@inproceedings{245, abstract = {{In cloud computing, software architects develop systems for virtually unlimited resources that cloud providers account on a pay-per-use basis. Elasticity management systems provision these resources autonomously to deal with changing workload. Such changing workloads call for new objective metrics allowing architects to quantify quality properties like scalability, elasticity, and efficiency, e.g., for requirements/SLO engineering and software design analysis. In literature, initial metrics for these properties have been proposed. However, current metrics lack a systematic derivation and assume knowledge of implementation details like resource handling. Therefore, these metrics are inapplicable where such knowledge is unavailable.To cope with these lacks, this short paper derives metrics for scalability, elasticity, and efficiency properties of cloud computing systems using the goal question metric (GQM) method. Our derivation uses a running example that outlines characteristics of cloud computing systems. Eventually, this example allows us to set up a systematic GQM plan and to derive an initial set of six new metrics. We particularly show that our GQM plan allows to classify existing metrics.}}, author = {{Becker, Matthias and Lehrig, Sebastian and Becker, Steffen}}, booktitle = {{Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering}}, pages = {{169----174}}, title = {{{Systematically Deriving Quality Metrics for Cloud Computing Systems}}}, doi = {{10.1145/2668930.2688043}}, year = {{2015}}, } @phdthesis{246, author = {{Besova, Galina}}, publisher = {{Universität Paderborn}}, title = {{{Systematic Development and Re-Use of Model Tranformations}}}, year = {{2015}}, } @article{260, abstract = {{During the last decade, researchers have proposed a number of model transformations enabling performance predictions. These transformations map performance-annotated software architecture models into stochastic models solved by analytical means or by simulation. However, so far, a detailed quantitative evaluation of the accuracy and efficiency of different transformations is missing, making it hard to select an adequate transformation for a given context. This paper provides an in-depth comparison and quantitative evaluation of representative model transformations to, e.g., Queueing Petri Nets and Layered Queueing Networks. The semantic gaps between typical source model abstractions and the different analysis techniques are revealed. The accuracy and efficiency of each transformation are evaluated by considering four case studies representing systems of different size and complexity. The presented results and insights gained from the evaluation help software architects and performance engineers to select the appropriate transformation for a given context, thus significantly improving the usability of model transformations for performance prediction.}}, author = {{Brosig, Fabian and Meier, Philipp and Becker, Steffen and Koziolek, Anne and Koziolek, Heiko and Kounev, Samuel}}, journal = {{Transactions on Software Engineering}}, number = {{2}}, pages = {{157----175}}, publisher = {{IEEE}}, title = {{{Quantitative Evaluation of Model-Driven Performance Analysis and Simulation of Component-based Architectures}}}, doi = {{10.1109/TSE.2014.2362755}}, year = {{2015}}, } @inproceedings{262, abstract = {{Programs from Proofs" is a generic method which generates new programs out of correctness proofs of given programs. The technique ensures that the new and given program are behaviorally equivalent and that the new program is easily verifiable, thus serving as an alternative to proof-carrying code concepts. So far, this generic method has one instantiation that verifies type-state properties of programs. In this paper, we present a whole range of new instantiations, all based on data ow analyses. More precisely, we show how an imprecise but fast data ow analysis can be enhanced with a predicate analysis as to yield a precise but expensive analysis. Out of the safety proofs of this analysis, we generate new programs, again behaviorally equivalent to the given ones, which are easily verifiable" in the sense that now the data ow analysis alone can yield precise results. An experimental evaluation practically supports our claim of easy verification.