004 Datenverarbeitung; Informatik
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Nowadays, model-driven engineering (MDE) promises to ease software development by decreasing the inherent complexity of classical software development. In order to deliver on this promise, MDE increases the level of abstraction and automation, through a consideration of domain-specific models (DSMs) and model operations (e.g. model transformations or code generations). DSMs conform to domain-specific modeling languages (DSMLs), which increase the level of abstraction, and model operations are first-class entities of software development because they increase the level of automation. Nevertheless, MDE has to deal with at least two new dimensions of complexity, which are basically caused by the increased linguistic and technological heterogeneity. The first dimension of complexity is setting up an MDE environment, an activity comprised of the implementation or selection of DSMLs and model operations. Setting up an MDE environment is both time-consuming and error-prone because of the implementation or adaptation of model operations. The second dimension of complexity is concerned with applying MDE for actual software development. Applying MDE is challenging because a collection of DSMs, which conform to potentially heterogeneous DSMLs, are required to completely specify a complex software system. A single DSML can only be used to describe a specific aspect of a software system at a certain level of abstraction and from a certain perspective. Additionally, DSMs are usually not independent but instead have inherent interdependencies, reflecting (partial) similar aspects of a software system at different levels of abstraction or from different perspectives. A subset of these dependencies are applications of various model operations, which are necessary to keep the degree of automation high. This becomes even worse when addressing the first dimension of complexity. Due to continuous changes, all kinds of dependencies, including the applications of model operations, must also be managed continuously. This comprises maintaining the existence of these dependencies and the appropriate (re-)application of model operations. The contribution of this thesis is an approach that combines traceability and model management to address the aforementioned challenges of configuring and applying MDE for software development. The approach is considered as a traceability approach because it supports capturing and automatically maintaining dependencies between DSMs. The approach is considered as a model management approach because it supports managing the automated (re-)application of heterogeneous model operations. In addition, the approach is considered as a comprehensive model management. Since the decomposition of model operations is encouraged to alleviate the first dimension of complexity, the subsequent composition of model operations is required to counteract their fragmentation. A significant portion of this thesis concerns itself with providing a method for the specification of decoupled yet still highly cohesive complex compositions of heterogeneous model operations. The approach supports two different kinds of compositions - data-flow compositions and context compositions. Data-flow composition is used to define a network of heterogeneous model operations coupled by sharing input and output DSMs alone. Context composition is related to a concept used in declarative model transformation approaches to compose individual model transformation rules (units) at any level of detail. In this thesis, context composition provides the ability to use a collection of dependencies as context for the composition of other dependencies, including model operations. In addition, the actual implementation of model operations, which are going to be composed, do not need to implement any composition concerns. The approach is realized by means of a formalism called an executable and dynamic hierarchical megamodel, based on the original idea of megamodels. This formalism supports specifying compositions of dependencies (traceability and model operations). On top of this formalism, traceability is realized by means of a localization concept, and model management by means of an execution concept.
