@inproceedings{18249, abstract = {{Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration. Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product con-figuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (e.g. tabletop, ta-ble legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Schmidt, Eugen and Engels, Gregor}}, booktitle = {{Human-Centered Software Engineering. HCSE 2020}}, editor = {{Bernhaupt, Regina and Ardito, Carmelo and Sauer, Stefan}}, keywords = {{Product Configuration, Augmented Reality, Runtime Adaptation, Dynamic Software Product Lines}}, location = {{Eindhoven}}, publisher = {{Springer}}, title = {{{Model-based Product Configuration in Augmented Reality Applications}}}, doi = {{10.1007/978-3-030-64266-2_5}}, volume = {{12481}}, year = {{2020}}, } @inproceedings{16933, abstract = {{The continuous innovation of its business models is an important task for a company to stay competitive. During this process, the company has to validate various hypotheses about its business models by adapting to uncertain and changing customer needs effectively and efficiently. This adaptation, in turn, can be supported by the concept of Software Product Lines (SPLs). SPLs reduce the time to market by deriving products for customers with changing requirements using a common set of features, structured as a feature model. Analogously, we support the process of business model adaptation by applying the engineering process of SPLs to the structure of the Business Model Canvas (BMC). We call this concept a Business Model Decision Line (BMDL). The BMDL matches business domain knowledge in the form of a feature model with customer needs to derive hypotheses about the business model together with experiments for validation. Our approach is effective by providing a comprehensive overview of possible business model adaptations and efficient by reusing experiments for different hypotheses. We implement our approach in a tool and illustrate the usefulness with an example of developing business models for a mobile application.}}, author = {{Gottschalk, Sebastian and Rittmeier, Florian and Engels, Gregor}}, booktitle = {{Proceedings of the 22nd IEEE International Conference on Business Informatics}}, keywords = {{Business Model Decision Line, Business Model Adaptation, Hypothesis-driven Adaptation, Software Product Line, Feature Model}}, location = {{Antwerp}}, publisher = {{IEEE}}, title = {{{Hypothesis-driven Adaptation of Business Models based on Product Line Engineering}}}, doi = {{10.1109/CBI49978.2020.00022}}, year = {{2020}}, } @article{20533, author = {{Krüger, Stefan and Späth, Johannes and Ali, Karim and Bodden, Eric and Mezini, Mira}}, issn = {{2326-3881}}, journal = {{IEEE Transactions on Software Engineering}}, keywords = {{Java, Encryption, Static analysis, Tools, Ciphers, Semantics, cryptography, domain-specific language, static analysis}}, pages = {{1--1}}, title = {{{CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs}}}, doi = {{10.1109/TSE.2019.2948910}}, year = {{2019}}, } @inproceedings{9275, abstract = {{In the last years, store-oriented software ecosystems are gaining more and more attention from a business perspective. In these ecosystems, third-party developers upload extensions to a store which can be downloaded by end users. While the functional scope of such ecosystems is relatively similar, the underlying business models differ greatly in and between their different product domains (e.g. Mobile Phone, Smart TV). This variability, in turn, makes it challenging for store providers to find a business model that fits their own needs. To handle this variability, we introduce the Business Variability Model (BVM) for modeling business model decisions. The basis of these decisions is the analysis of 60 store-oriented software ecosystems in eight different product domains. We map their business model decisions to the Business Model Canvas, condense them to a variability model and discuss particular variants and their dependencies. Our work provides store providers a new approach for modeling business model decisions together with insights of existing business models. This, in turn, supports them in creating new and improving existing business models.}}, author = {{Gottschalk, Sebastian and Rittmeier, Florian and Engels, Gregor}}, booktitle = {{Business Modeling and Software Design}}, editor = {{Shishkov, Boris}}, keywords = {{Software Ecosystems, Business Models, Variabilities}}, location = {{Lisbon}}, pages = {{153--169}}, publisher = {{Springer International Publishing}}, title = {{{Business Models of Store-Oriented Software Ecosystems: A Variability Modeling Approach}}}, doi = {{10.1007/978-3-030-24854-3_10}}, year = {{2019}}, } @article{8424, abstract = {{The vision of On-the-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language. Since non-technical users write their software requirements themselves and in unrestricted natural language, deficits occur such as inaccuracy and incompleteness. These deficits