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Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
The emergence of agile methods and practices has not only changed the development processes but might also have affected how companies conduct software process improvement (SPI). Through a set of complementary studies, we aim to understand how SPI has changed in times of agile software development. Specifically, we aim (1) to identify and characterize the set of publications that connect elements of agility to SPI, (2) to explore to which extent agile methods/practices have been used in the context of SPI, and (3) to understand whether the topics addressed in the literature are relevant and useful for industry professionals. To study these questions, we conducted an in-depth analysis of the literature identified in a previous mapping study, an interview study, and an analysis of the responses given by industry professionals to SPI-related questions stemming from an independently conducted survey study.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.
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. Based on 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.
The need for creating digitally enhanced products, services, and experiences as well as the emergence of new or modified business models has a significant impact on the automotive domain. Innovative solutions and new topics such as Smart Mobility or Connectivity require current automotive development processes to undergo major changes. They need to be redesigned in a way that it is possible to learn and adapt continuously at a fast pace. Agile methods are promising approaches to address these new challenges. However, agile methods are not tailored to the specific characteristics of the automotive domain such as software product line (SPLs) development. Although, there have been efforts to apply agile methods in the automotive domain, widespread adoptions have not yet taken place.
Software engineering education is supposed to provide students with industry-relevant knowledge and skills. Educators must address issues beyond exercises and theories that can be directly rehearsed in small settings. A way to experience such effects and to increase the relevance of software engineering education is to apply empirical studies in teaching. In our article, we show how different types of empirical studies can be used for educational purposes in software engineering. We give examples illustrating how to utilize empirical studies, discuss challenges, and derive an initial guideline that supports teachers to include empirical studies in software engineering courses.
Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured methods and flexible agile practices. Yet, the number of methods and practices is large and the actual process composition is often carried out in an ad-hoc manner. This paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what contextual factors influence the use and combination of hybrid software development approaches.
Due to rapidly changing technologies and business contexts, many products and services are developed under high uncertainties. It is often impossible to predict customer behaviors and outcomes upfront. Therefore, product and service developers must continuously find out what customers want, requiring a more experimental mode of management and appropriate support for continuously conducting experiments. We have analytically derived an initial model for continuous experimentation from prior work and matched it against empirical case study findings from two startup companies. We examined the preconditions for setting up an experimentation system for continuous customer experiments. The resulting RIGHT model for Continuous Experimentation (Rapid Iterative value creation Gained through High-frequency Testing) illustrates the building blocks required for such a system and the necessary infrastructure. The major findings are that a suitable experimentation system requires the ability to design, manage, and conduct experiments, create so-called minimum viable products or features, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper, rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and integration of experiment results in the product development cycle, software development process, and business strategy. This summary refers to the article The RIGHT Model for Continuous Experimentation, published in the Journal of Systems and Software [Fa17].
The ability to develop and deploy high-quality software at a high speed gets increasing relevance for the comptetitiveness of car manufacturers. Agile practices have shown benefits such as faster time to market in several application domains. Therefore, it seems to be promising to carefully adopt agile practices also in the automotive domain. This article presents findings from an interview-based qualitative survey. It aims at understanding perceived forces that support agile adoption. Particularly, it focuses on embedded software development for electronic control units in the automotive domain.
Software process improvement (SPI) is around for decades: frameworks are proposed, success factors are studied, and experiences have been reported. However, the sheer mass of concepts, approaches, and standards published over the years overwhelms practitioners as well as researchers. What is out there? Are there new emerging approaches? What are open issues? Still, we struggle to answer the question for what is the current state of SPI and related research? We present initial results from a systematic mapping study to shed light on the field of SPI and to draw conclusions for future research directions. An analysis of 635 publications draws a big picture of SPI-related research of the past 25 years. Our study shows a high number of solution proposals, experience reports, and secondary studies, but only few theories. In particular, standard SPI models are analyzed and evaluated for applicability, especially from the perspective of SPI in small-to-medium-sized companies, which leads to new specialized frameworks. Furthermore, we find a growing interest in success factors to aid companies in conducting SPI.
This summary refers to the paper Software process improvement : where is the evidence? [Ku15].
This paper was published as full research paper in the ICSSP’2015 proceedings.