}}, author = {{Jakobs, Marie-Christine and Wehrheim, Heike}}, booktitle = {{Proceedings of the 30th Annual ACM Symposium on Applied Computing}}, pages = {{1729--1736}}, title = {{{Programs from Proofs of Predicated Dataflow Analyses}}}, doi = {{10.1145/2695664.2695690}}, year = {{2015}}, } @inproceedings{269, abstract = {{Proof-carrying hardware is an approach that has recently been proposed for the efficient verification of reconfigurable modules. We present an application of proof-carrying hardware to guarantee the correct functionality of dynamically reconfigured image processing modules. Our prototype comprises a reconfigurable-system-on-chip with an embedded virtual FPGA fabric. This setup allows us to leverage open source FPGA synthesis and backend tools to produce FPGA configuration bitstreams with an open format and, thus, to demonstrate and experimentally evaluate proof-carrying hardware at the bitstream level.}}, author = {{Wiersema, Tobias and Wu, Sen and Platzner, Marco}}, booktitle = {{Proceedings of the International Symposium in Reconfigurable Computing (ARC)}}, pages = {{365----372}}, title = {{{On-The-Fly Verification of Reconfigurable Image Processing Modules based on a Proof-Carrying Hardware Approach}}}, doi = {{10.1007/978-3-319-16214-0_32}}, year = {{2015}}, } @article{323, abstract = {{On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques.}}, author = {{Jungmann, Alexander and Mohr, Felix}}, journal = {{Journal of Internet Services and Applications}}, number = {{1}}, pages = {{1--18}}, publisher = {{Springer}}, title = {{{An approach towards adaptive service composition in markets of composed services}}}, doi = {{10.1186/s13174-015-0022-8}}, year = {{2015}}, } @inproceedings{324, abstract = {{Services are self-contained software components that can beused platform independent and that aim at maximizing software reuse. Abasic concern in service oriented architectures is to measure the reusabilityof services. One of the most important qualities is the functionalreusability, which indicates how relevant the task is that a service solves.Current metrics for functional reusability of software, however, have verylittle explanatory power and do not accomplish this goal.This paper presents a new approach to estimate the functional reusabilityof services based on their relevance. To this end, it denes the degreeto which a service enables the execution of other services as its contri-bution. Based on the contribution, relevance of services is dened as anestimation for their functional reusability. Explanatory power is obtainedby normalizing relevance values with a reference service. The applicationof the metric to a service test set conrms its supposed capabilities.}}, author = {{Mohr, Felix}}, booktitle = {{Proceedings of the 14th International Conference on Software Reuse (ICSR)}}, pages = {{298----313}}, title = {{{A Metric for Functional Reusability of Services}}}, doi = {{10.1007/978-3-319-14130-5_21}}, year = {{2015}}, } @article{3343, abstract = {{In this paper we consider an extended variant of query learning where the hidden concept is embedded in some Boolean circuit. This additional processing layer modifies query arguments and answers by fixed transformation functions which are known to the learner. For this scenario, we provide a characterization of the solution space and an ordering on it. We give a compact representation of the minimal and maximal solutions as quantified Boolean formulas and we adapt the original algorithms for exact learning of specific classes of propositional formulas.}}, author = {{Bubeck, Uwe and Kleine Büning, Hans}}, issn = {{0004-3702}}, journal = {{Artificial Intelligence}}, keywords = {{Query learning, Propositional logic}}, pages = {{246 -- 257}}, publisher = {{Elsevier}}, title = {{{Learning Boolean Specifications}}}, doi = {{10.1016/j.artint.2015.09.003}}, year = {{2015}}, } @article{290, abstract = {{Model transformation is a key concept in model-driven software engineering. The definition of model transformations is usually based on meta-models describing the abstract syntax of languages. While meta-models are thereby able to abstract from uperfluous details of concrete syntax, they often loose structural information inherent in languages, like information on model elements always occurring together in particular shapes. As a consequence, model transformations cannot naturally re-use language structures, thus leading to unnecessary complexity in their development as well as in quality assurance.In this paper, we propose a new approach to model transformation development which allows to simplify the developed transformations and improve their quality via the exploitation of the languages׳ structures. The approach is based on context-free graph grammars and transformations defined by pairing productions of source and target grammars. We show that such transformations have important properties: they terminate and are sound, complete, and deterministic.