are usually met by natural language processing methods, which have to face special challenges in OTF Computing because maximum automation is the goal. In this paper, we present current automatic approaches for solving inaccuracies and incompletenesses in natural language requirement descriptions and elaborate open challenges. In particular, we will discuss the necessity of domain-specific resources and show why, despite far-reaching automation, an intelligent and guided integration of end users into the compensation process is required. In this context, we present our idea of a chat bot that integrates users into the compensation process depending on the given circumstances. }}, author = {{Bäumer, Frederik Simon and Kersting, Joschka and Geierhos, Michaela}}, issn = {{2073-431X}}, journal = {{Computers}}, keywords = {{Inaccuracy Detection, Natural Language Software Requirements, Chat Bot}}, location = {{Vilnius, Lithuania}}, number = {{1}}, publisher = {{MDPI AG, Basel, Switzerland}}, title = {{{Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches}}}, doi = {{10.3390/computers8010022}}, volume = {{8}}, year = {{2019}}, } @inproceedings{9809, abstract = {{Remarkable advantages of Containers (CNs) over Virtual Machines (VMs) such as lower overhead and faster startup has gained the attention of Communication Service Providers (CSPs) as using CNs for providing Virtual Network Functions (VNFs) can save costs while increasing the service agility. However, as it is not feasible to realise all types of VNFs in CNs, the coexistence of VMs and CNs is proposed. To put VMs and CNs together, an orchestration framework that can chain services across distributed and heterogeneous domains is required. To this end, we implemented a framework by extending and consolidating state-of-the-art tools and technologies originated from Network Function Virtualization (NFV), Software-defined Networking (SDN) and cloud computing environments. This framework chains services provisioned across Kubernetes and OpenStack domains. During the demo, we deploy a service consist of CN- and VM-based VNFs to demonstrate different features provided by our framework.}}, author = {{Razzaghi Kouchaksaraei, Hadi and Karl, Holger}}, booktitle = {{13th ACM International Conference on Distributed and Event-based Systems}}, keywords = {{Network Function Virtualization, Software-defined Networking, Cloud Computing, service orchestration, OpenStack, Kubernetes}}, location = {{Darmstadt}}, title = {{{Service Function Chaining Across OpenStack and Kubernetes Domains}}}, doi = {{10.1145/3328905.3332505}}, year = {{2019}}, } @inproceedings{9850, abstract = {{A business model describes the mechanisms whereby a firm creates, delivers, and captures value. Following the steadily growing interest in business model innovation, software tools have shown great potential in supporting business model development and innovation. Yet, understanding the cognitive processes involved in the generation of business model ideas is an aspect of software design-knowledge that has so far been neglected. To investigate whether providing stimuli – in this case, brainstorming questions – can enhance individual creativity in this context, we conduct an exploratory experiment with over 100 participants. Our study is the first to systematically investigate the process of idea generation using a software-based business model development tool with stimuli. Our preliminary findings have the potential to support the future development of business model development tools and to refine the research design used to evaluate such tools.}}, author = {{Szopinski, Daniel}}, booktitle = {{Proceedings of the ACM Creativity & Cognition}}, keywords = {{Business model innovation, idea generation, cognitive stimuli, business model development tools, experiment, creativity support system}}, location = {{San Diego, USA}}, title = {{{Can stimuli improve business model idea generation? Developing software-based tools for business model innovation}}}, year = {{2019}}, } @inproceedings{15368, abstract = {{Service Level Agreements are essential tools enabling clients and telco operators to specify required quality of service. The 5GTANGO NFV platform enables SLAs through policies and custom service lifecycle management components. This allows the operator to trigger certain lifecycle management events for a service, and the network service developer to define how to execute such events (e.g., how to scale). In this demo we will demonstrate this unique 5GTANGO concept using an elastic proxy service supported by a high availability SLA enforced through a range of traffic regimes.