The field of machine learning studies algorithms that infer predictive models from data. Predictive models are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a predictive model, it is crucial to know the model’s approximate performance. To evaluate performance, a set of labeled test instances is required that is drawn from the distribution the model will be exposed to at application time. In many practical scenarios, unlabeled test instances are readily available, but the process of labeling them can be a time- and cost-intensive task and may involve a human expert. This thesis addresses the problem of evaluating a given predictive model accurately with minimal labeling effort. We study an active model evaluation process that selects certain instances of the data according to an instrumental sampling distribution and queries their labels. We derive sampling distributions that minimize estimation error with respect to different performance measures such as error rate, mean squared error, and F-measures. An analysis of the distribution that governs the estimator leads to confidence intervals, which indicate how precise the error estimation is. Labeling costs may vary across different instances depending on certain characteristics of the data. For instance, documents differ in their length, comprehensibility, and technical requirements; these attributes affect the time a human labeler needs to judge relevance or to assign topics. To address this, the sampling distribution is extended to incorporate instance-specific costs. We empirically study conditions under which the active evaluation processes are more accurate than a standard estimate that draws equally many instances from the test distribution. We also address the problem of comparing the risks of two predictive models. The standard approach would be to draw instances according to the test distribution, label the selected instances, and apply statistical tests to identify significant differences. Drawing instances according to an instrumental distribution affects the power of a statistical test. We derive a sampling procedure that maximizes test power when used to select instances, and thereby minimizes the likelihood of choosing the inferior model. Furthermore, we investigate the task of comparing several alternative models; the objective of an evaluation could be to rank the models according to the risk that they incur or to identify the model with lowest risk. An experimental study shows that the active procedure leads to higher test power than the standard test in many application domains. Finally, we study the problem of evaluating the performance of ranking functions, which are used for example for web search. In practice, ranking performance is estimated by applying a given ranking model to a representative set of test queries and manually assessing the relevance of all retrieved items for each query. We apply the concepts of active evaluation and active comparison to ranking functions and derive optimal sampling distributions for the commonly used performance measures Discounted Cumulative Gain and Expected Reciprocal Rank. Experiments on web search engine data illustrate significant reductions in labeling costs.
Structuring process models
(2012)
One can fairly adopt the ideas of Donald E. Knuth to conclude that process modeling is both a science and an art. Process modeling does have an aesthetic sense. Similar to composing an opera or writing a novel, process modeling is carried out by humans who undergo creative practices when engineering a process model. Therefore, the very same process can be modeled in a myriad number of ways. Once modeled, processes can be analyzed by employing scientific methods. Usually, process models are formalized as directed graphs, with nodes representing tasks and decisions, and directed arcs describing temporal constraints between the nodes. Common process definition languages, such as Business Process Model and Notation (BPMN) and Event-driven Process Chain (EPC) allow process analysts to define models with arbitrary complex topologies. The absence of structural constraints supports creativity and productivity, as there is no need to force ideas into a limited amount of available structural patterns. Nevertheless, it is often preferable that models follow certain structural rules. A well-known structural property of process models is (well-)structuredness. A process model is (well-)structured if and only if every node with multiple outgoing arcs (a split) has a corresponding node with multiple incoming arcs (a join), and vice versa, such that the set of nodes between the split and the join induces a single-entry-single-exit (SESE) region; otherwise the process model is unstructured. The motivations for well-structured process models are manifold: (i) Well-structured process models are easier to layout for visual representation as their formalizations are planar graphs. (ii) Well-structured process models are easier to comprehend by humans. (iii) Well-structured process models tend to have fewer errors than unstructured ones and it is less probable to introduce new errors when modifying a well-structured process model. (iv) Well-structured process models are better suited for analysis with many existing formal techniques applicable only for well-structured process models. (v) Well-structured process models are better suited for efficient execution and optimization, e.g., when discovering independent regions of a process model that can be executed concurrently. Consequently, there are process modeling languages that encourage well-structured modeling, e.g., Business Process Execution Language (BPEL) and ADEPT. However, the well-structured process modeling implies some limitations: (i) There exist processes that cannot be formalized as well-structured process models. (ii) There exist processes that when formalized as well-structured process models require a considerable duplication of modeling constructs. Rather than expecting well-structured modeling from start, we advocate for the absence of structural constraints when modeling. Afterwards, automated methods can suggest, upon request and whenever possible, alternative formalizations that are "better" structured, preferably well-structured. In this thesis, we study the problem of automatically transforming process models into equivalent well-structured models. The developed transformations are performed under a strong notion of behavioral equivalence which preserves concurrency. The findings are implemented in a tool, which is publicly available.