}}, author = {{Besova, Galina and Steenken, Dominik and Wehrheim, Heike}}, journal = {{Computer Languages, Systems & Structures}}, pages = {{116--138}}, publisher = {{Elsevier}}, title = {{{Grammar-based model transformations: Definition, execution, and quality properties}}}, doi = {{10.1016/j.cl.2015.05.003}}, year = {{2015}}, } @misc{291, author = {{Börding, Paul}}, publisher = {{Universität Paderborn}}, title = {{{Fuzzy Matching von Vor- und Nachbedingungen in Servicespezikationen}}}, year = {{2015}}, } @inbook{293, abstract = {{Opinion mining from physician rating websites depends on the quality of the extracted information. Sometimes reviews are user-error prone and the assigned stars or grades contradict the associated content. We therefore aim at detecting random individual error within reviews. Such errors comprise the disagreement in polarity of review texts and the respective ratings. The challenges that thereby arise are (1) the content and sentiment analysis of the review texts and (2) the removal of the random individual errors contained therein. To solve these tasks, we assign polarities to automatically recognized opinion phrases in reviews and then check for divergence in rating and text polarity. The novelty of our approach is that we improve user-generated data quality by excluding error-prone reviews on German physician websites from average ratings.}}, author = {{Geierhos, Michaela and Bäumer, Frederik Simon and Schulze, Sabine and Stuß, Valentina}}, booktitle = {{Proceedings of the 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2015)}}, editor = {{Ali, Moonis and Kwon, Young Sig and Lee, Chang-Hwan and Kim, Juntae and Kim, Yongdai }}, isbn = {{978-3-319-19065-5}}, location = {{Seoul, South Korea}}, pages = {{305--315}}, publisher = {{Springer}}, title = {{{Filtering Reviews by Random Individual Error}}}, doi = {{10.1007/978-3-319-19066-2_30}}, volume = {{9101}}, year = {{2015}}, } @misc{300, author = {{Neumann, Conrad}}, publisher = {{Universität Paderborn}}, title = {{{Ein Framework für Fuzzy Service Matching basierend auf Fuzzy Sets}}}, year = {{2015}}, } @misc{310, author = {{Bruns, Melanie}}, publisher = {{Universität Paderborn}}, title = {{{Design of an Evaluation Strategy for Fuzzy Service Matching}}}, year = {{2015}}, } @inproceedings{313, abstract = {{Nowadays, many service providers offer software components in the form of Software as a Service. Requesters that want to discover those services in order to use or to integrate them, need to find out which service satisfies their requirements best. For this purpose, service matching approaches determine how well the specifications of provided services satisfy their requirements (including structural, behavioral, and non-functional requirements). In this paper, we describe the tool-suite MatchBox that allows the integration of existing service matchers and their combination as part of flexibly configurable matching processes. Taking requirements and service specifications as an input, MatchBox is able to execute such matching processes and deliver rich matching results. In contrast to related tools, MatchBox allows users to take into account many different kinds of requirements, while it also provides the flexibility to control the matching process in many different ways. }}, author = {{Börding, Paul and Bruns, Melanie and Platenius, Marie Christin}}, booktitle = {{10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE'15)}}, pages = {{974----977}}, title = {{{Comprehensive Service Matching with MatchBox}}}, doi = {{10.1145/2786805.2803181}}, year = {{2015}}, } @inproceedings{315, abstract = {{In this paper, we introduce an approach for combining embedded systems with Service-oriented Computing techniques based on a concrete application scenario from the robotics domain. Our proposed Service-oriented Architecture allows for incorporating computational expensive functionality as services into a distributed computing environment. Furthermore, our framework facilitates a seamless integration of embedded systems such as robots as service providers into the computing environment. The entire communication is based on so-called recipes, which can be interpreted as autonomous messages that contain all necessary information for executing compositions of services.