}}, author = {{Soenen, Thomas and Vicens, Felipe and Bonnet, José and Parada, Carlos and Kapassa, Evgenia and Touloupou, Marious and Fotopulou, Eleni and Zafeiropoulos, Anastasios and Pol, Ana and Kolometsos, Stavros and Xilouris, George and Alemany, Pol and Vilalta, Ricard and Trakadas, Panos and Karkazis, Panos and Peuster, Manuel and Tavernier, Wouter}}, booktitle = {{2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)}}, issn = {{1573-0077}}, keywords = {{5G mobile communication, contracts, quality of service, telecommunication traffic, virtualisation, custom service lifecycle management components, lifecycle management events, network service developer, elastic proxy service, SLA-controlled proxy service, customisable MANO, operator policies, Service Level Agreements, unique 5G TANGO concept, 5G TANGO NFV platform, quality of service, traffic regimes, high availability SLA, Monitoring, Probes, Portals, Quality of service, Tools, Servers, Graphical user interfaces}}, location = {{Arlington, VA, USA, USA}}, pages = {{707--708}}, title = {{{SLA-controlled Proxy Service Through Customisable MANO Supporting Operator Policies}}}, year = {{2019}}, } @inproceedings{10108, abstract = {{Recent years have seen the development of numerous tools for the analysis of taint flows in Android apps. Taint analyses aim at detecting data leaks, accidentally or by purpose programmed into apps. Often, such tools specialize in the treatment of specific features impeding precise taint analysis (like reflection or inter-app communication). This multitude of tools, their specific applicability and their various combination options complicate the selection of a tool (or multiple tools) when faced with an analysis instance, even for knowledgeable users, and hence hinders the successful adoption of taint analyses. In this work, we thus present CoDiDroid, a framework for cooperative Android app analysis. CoDiDroid (1) allows users to ask questions about flows in apps in varying degrees of detail, (2) automatically generates subtasks for answering such questions, (3) distributes tasks onto analysis tools (currently DroidRA, FlowDroid, HornDroid, IC3 and two novel tools) and (4) at the end merges tool answers on subtasks into an overall answer. Thereby, users are freed from having to learn about the use and functionality of all these tools while still being able to leverage their capabilities. Moreover, we experimentally show that cooperation among tools pays off with respect to effectiveness, precision and scalability.}}, author = {{Pauck, Felix and Wehrheim, Heike}}, booktitle = {{Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering}}, isbn = {{978-1-4503-5572-8}}, keywords = {{Android Taint Analysis, Cooperation, Precision, Tools}}, pages = {{374--384}}, title = {{{Together Strong: Cooperative Android App Analysis}}}, doi = {{10.1145/3338906.3338915}}, year = {{2019}}, } @article{17666, abstract = {{Software Defined Networks (SDN) and Network Function Virtualisation (NFV) provide the basis for autonomous response and mitigation against attacks on networked computer infrastructures. We propose a new framework that uses SDNs and NFV to achieve this goal: Secure Autonomous Response Network (SARNET). In a SARNET, an agent running a control loop constantly assesses the security state of the network by means of observables. The agent reacts to and resolves security problems, while learning from its previous decisions. Two main metrics govern the decision process in a SARNET: impact and efficiency; these metrics can be used to compare and evaluate countermeasures and are the building blocks for self-learning SARNETs that exhibit autonomous response. In this paper we present the software implementation of the SARNET framework, evaluate it in a real-life network and discuss the tradeoffs between parameters used by the SARNET agent and the efficiency of its actions.}}, author = {{Koning, R. and de Graaff, B. and Polevoy, Gleb and Meijer, R. and de Laat, C. and Grosso, P.}}, issn = {{0167-739X}}, journal = {{Future Generation Computer Systems}}, keywords = {{Software defined networks, Network function virtualization, Cyber attacks, Cyber security, Defense efficiency, Overlay networks}}, title = {{{Measuring the efficiency of SDN mitigations against attacks on computer infrastructures}}}, doi = {{https://doi.org/10.1016/j.future.2018.08.011}}, year = {{2018}}, } @article{20543, author = {{Nguyen Quang Do, Lisa and Krüger, Stefan and Hill, Patrick and Ali, Karim and Bodden, Eric}}, issn = {{2326-3881}}, journal = {{IEEE Transactions on Software Engineering}}, keywords = {{Debugging, Static analysis, Tools, Computer bugs, Standards, Writing, Encoding, Testing and Debugging, Program analysis, Development tools, Integrated environments, Graphical environments, Usability testing}}, pages = {{1--1}}, title = {{{Debugging Static Analysis}}}, doi = {{10.1109/TSE.2018.2868349}}, year = {{2018}}, } @inbook{2322, abstract = {{The vision of On-The-Fly Computing is an automatic composition of existing software services. Based on natural language software descriptions, end users will receive compositions tailored to their needs. For this reason, the quality of the initial software service description strongly determines whether a software composition really meets the expectations of end users. In this paper, we expose open NLP challenges needed to be faced for service composition in On-The-Fly Computing.