Evaluating a Textual Feature Modelling Language: Four Industrial Case Studies

Abstract. Feature models are commonly used in software product line engineer-ing as a means to document variability. Since their introduction, feature models have been extended and formalised in various ways. The majority of these ex-tensions are variants of the original tree-based graphical notation. But over time, textual dialects have also been proposed. The textual variability language (TVL) was proposed to combine the advantages of both graphical and textual notations. However, its benefits and limitations have not been empirically evaluated up to now. In this paper, we evaluate TVL with four cases from companies of differ-ent sizes and application domains. The study shows that practitioners can benefit from TVL. The participants appreciated the notation, the advantages of a textual language and considered the learning curve to be gentle. The study also reveals some limitations of the current version of TVL.

Promoting Reuse with Active Reuse Repository Systems

Abstract. Software component-based reuse is diÆcult for software de-velopers to adopt because rst they must know what components exist in a reuse repository and then they must know how to retrieve them easily. This paper describes the concept and implementation of active reuse repository systems that address the above two issues. Active reuse repository systems employ active information delivery mechanisms to deliver potentially reusable components that are relevant to the current development task. They can help software developers reuse components they did not even know existed. They can also greatly reduce the cost of component location because software developers need neither to specify reuse queries explicitly, nor to switch working contexts back and forth between development environments and reuse repository systems.

Cognitive Tutors as Research Platforms: Extending an Established Tutoring System for Collaborative and Metacognitive Experimentation (2006

Abstract. Cognitive tutors have been shown to increase student learning in long-term classroom studies but would become even more effective if they provided collaborative support and metacognitive tutoring. Reconceptualizing an established tutoring system as a research platform to test different collaborative and metacognitive interventions would lead to gains in learning research. In this paper, we define a component-based architecture for such a platform, drawing from previous theoretical frameworks for tutoring systems. We then describe two practical implementation challenges not typically addressed by these frameworks. We detail our efforts to extend a cognitive tutor and evaluate our progress in terms of flexibility, control, and practicality.

An Engineer-To-Order Mass Customization Development Framework

Part 1: Knowledge-Based Performance ImprovementInternational audienceDevelopers of automated manufacturing systems are often categorised as Engineer-To-Order companies, relying on the ability to offer solutions that are tailored to the individual consumer. Managing product variety and enabling reusability between solutions becomes key concepts towards increasing competitiveness and revenue, in which Engineer-To-Order companies may benefit from adopting Mass Customization concepts. As automated manufacturing systems tends to be software intensive, it become equally important to enable reusability for physical components and for software related artefacts. In parallel to Mass Customization, Software Product Line Engineering has emerged as a way for software developers to manage variability and reusability. This paper seeks to combine the concepts of Mass Customization and Software Product Line Engineering, by introducing a development framework applicable for Engineer-To-Order companies offering automated manufacturing systems