}}, author = {{Jungmann, Alexander and Jatzkowski, Jan and Kleinjohann, Bernd}}, booktitle = {{Proceedings of the 5th IFIP International Embedded Systems Symposium}}, title = {{{Combining Service-oriented Computing with Embedded Systems - A Robotics Case Study}}}, year = {{2015}}, } @article{3162, author = {{Ziegert, Steffen and Wehrheim, Heike}}, journal = {{Computer Science - R & D}}, number = {{3-4}}, pages = {{303----320}}, title = {{{Temporal plans for software architecture reconfiguration}}}, doi = {{10.1007/s00450-014-0259-7}}, year = {{2015}}, } @phdthesis{318, author = {{Huma, Zille}}, publisher = {{Universität Paderborn}}, title = {{{Automatic Service Discovery and Composition for heterogeneous service partners}}}, year = {{2015}}, } @inproceedings{319, abstract = {{Services are self-contained and platform independent software components that aim at maximizing software reuse. The automated composition of services to a target software artifact has been tackled with many AI techniques, but existing approaches make unreasonably strong assumptions such as a predefined data flow, are limited to tiny problem sizes, ignore non-functional properties, or assume offline service repositories. This paper presents an algorithm that automatically composes services without making such assumptions. We employ a backward search algorithm that starts from an empty composition and prepends service calls to already discovered candidates until a solution is found. Available services are determined during the search process. We implemented our algorithm, performed an experimental evaluation, and compared it to other approaches.}}, author = {{Mohr, Felix and Jungmann, Alexander and Kleine Büning, Hans}}, booktitle = {{Proceedings of the 12th IEEE International Conference on Services Computing (SCC)}}, pages = {{57----64}}, title = {{{Automated Online Service Composition}}}, doi = {{10.1109/SCC.2015.18}}, year = {{2015}}, } @inproceedings{272, abstract = {{Automated service composition aims at automatically generating software solutions based on services to provide more complex functionality. In this paper, we give an initial overview about why adaptivity becomes increasingly important when aiming for automated composition of service functionality in dynamic and freely accessible environments such as service markets. We systematically derive dependencies among crucial processes such as service composition and service execution in a holistic view. Furthermore, we briefly discuss the influences and effects of changes in the environment according to the derived dependencies, and derive possible future research directions. }}, author = {{Jungmann, Alexander}}, booktitle = {{Proceedings of the IEEE 11th World Congress on Services (SERVICES)}}, pages = {{329----332}}, title = {{{On Adaptivity for Automated Composition of Service Functionality}}}, doi = {{10.1109/SERVICES.2015.57}}, year = {{2015}}, } @inproceedings{279, abstract = {{Service discovery in global software markets is performed by brokers who act as intermediaries between service consumers and service providers.In order to discover services, brokers apply service matching for determining whether the specification of a provided service satisfies the consumer's requirements.Brokers can already choose between a lot of different service matching approaches considering different service properties (structural, behavioral, and non-functional properties).Different matching approaches can be combined into configurable matching processes leading to a high matching quality (e.g., accurate matching results). However, this combination and configuration is a manual procedure and has to be repeated for different consumers' or market requirements regarding matching quality. In this paper, we propose our framework MatchBox, which supports a broker in reusing existing matching approaches and combining them in a model-driven way based on a reconfigurable model of the matching process.Using this reconfigurable model, MatchBox takes care of control and data flow between matching approaches and executes the modeled processes automatically.As a case study, we integrated eleven matchers into MatchBox to demonstrate that it remains flexibility and reduces effort for a broker at the same time.}}, author = {{Platenius, Marie Christin and Arifulina, Svetlana and Schäfer, Wilhelm}}, booktitle = {{Proceedings of the 18th International ACM Sigsoft Symposium on Component-Based Software Engineering (CBSE'15)}}, pages = {{75--84}}, title = {{{MatchBox: A Framework for Dynamic Configuration of Service Matching Processes}}}, doi = {{10.1145/2737166.2737174}}, year = {{2015}}, }