}}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela}}, booktitle = {{Proceedings of the 23rd International Conference on Natural Language and Information Systems}}, editor = {{Silberztein, Max and Atigui, Faten and Kornyshova, Elena and Métais, Elisabeth and Meziane, Farid }}, isbn = {{978-3-319-91946-1}}, keywords = {{Requirements Extraction, Temporal Reordering of Software Functions, Inaccuracy Compensation}}, location = {{Paris, France}}, pages = {{509--513}}, publisher = {{Springer}}, title = {{{How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges}}}, doi = {{10.1007/978-3-319-91947-8_53}}, volume = {{10859}}, year = {{2018}}, } @article{2331, abstract = {{A user generally writes software requirements in ambiguous and incomplete form by using natural language; therefore, a software developer may have difficulty in clearly understanding what the meanings are. To solve this problem with automation, we propose a classifier for semantic annotation with manually pre-defined semantic categories. To improve our classifier, we carefully designed syntactic features extracted by constituency and dependency parsers. Even with a small dataset and a large number of classes, our proposed classifier records an accuracy of 0.75, which outperforms the previous model, REaCT.}}, author = {{Kim, Yeongsu and Lee, Seungwoo and Dollmann, Markus and Geierhos, Michaela}}, issn = {{2207-6360}}, journal = {{International Journal of Advanced Science and Technology}}, keywords = {{Software Engineering, Natural Language Processing, Semantic Annotation, Machine Learning, Feature Engineering, Syntactic Structure}}, pages = {{123--136}}, publisher = {{SERSC Australia}}, title = {{{Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure}}}, doi = {{10.14257/ijast.2018.112.12}}, volume = {{112}}, year = {{2018}}, } @inproceedings{4339, abstract = {{On-The-Fly Computing is the vision of covering software needs of end users by fully-automatic compositions of existing software services. End users will receive so-called service compositions tailored to their very individual needs, based on natural language software descriptions. This everyday language may contain inaccuracies and incompleteness, which are well-known challenges in requirements engineering. In addition to existing approaches that try to automatically identify and correct these deficits, there are also new trends to involve users more in the elaboration and refinement process. In this paper, we present the relevant state of the art in the field of automated detection and compensation of multiple inaccuracies in natural language service descriptions and name open challenges needed to be tackled in NL-based software service composition. }}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela}}, booktitle = {{Proceedings of the 24th International Conference on Information and Software Technologies (ICIST 2018)}}, editor = {{Damaševičius, Robertas and Vasiljevienė, Giedrė}}, isbn = {{9783319999715}}, issn = {{1865-0929}}, keywords = {{Inaccuracy detection, Natural language software requirements}}, location = {{Vilnius, Lithuania}}, pages = {{559--570}}, publisher = {{Springer}}, title = {{{NLP in OTF Computing: Current Approaches and Open Challenges}}}, doi = {{10.1007/978-3-319-99972-2_46}}, volume = {{920}}, year = {{2018}}, } @inproceedings{44, abstract = {{Natural language software requirements descriptions enable end users to formulate their wishes and expectations for a future software product without much prior knowledge in requirements engineering. However, these descriptions are susceptible to linguistic inaccuracies such as ambiguities and incompleteness that can harm the development process. There is a number of software solutions that can detect deficits in requirements descriptions and partially solve them, but they are often hard to use and not suitable for end users. For this reason, we develop a software system that helps end-users to create unambiguous and complete requirements descriptions by combining existing expert tools and controlling them using automatic compensation strategies. In order to recognize the necessity of individual compensation methods in the descriptions, we have developed linguistic indicators, which we present in this paper. Based on these indicators, the whole text analysis pipeline is ad-hoc configured and thus adapted to the individual circumstances of a requirements description.