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P239 - Software Engineering & Management 2015

https://dl.gi.de/handle/20.500.12116/21184
Auflistung nach:

Auflistung P239 - Software Engineering & Management 2015 nach Autor:in "Apel, Sven"

1 - 3 von 3
  • Konferenzbeitrag
    Analysis strategies for software product lines: A classification and survey
    (Software-engineering and management 2015, 2015) Thüm, Thomas; Apel, Sven; Kästner, Christian; Schaefer, Ina; Saake, Gunter
    Software-product-line engineering enables the efficient development of similar software products. Instead of developing each product from scratch, products are generated from common artifacts. However, the product generation is a challenge for the analysis of correctness properties. Applying traditional analysis techniques, such as type checking and model checking, to each product involves redundant effort and is often not feasible due to the combinatorial explosion of products. Approaches to scale analysis techniques to product lines have been presented in unrelated research
  • Konferenzbeitrag
    Measuring program comprehension with functional magnetic resonance imaging
    (Software-engineering and management 2015, 2015) Siegmund, Janet; Apel, Sven; Kästner, Christian; Parnin, Chris; Bethmann, Anja; Saake, Gunter; Leich, Thomas; Brechmann, André
    We observed program comprehension with functional magnetic resonance imaging and found activation in brain areas related to working memory, divided attention, problem solving, and language processing.
  • Konferenzbeitrag
    Strategies for analyzing configurable systems
    (Software-engineering and management 2015, 2015) Rhein, Alexander Von; Apel, Sven
    The advent of variability management and generator technology enables users to derive individual system variants from a given configurable system just based on a selection of desired configuration options. To cope with the possibly huge configuration space, researchers have been developing analysis techniques that follow different strategies to incorporate (static) variability. We discuss different strategies (variability-aware analysis and sampling) and evaluate them in different settings (model checking, type checking, and liveness analysis). A key finding is that variability-aware analysis outperforms most sampling approaches with respect to analysis time while being able to make definite statements about all variants of a configurable system.