In-Memory Data Management
(2012)
Nach 50 Jahren erfolgreicher Entwicklunghat die Business-IT einen neuenWendepunkt erreicht. Hier zeigen die Autoren erstmalig, wieIn-Memory Computing dieUnternehmensprozesse künftig verändern wird. Bisher wurden Unternehmensdaten aus Performance-Gründen auf verschiedene Datenbanken verteilt: Analytische Datenresidieren in Data Warehouses und werden regelmäßig mithilfe transaktionaler Systeme synchronisiert. Diese Aufspaltung macht flexibles Echtzeit-Reporting aktueller Daten unmöglich. Doch dank leistungsfähigerMulti-Core-CPUs, großer Hauptspeicher, Cloud Computing und immerbesserer mobiler Endgeräte lassen die Unternehmen dieses restriktive Modell zunehmend hinter sich. Die Autoren stellen Techniken vor, die eine analytische und transaktionale Verarbeitung in Echtzeit erlauben und so dem Geschäftsleben neue Wege bahnen.
ASP modulo CSP
(2012)
We present the hybrid ASP solver clingcon, combining the simple modeling language and the high performance Boolean solving capacities of Answer Set Programming (ASP) with techniques for using non-Boolean constraints from the area of Constraint Programming (CP). The new clingcon system features an extended syntax supporting global constraints and optimize statements for constraint variables. The major technical innovation improves the interaction between ASP and CP solver through elaborated learning techniques based on irreducible inconsistent sets. A broad empirical evaluation shows that these techniques yield a performance improvement of an order of magnitude.
The constantly growing capacity of reconfigurable devices allows simultaneous execution of complex applications on those devices. The mere diversity of applications deems it impossible to design an interconnection network matching the requirements of every possible application perfectly, leading to suboptimal performance in many cases. However, the architecture of the interconnection network is not the only aspect affecting performance of communication. The resource manager places applications on the device and therefore influences latency between communicating partners and overall network load. Communication protocols affect performance by introducing data and processing overhead putting higher load on the network and increasing resource demand. Approaching communication holistically not only considers the architecture of the interconnect, but communication-aware resource management, communication protocols and resource usage just as well. Incorporation of different parts of a reconfigurable system during design- and runtime and optimizing them with respect to communication demand results in more resource efficient communication. Extensive evaluation shows enhanced performance and flexibility, if communication on reconfigurable devices is regarded in a holistic fashion.
F2C2
(2012)
Background: Flux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.
Results: We present a new method F2C2 for FCA, which is orders of magnitude faster than previous approaches. As a consequence, FCA of genome-scale metabolic networks can now be performed in a routine manner.
Conclusions: We propose F2C2 as a fast tool for the computation of flux coupling in genome-scale metabolic networks. F2C2 is freely available for non-commercial use at https://sourceforge.net/projects/f2c2/files/.
One of the key challenges in service-oriented systems engineering is the prediction and assurance of non-functional properties, such as the reliability and the availability of composite interorganizational services. Such systems are often characterized by a variety of inherent uncertainties, which must be addressed in the modeling and the analysis approach. The different relevant types of uncertainties can be categorized into (1) epistemic uncertainties due to incomplete knowledge and (2) randomization as explicitly used in protocols or as a result of physical processes. In this report, we study a probabilistic timed model which allows us to quantitatively reason about nonfunctional properties for a restricted class of service-oriented real-time systems using formal methods. To properly motivate the choice for the used approach, we devise a requirements catalogue for the modeling and the analysis of probabilistic real-time systems with uncertainties and provide evidence that the uncertainties of type (1) and (2) in the targeted systems have a major impact on the used models and require distinguished analysis approaches. The formal model we use in this report are Interval Probabilistic Timed Automata (IPTA). Based on the outlined requirements, we give evidence that this model provides both enough expressiveness for a realistic and modular specifiation of the targeted class of systems, and suitable formal methods for analyzing properties, such as safety and reliability properties in a quantitative manner. As technical means for the quantitative analysis, we build on probabilistic model checking, specifically on probabilistic time-bounded reachability analysis and computation of expected reachability rewards and costs. To carry out the quantitative analysis using probabilistic model checking, we developed an extension of the Prism tool for modeling and analyzing IPTA. Our extension of Prism introduces a means for modeling probabilistic uncertainty in the form of probability intervals, as required for IPTA. For analyzing IPTA, our Prism extension moreover adds support for probabilistic reachability checking and computation of expected rewards and costs. We discuss the performance of our extended version of Prism and compare the interval-based IPTA approach to models with fixed probabilities.