}}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela}}, booktitle = {{Proceedings of the 51st Hawaii International Conference on System Sciences}}, isbn = {{978-0-9981331-1-9}}, keywords = {{Software Product Lines: Engineering, Services, and Management, Ambiguities, Incompleteness, Natural Language Processing, Software Requirements}}, location = {{Big Island, Waikoloa Village}}, pages = {{5746--5755}}, title = {{{Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-based Configuration of Text Analysis Pipelines}}}, doi = {{10125/50609}}, year = {{2018}}, } @inproceedings{48867, abstract = {{Assessing the performance of stochastic optimization algorithms in the field of multi-objective optimization is of utmost importance. Besides the visual comparison of the obtained approximation sets, more sophisticated methods have been proposed in the last decade, e. g., a variety of quantitative performance indicators or statistical tests. In this paper, we present tools implemented in the R package ecr, which assist in performing comprehensive and sound comparison and evaluation of multi-objective evolutionary algorithms following recommendations from the literature.}}, author = {{Bossek, Jakob}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}}, isbn = {{978-1-4503-5764-7}}, keywords = {{evolutionary optimization, performance assessment, software-tools}}, pages = {{1350–1356}}, publisher = {{Association for Computing Machinery}}, title = {{{Performance Assessment of Multi-Objective Evolutionary Algorithms with the R Package ecr}}}, doi = {{10.1145/3205651.3208312}}, year = {{2018}}, } @article{20557, author = {{Lillack, Max and Kästner, Christian and Bodden, Eric}}, issn = {{0098-5589}}, journal = {{IEEE Transactions on Software Engineering}}, keywords = {{Androids, Bluetooth, Humanoid robots, Java, Software, Tools, Configuration options, Static analysis, Variability mining}}, number = {{99}}, pages = {{1--1}}, title = {{{Tracking Load-time Configuration Options}}}, doi = {{10.1109/TSE.2017.2756048}}, volume = {{PP}}, year = {{2017}}, } @inproceedings{97, abstract = {{Bridging the gap between informal, imprecise, and vague user requirements descriptions and precise formalized specifications is the main task of requirements engineering. Techniques such as interviews or story telling are used when requirements engineers try to identify a user's needs. The requirements specification process is typically done in a dialogue between users, domain experts, and requirements engineers. In our research, we aim at automating the specification of requirements. The idea is to distinguish between untrained users and trained users, and to exploit domain knowledge learned from previous runs of our system. We let untrained users provide unstructured natural language descriptions, while we allow trained users to provide examples of behavioral descriptions. In both cases, our goal is to synthesize formal requirements models similar to statecharts. From requirements specification processes with trained users, behavioral ontologies are learned which are later used to support the requirements specification process for untrained users. Our research method is original in combining natural language processing and search-based techniques for the synthesis of requirements specifications. Our work is embedded in a larger project that aims at automating the whole software development and deployment process in envisioned future software service markets.}}, author = {{van Rooijen, Lorijn and Bäumer, Frederik Simon and Platenius, Marie Christin and Geierhos, Michaela and Hamann, Heiko and Engels, Gregor}}, booktitle = {{2017 IEEE 25th International Requirements Engineering Conference Workshops (REW)}}, isbn = {{978-1-5386-3489-9}}, keywords = {{Software, Unified modeling language, Requirements engineering, Ontologies, Search problems, Natural languages}}, location = {{Lisbon, Portugal}}, pages = {{379--385}}, publisher = {{IEEE}}, title = {{{From User Demand to Software Service: Using Machine Learning to Automate the Requirements Specification Process}}}, doi = {{10.1109/REW.2017.26}}, year = {{2017}}, } @inproceedings{48863, abstract = {{The novel R package ecr (version 2), short for Evolutionary Computation in R, provides a comprehensive collection of building blocks for constructing powerful evolutionary algorithms for single- and multi-objective continuous and combinatorial optimization problems. It allows to solve standard optimization tasks with few lines of code using a black-box approach. Moreover, rapid prototyping of non-standard ideas is possible via an explicit, white-box approach. This paper describes the design principles of the package and gives some introductory examples on how to use the package in practise.}}, author = {{Bossek, Jakob}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}}, isbn = {{978-1-4503-4939-0}}, keywords = {{evolutionary optimization, software-tools}}, pages = {{1187–1193}}, publisher = {{Association for Computing Machinery}}, title = {{{Ecr 2.0: A Modular Framework for Evolutionary Computation in R}}}, doi = {{10.1145/3067695.3082470}}, year = {{2017}}, } @inbook{51827, author = {{Schmitt, Martin}}, booktitle = {{International Communities of Invention and Innovation}}, editor = {{Tatnall, Arthur and Leslie, Christopher}}, keywords = {{Kreditscoring, Informationssystem, Software}}, pages = {{141–164}}, publisher = {{Springer}}, title = {{{The Code of Banking. Software as the Digitalization of German Savings Banks}}}, year = {{2016}}, }