' feelings, perceptions, motivations and identification with their tasks in their respective project environments. User experience is a concept that captures how persons feel about products, systems and services. It evolved from disciplines such as interaction design and usability to a much richer scope that includes feelings, motivations, and satisfaction. Similarly, developer experience could be defined as a means for capturing how developers think and feel about their activities within their working environments, with the assumption that an improvement of the developer experience has positive impacts on characteristics such as sustained team and project performance. This article motivates the importance of developer experience, sketches related approaches from other domains, proposes a definition of developer experience that is derived from similar concepts in other domains, describes an ongoing empirical study to better understand developer experience, and finally gives an outlook on planned future research activities.

Frank Elberzhager, Jürgen Münch

Testing of software or software-based systems and services is considered as one of the most effort-consuming activities in the lifecycle. This applies especially to those domains where highly iterative development and continuous integration cannot be applied. Several approaches have been proposed to use measurement as a means to improve test effectiveness and efficiency. Most of them rely on using product data, historical data, or in-process data that is not related to quality assurance ac- tivities. Very few approaches use data from early quality assurance activities such as inspection data in order to focus testing activities and thereby reduce test effort. This article gives an overview of potential benefits of using data from early defect detection activities, potentially in addition to other data, in order to focus testing activities. In addition, the article sketches an integrated inspection and testing process and its evaluation in the context of two case studies. Taking the study limitations into account, the results show an overall reduction of testing effort by up to 34%, which mirrors an efficiency improvement of up to about 50% for testing.

Michael Kläs, Constanza Lampasona, Jürgen Münch

Measuring and evaluating software quality has become a fundamental task. Many models have been proposed to support stakeholders in dealing with software quality. However, in most cases, quality models do not fit perfectly for the target application context. Since approaches for efficiently adapting quality models are largely missing, many quality models in practice are built from scratch or reuse only high-level concepts of existing models. We present a tool-supported approach for the efficient adaptation of quality models. An initial empirical investigation indicates that the quality models obtained applying the proposed approach are considerably more consistently and appropriately adapted than those obtained following an ad-hoc approach. Further, we could observe that model adaptation is significantly more efficient (~factor 8) when using this approach.

Martin Kowalczyk, Henning Barthel, Jürgen Münch et al.

Explicitly linking software-related activities to an organisation's higher-level goals has been shown to be critical for organizational success. GQM+Strategies provides mechanisms for explicitly linking goals and strategies, based on goal-oriented strategic measurement systems. Deploying such strategic measurement systems in an organization is highly challenging. Experience has shown that a clear deployment strategy is needed for achieving sustainable success. In particular, an adequate deployment process as well as corresponding tool support can facilitate the deployment. This paper introduces the systematical GQM+Strategies deployment process and gives an overview of GQM+Strategies modelling and associated tool support. Additionally, it provides an overview of industrial applications and describes success factors and benefits for the usage of GQM+Strategies.