Konsistente Feature Modell gesteuerte Softwareproduktlinien Evolution

SPLs are an approach to manage families of closely related software systems in terms of configurable functionality. A feature model captures common and variable functionalities of an SPL on a conceptual level in terms of features. Reusable artifacts, such as code, documentation, or tests are related to features using a feature-artifact mapping. A product of an SPL can be derived by selecting features in a configuration. Over the course of time, SPLs and their artifacts are subject to change. As SPLs are particularly complex, their evolution is a challenging task. Consequently, SPL evolution must be thoroughly planned well in advance. However, plans typically do not turn out as expected and, thus, replanning is required. Feature models lean themselves for driving SPL evolution. However, replanning of feature-model evolution can lead to inconsistencies and feature-model anomalies may be introduced during evolution. Along with feature-model evolution, other SPL artifacts, especially configurations, need to consistently evolve. The work of this thesis provides remedy to the aforementioned challenges by presenting an approach for consistent evolution of SPLs. The main contributions of this thesis can be distinguished into three key areas: planning and replanning feature-model evolution, analyzing feature-model evolution, and consistent SPL artifact evolution. As a starting point for SPL evolution, we introduce Temporal Feature Models (TFMs) that allow capturing the entire evolution timeline of a feature model in one artifact, i.e., past history, present changes, and planned evolution steps. We provide an execution semantics of feature-model evolution operations that guarantees consistency of feature-model evolution timelines. To keep feature models free from anomalies, we introduce analyses to detect anomalies in feature-model evolution timelines and explain these anomalies in terms of their causing evolution operations. To enable consistent SPL artifact evolution, we generalize the concept of modeling evolution timelines in TFMs to be applicable for any modeling language. Moreover, we provide a methodology that enables involved engineers to define and use guidance for configuration evolution.Softwareproduktlinien (SPLs) ermöglichen es, konfigurierbare Funktionalität von eng verwandten Softwaresystemen zu verwalten. In einem Feature Modell werden gemeinsame und variable Funktionalitäten einer SPL auf Basis abstrakter Features modelliert. Wiederverwendbare Artefakte werden in einem Feature-Artefakt Mapping Features zugeordnet. Ein Produkt einer SPL kann abgeleitet werden, indem Features in einer Konfiguration ausgewählt werden. Im Laufe der Zeit müssen sich SPLs und deren Artefakte verändern. Da SPLs ganze Softwarefamilien modellieren, ist deren Evolution eine besonders herausfordernde Aufgabe, die gründlich im Voraus geplant werden muss. Feature Modelle eignen sich besonders als Planungsmittel einer SPL. Umplanung von Feature Modell Evolution kann jedoch zu Inkonsistenzen führen und Feature Modell Anomalien können im Zuge der Evolution eingeführt werden. Im Anschluss an die Feature Modell Evolution muss die Evolution anderer SPL Artefakte, insbesondere Konfigurationen, konsistent modelliert werden. In dieser Arbeit wird ein Ansatz zur konsistenten Evolution von SPLs vorgestellt, der die zuvor genannten Herausforderungen adressiert. Die Beiträge dieser Arbeit lassen sich in drei Kernbereiche aufteilen: Planung und Umplanung von Feature Modell Evolution, Analyse von Feature Modell Evolution und konsistente Evolution von SPL Artefakten. Temporal Feature Models (TFMs) werden als Startpunkt für SPL Evolution eingeführt. In einem TFM wird die gesamte Evolutionszeitlinie eines Feature Modells in einem Artefakt abgebildet, was sowohl vergangene Änderungen, den aktuellen Zustand, als auch geplante Änderungen beinhaltet. Auf Basis einer Ausführungssemantik wird die Konsistenz von Feature Modell Evolutionszeitlinien sichergestellt. Um Feature Modelle frei von Anomalien zu halten, werden Analysen eingeführt, welche die gesamte Evolutionszeitlinie eines Feature Modells auf Anomalien untersucht und diese mit verursachenden Evolutionsoperationen erklärt. Das Konzept zur Modellierung von Feature Modell Evolutionszeitlinien aus TFMs wird verallgemeinert, um die gesamte Evolution von Modellen beliebiger Modellierungssprachen spezifizieren zu können. Des Weiteren wird eine Methodik vorgestellt, die beteiligten Ingenieuren eine geführte Evolution von Konfigurationen ermöglicht

Consistency-Preserving Evolution Planning on Feature Models

A software product line (SPL) enables large-scale reuse in a family of related software systems through configurable features. SPLs represent a long-term investment so that their ongoing evolution becomes paramount and requires careful planning. While existing approaches enable to create an evolution plan for an SPL on feature-model (FM) level, they assume the plan to be rigid and do not support retroactive changes. In this paper, we present a method that enables to create and retroactively adapt an FM evolution plan while preventing undesired impacts on its structural and logical consistency. This method is founded in structural operational semantics and linear temporal logic. We implement our method using rewriting logic, integrate it within an FM tool suite and perform an evaluation using a collection of existing FM evolution scenarios

Improving radiometry of imaging spectrometers by using programmable spectral regions of interest

Programmable imaging spectrometers can be adjusted to fit specific application requirements that differ from the instrument initial spectral design goals. Sensor spectral characteristics and its signal-to-noise ratio (SNR) can be changed by applying customized online binning patterns. We present a software utility that generates application driven spectral binning patterns by using an SNR dependent sensor model. The utility, named BinGO (BInning patterN Generator and Optimiser), is used to produce predefined binning patterns that either (a) allow an existing imaging spectrometer to optimize its spectral characteristics for a specific application, (b) allow an existing imaging spectrometer to spectral and/or spatially emulate another instrument, or (c) design new multispectral or imaging spectrometer missions (i.e.�spaceborne, airborne, terrestrial). We present a variety of BinGO case studies, including the simulation of airborne (APEX) [Itten, K.I. et�al., 2008. APEX -- The hyperspectral ESA Airborne Prism Experiment. Sensors 8(1), 1-25], spaceborne (SENTINEL III) [Nieke, J., Frerick, J.,�Stroede, J., Mavrocordatos, C., Berruti, B., 2008. Status of the optical payload and processor development of ESA's Sentinel 3 mission. In: Proceedings of the Geoscience and Remote Sensing Symposium IGARSS 2008, pp. 427-430], as well as scientific and performance optimized approaches. We conclude that the presented approach can successfully be used to increase the efficiency of spectral information retrieval by using imaging spectroscopy data and to simulate various missions and requirements, finally supporting proper trade-off decisions to be made between performance optimization and scientific requirements. In addition, if specific sensor parameters are known, BinGO can also model other imaging spectrometers