Investigating styles in variability modeling: Hierarchical vs. constrained styles

Context: A common way to represent product lines is with variability modeling. Yet, there are different ways to extract and organize relevant characteristics of variability. Comprehensibility of these models and the ease of creating models are important for the efficiency of any variability management approach. Objective: The goal of this paper is to investigate the comprehensibility of two common styles to organize variability into models - hierarchical and constrained - where the dependencies between choices are specified either through the hierarchy of the model or as cross-cutting constraints, respectively. Method: We conducted a controlled experiment with a sample of 90 participants who were students with prior training in modeling. Each participant was provided with two variability models specified in Common Variability Language (CVL) and was asked to answer questions requiring interpretation of provided models. The models included 9 to 20 nodes and 8 to 19 edges and used the main variability elements. After answering the questions, the participants were asked to create a model based on a textual description. Results: The results indicate that the hierarchical modeling style was easier to comprehend from a subjective point of view, but there was also a significant interaction effect with the degree of dependency in the models, that influenced objective comprehension. With respect to model creation, we found that the use of a constrained modeling style resulted in higher correctness of variability models. Conclusions: Prior exposure to modeling style and the degree of dependency among elements in the model determine what modeling style a participant chose when creating the model from natural language descriptions. Participants tended to choose a hierarchical style for modeling situations with high dependency and a constrained style for situations with low dependency. Furthermore, the degree of dependency also influences the comprehension of the variability model

Usability evaluation of variability modeling by means of Common Variability Language

Common Variability Language (CVL) is a recent proposal for OMG's upcoming Variability Modeling standard. CVL models variability in terms of Model Fragments. Usability is a widely-recognized quality criterion essential to warranty the successful use of tools that put these ideas in practice. Facing the need of evaluating the usability of CVL modeling tools, this paper presents a Usability Evaluation of CVL applied to a Modeling Tool for firmware code of Induction Hobs. This evaluation addresses the configuration, scoping and visualization facets. The evaluation involved the end users of the tool whom are engineers of our Induction Hob industrial partner. Effectiveness and efficiency results indicate that model configuration in terms of model fragment substitutions is intuitive enough but both scoping and visualization require improved tool support. Results also enabled us to identify a list of usability problems which may contribute to alleviate scoping and visualization issues in CVL.Echeverria, J.; Font, J.; Pastor López, O.; Cetina Englada, C. (2015). Usability evaluation of variability modeling by means of Common Variability Language. Complex Systems Informatics and Modeling Quarterly. (5):61-81. doi:10.7250/csimq.2015-5.05S6181

That Others May Learn: Three Views on Vicarious Learning in Organizations.

Vicarious learning, the process by which an individual learns from another’s experience, has long been recognized as a source of development and performance improvement in organizations, at both individual and collective levels. Yet existing perspectives on this critical learning process have been fairly limited, typically casting vicarious learning as a simple process of observation and imitation, enabled by formal organizational knowledge-transfer conduits. Largely absent from prior approaches is a consideration of the interpersonal dynamics underlying vicarious learning, leaving unexplored important questions related to 1) the actual behaviors unfolding when individuals interact to learn from one another’s experience, 2) how people coordinate efforts to enact and facilitate these vicarious learning interactions, and 3) the performance impact of different patterns of engagement in these interactions. In this dissertation, I advance a perspective on vicarious learning that views it as relationally co-created, emergently organized, and dyadically reciprocal, exploring the issues identified above in three distinct chapters. First, I present a theoretical model of what I term coactive vicarious learning, integrating theories of experiential learning and symbolic interactionism to articulate a co-construction process of vicarious learning, arising from individuals’ discussion and shared meaning-making. I unpack the antecedents and underlying behaviors of these discursive vicarious learning interactions, and theorize that they not only increase individuals’ knowledge, but also build individual and relational capacity for future learning. Second, I present a qualitative study of how these vicarious learning interactions manifest at work, inductively exploring the organizing processes used to facilitate vicarious learning in air medical transport teams. I advance a view of vicarious learning not as wholly determined by formal structures, but rather as an emergently organized phenomenon, enacted through interpersonal storytelling and facilitated by the coalescence of informal practices and formal structures. Third, I present a quantitative examination of different distributions of vicarious learning in work teams. Specifically, I examine what leads individuals to engage in reciprocal vicarious learning relationships (where each individual learns from the other, in contrast to the prevailing view of vicarious learning as one-way information transfer) and demonstrate that greater reciprocation of vicarious learning within a team enhances performance.PhDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113410/1/cgmyers_1.pd

Consolidation of Customized Product Copies into Software Product Lines

In software development, project constraints lead to customer-specific variants by copying and adapting the product. During this process, modifications are scattered all over the code. Although this is flexible and efficient in the short term, a Software Product Line (SPL) offers better results in the long term, regarding cost reduction, time-to-market, and quality attributes. This book presents a novel approach named SPLevo, which consolidates customized product copies into an SPL

Consolidation of Customized Product Copies into Software Product Lines

Copy-based customization is a widespread technique to serve individual customer needs with existing software solutions. To cope with long term disadvantages resulting from this practice, this dissertation developed an approach to support the consolidation of such copies into a Software Product Line with a future-compliant product base providing managed variability

Integrating location and logistics models

Economic geographers investigate facility location problems by applying procedures derived from the classical location theory. These conventional procedures focus on the analysis of the tradeoffs between facility and transportation decisions, and provide solutions to location problems that minimize distance-based cost components. The classical approach leads to basic shortcomings when applied to physical distribution problems. Furthermore, the GIS industry shows little attention to physical distribution problems and the manipulation of logistics data is difficult in out-of-box GIS products. Logistics decision-makers attempt to optimize their distribution systems by performing the tradeoff analysis among facility, inventory and transportation decisions. In addition, the minimization of distribution costs is generally performed analyzing time-sensitive costs only. This study aims to improve the contribution of geographic methodologies to distribution problems by analyzing inventory and transportation decisions, and then integrating time-sensitive cost components with distance-based system costs. An implemented formulation of the p-median problem is developed for this purpose in this study. A heuristic algorithm based on the swapping location criterion is used for the achievement of the solution of the physical distribution problem. Conventional swapping algorithms consider the best feasible solution by analyzing the spatial configuration of facilities. In this study, the implemented heuristic algorithm analyzes both savings obtained applying a change in the spatial configuration of the facilities and in the average speed of the transportation provider. This formulation is embedded as an extension available for the package ArcView 3.2 by ESRI. The logistics extension also includes a customized GUI for the input, editing, analysis, and output of logistics data. The major outcome from this study is that average speed of service and value of shipped item play a key role in the determination of the total distribution costs. The minimization of these costs, from a shipper\u27s perspective, suggests number and location of warehouses that optimize the physical distribution system

Consolidation of Customized Product Copies into Software Product Lines

In software development, project constraints lead to customer-specific variants by copying and adapting the product. During this process, modifications are scattered all over the code. Although this is flexible and efficient in the short term, a Software Product Line (SPL) offers better results in the long term, regarding cost reduction, time-to-market, and quality attributes. This book presents a novel approach named SPLevo, which consolidates customized product copies into an SPL

Lanthorn, vol. 40, no. 39, February 2, 2006

Lanthorn is Grand Valley State\u27s student newspaper, published from 1968 to the present