Fußverkehr findet im gesamten öffentlichen Raum statt und ermöglicht die lückenlose Verbindung von Tür zu Tür. Jeder Mensch steht vor Beginn einer Fortbewegung vor den Fragen „Wo bin ich?“, „Wo liegt mein Ziel?“ und „Wie komme ich dahin?“. Ein Großteil der auf dem Markt befindlichen Navigationssysteme für Fußgänger stellen reduzierte Varianten aus Fahrzeugen dar und basieren auf 2D- Kartendarstellungen oder bilden die Realität als dreidimensionales Modell ab. Navigationsprobleme entstehen dann, wenn es dem Nutzer nicht gelingt, die Information aus der Anweisung auf die Wirklichkeit zu beziehen und umzusetzen. Ein möglicher Grund dafür liegt in der Visualisierung der Navigationsanweisung. Die räumliche Wahrnehmung des Menschen erfolgt ausgehend von einem bestimmten Betrachtungsstandpunkt und bringt die Lage von Objekten und deren Beziehung zueinander zum Ausdruck. Der Einsatz von Augmented Reality (erweiterte Realität) entspricht dem Erscheinungsbild der menschlichen Wahrnehmung und ist für Menschen eine natürliche und zugleich vertraute Ansichtsform. Im Unterschied zu kartographischer Visualisierung wird die Umwelt mittels Augmented Reality nicht modelliert, sondern realitätsgetreu abgebildet und ergänzt. Das Ziel dieser Arbeit ist ein Navigationsverfahren, das der natürlichen Fort-bewegung und Sichtweise von Fußgängern gerecht wird. Das Konzept basiert auf dem Einsatz einer Kombination aus Realität und virtueller Realität zu einer erweiterten Ansicht. Da keine Darstellungsform als die Route selbst besser geeignet ist, um einen Routenverlauf zu beschreiben, wird die Realität durch eine virtuelle Route erweitert. Die perspektivische Anpassung der Routendarstellung erfordert die sensorische Erfassung der Position und Lage des Betrachtungsstandpunktes. Das der Navigation zu Grunde liegende Datenmodell bleibt dem Betrachter dabei verborgen und ist nur in Form der erweiterten Realität sichtbar. Der im Rahmen dieser Arbeit entwickelte Prototyp trägt die Bezeichnung RealityView. Die Basis bildet ein freies und quelloffenes Navigationssystem, das für die Fußgängernavigation modular erweitert wurde. Das Ergebnis ist ein smartphonebasierter Navigationsprototyp, in dem die Ansichtsform einer zweidimensionalen Bildschirmkarte im Grundriss und die Darstellung einer erweiterten Realität im Aufriss kombiniert werden. Die Evaluation des Prototyps bestätigt die Hypothese, dass der Einsatz von Augmented Reality für die Navigation von Fußgängern möglich ist und von der Nutzergruppe akzeptiert wird. Darüber hinaus bescheinigen Wissenschaftler im Rahmen von Experten-interviews den konzeptionellen Ansatz und die prototypische Umsetzung des RealityView. Die Auswertung einer Eye-Tracking-Pilotstudie erbrachte den Nachweis, dass Fußgänger die Navigationsanweisung auf markante Objekte der Umwelt beziehen, deren Auswahl durch den Einsatz von Augmented Reality begünstigt wird.
MDE techniques are more and more used in praxis. However, there is currently a lack of detailed reports about how different MDE techniques are integrated into the development and combined with each other. To learn more about such MDE settings, we performed a descriptive and exploratory field study with SAP, which is a worldwide operating company with around 50.000 employees and builds enterprise software applications. This technical report describes insights we got during this study. For example, we identified that MDE settings are subject to evolution. Finally, this report outlines directions for future research to provide practical advises for the application of MDE settings.