Collaborative traceability management: a multiple case study from the perspectives of organization, process, and culture

Traceability is crucial for many activities in software and systems engineering including monitoring the development progress, and proving compliance with standards. In practice, the use and maintenance of trace links are challenging as artifacts undergo constant change, and development takes place in distributed scenarios with multiple collaborating stakeholders. Although traceability management in general has been addressed in previous studies, there is a need for empirical insights into the collaborative aspects of traceability management and how it is situated in existing development contexts. The study reported in this paper aims to close this gap by investigating the relation of collaboration and traceability management, based on an understanding of characteristics of the development effort. In our multiple exploratory case study, we conducted semi-structured interviews with 24 individuals from 15 industrial projects. We explored which challenges arise, how traceability management can support collaboration, how collaboration relates to traceability management approaches, and what characteristics of the development effort influence traceability management and collaboration. We found that practitioners struggle with the following challenges: (1) collaboration across team and tool boundaries, (2) conveying the benefits of traceability, and (3) traceability maintenance. If these challenges are addressed, we found that traceability can facilitate communication and knowledge management in distributed contexts. Moreover, there exist multiple approaches to traceability management with diverse collaboration approaches, i.e., requirements-centered, developer-driven, and mixed approaches. While traceability can be leveraged in software development with both agile and plan-driven paradigms, a certain level of rigor is needed to realize its benefits and overcome challenges. To support practitioners, we provide principles of collaborative traceability management. The main contribution of this paper is empirical evidence of how culture, processes, and organization impact traceability management and collaboration, and principles to support practitioners with collaborative traceability management. We show that collaboration and traceability management have the potential to be mutually beneficial—when investing in one, also the other one is positively affected

Tackling Combinatorial Explosion: A Study of Industrial Needs and Practices for Analyzing Highly Configurable Systems

Highly configurable systems are complex pieces of software. To tackle this complexity, hundreds of dedicated analysis techniques have been conceived, many of which able to analyze system properties for all possible system configurations, as opposed to traditional, single-system analyses. Unfortunately, it is largely unknown whether these techniques are adopted in practice, whether they address actual needs, or what strategies practitioners actually apply to analyze highly configurable systems. We present a study of analysis practices and needs in industry. It relied on a survey with 27 practitioners engineering highly configurable systems and follow-up interviews with 15 of them, covering 18 different companies from eight countries. We confirm that typical properties considered in the literature (e.g., reliability) are relevant, that consistency between variability models and artifacts is critical, but that the majority of analyses for specifications of configuration options (a.k.a., variability model analysis) is not perceived as needed. We identified rather pragmatic analysis strategies, including practices to avoid the need for analysis. For instance, testing with experience-based sampling is the most commonly applied strategy, while systematic sampling is rarely applicable. We discuss analyses that are missing and synthesize our insights into suggestions for future research

How do students experience and judge software comprehension techniques?

Today, there is a wide range of techniques to support softwarecomprehension. However, we do not fully understand yet whattechniques really help novices, to comprehend a software system.In this paper, we present a master level project course on softwareevolution, which has a large focus on software comprehension. Wecollected data about student\u27s experience with diverse comprehension techniques during focus group discussions over the course oftwo years. Our results indicate that systematic code reading canbe supported by additional techniques to guiding reading efforts.Most techniques are considered valuable for gaining an overviewand some techniques are judged to be helpful only in later stagesof software comprehension efforts

The MobSTr Dataset - An Exemplar for Traceability and Model-based Safety Assessment

The MobSTr dataset contains a number of artifacts for an autonomous driver assistance system, ranging from textual requirements to models for system design and models relevant to safety assurance. The artifacts provided are connected with traceability links created and managed with Eclipse Capra, an open source traceability management tool. The dataset builds upon a custom traceability information model that provides type safety and semantics for the trace links.MobSTr is intended for researchers that work on software and systems traceability as well as on model-based safety assurance. It is already being used in a number of studies, including research on trace link consistency, change impact analysis, and automated analysis of safety and timing requirements