@misc{Matthies2019, author = {Matthies, Christoph}, title = {Agile process improvement in retrospectives}, series = {41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)}, journal = {41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-7281-1764-5}, issn = {2574-1934}, doi = {10.1109/ICSE-Companion.2019.00063}, pages = {150 -- 152}, year = {2019}, abstract = {Working in iterations and repeatedly improving team workflows based on collected feedback is fundamental to agile software development processes. Scrum, the most popular agile method, provides dedicated retrospective meetings to reflect on the last development iteration and to decide on process improvement actions. However, agile methods do not prescribe how these improvement actions should be identified, managed or tracked in detail. The approaches to detect and remove problems in software development processes are therefore often based on intuition and prior experiences and perceptions of team members. Previous research in this area has focused on approaches to elicit a team's improvement opportunities as well as measurements regarding the work performed in an iteration, e.g. Scrum burn-down charts. Little research deals with the quality and nature of identified problems or how progress towards removing issues is measured. In this research, we investigate how agile development teams in the professional software industry organize their feedback and process improvement approaches. In particular, we focus on the structure and content of improvement and reflection meetings, i.e. retrospectives, and their outcomes. Researching how the vital mechanism of process improvement is implemented in practice in modern software development leads to a more complete picture of agile process improvement.}, language = {en} } @misc{Matthies2019, author = {Matthies, Christoph}, title = {Feedback in Scrum}, series = {2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)}, journal = {2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-7281-1764-5}, issn = {2574-1934}, doi = {10.1109/ICSE-Companion.2019.00081}, pages = {198 -- 201}, year = {2019}, abstract = {Improving the way that teams work together by reflecting and improving the executed process is at the heart of agile processes. The idea of iterative process improvement takes various forms in different agile development methodologies, e.g. Scrum Retrospectives. However, these methods do not prescribe how improvement steps should be conducted in detail. In this research we investigate how agile software teams can use their development data, such as commits or tickets, created during regular development activities, to drive and track process improvement steps. Our previous research focused on data-informed process improvement in the context of student teams, where controlled circumstances and deep domain knowledge allowed creation and usage of specific process measures. Encouraged by positive results in this area, we investigate the process improvement approaches employed in industry teams. Researching how the vital mechanism of process improvement is implemented and how development data is already being used in practice in modern software development leads to a more complete picture of agile process improvement. It is the first step in enabling a data-informed feedback and improvement process, tailored to a team's context and based on the development data of individual teams.}, language = {en} } @misc{BrandGiese2019, author = {Brand, Thomas and Giese, Holger}, title = {Generic adaptive monitoring based on executed architecture runtime model queries and events}, series = {IEEE Xplore}, journal = {IEEE Xplore}, publisher = {IEEE}, address = {New York}, isbn = {978-1-7281-2731-6}, issn = {1949-3673}, doi = {10.1109/SASO.2019.00012}, pages = {17 -- 22}, year = {2019}, abstract = {Monitoring is a key functionality for automated decision making as it is performed by self-adaptive systems, too. Effective monitoring provides the relevant information on time. This can be achieved with exhaustive monitoring causing a high overhead consumption of economical and ecological resources. In contrast, our generic adaptive monitoring approach supports effectiveness with increased efficiency. Also, it adapts to changes regarding the information demand and the monitored system without additional configuration and software implementation effort. The approach observes the executions of runtime model queries and processes change events to determine the currently required monitoring configuration. In this paper we explicate different possibilities to use the approach and evaluate their characteristics regarding the phenomenon detection time and the monitoring effort. Our approach allows balancing between those two characteristics. This makes it an interesting option for the monitoring function of self-adaptive systems because for them usually very short-lived phenomena are not relevant.}, language = {en} } @misc{BruechnerRenzKlingbeil2019, author = {Bruechner, Dominik and Renz, Jan and Klingbeil, Mandy}, title = {Creating a Framework for User-Centered Development and Improvement of Digital Education}, series = {Scale}, journal = {Scale}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6804-9}, doi = {10.1145/3330430.3333644}, pages = {4}, year = {2019}, abstract = {We investigate how the technology acceptance and learning experience of the digital education platform HPI Schul-Cloud (HPI School Cloud) for German secondary school teachers can be improved by proposing a user-centered research and development framework. We highlight the importance of developing digital learning technologies in a user-centered way to take differences in the requirements of educators and students into account. We suggest applying qualitative and quantitative methods to build a solid understanding of a learning platform's users, their needs, requirements, and their context of use. After concept development and idea generation of features and areas of opportunity based on the user research, we emphasize on the application of a multi-attribute utility analysis decision-making framework to prioritize ideas rationally, taking results of user research into account. Afterward, we recommend applying the principle build-learn-iterate to build prototypes in different resolutions while learning from user tests and improving the selected opportunities. Last but not least, we propose an approach for continuous short- and long-term user experience controlling and monitoring, extending existing web- and learning analytics metrics.}, language = {en} } @misc{BiloFriedrichLenzneretal.2019, author = {Bilo, Davide and Friedrich, Tobias and Lenzner, Pascal and Melnichenko, Anna}, title = {Geometric Network Creation Games}, series = {SPAA '19: The 31st ACM Symposium on Parallelism in Algorithms and Architectures}, journal = {SPAA '19: The 31st ACM Symposium on Parallelism in Algorithms and Architectures}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6184-2}, doi = {10.1145/3323165.3323199}, pages = {323 -- 332}, year = {2019}, abstract = {Network Creation Games are a well-known approach for explaining and analyzing the structure, quality and dynamics of real-world networks like the Internet and other infrastructure networks which evolved via the interaction of selfish agents without a central authority. In these games selfish agents which correspond to nodes in a network strategically buy incident edges to improve their centrality. However, past research on these games has only considered the creation of networks with unit-weight edges. In practice, e.g. when constructing a fiber-optic network, the choice of which nodes to connect and also the induced price for a link crucially depends on the distance between the involved nodes and such settings can be modeled via edge-weighted graphs. We incorporate arbitrary edge weights by generalizing the well-known model by Fabrikant et al. [PODC'03] to edge-weighted host graphs and focus on the geometric setting where the weights are induced by the distances in some metric space. In stark contrast to the state-of-the-art for the unit-weight version, where the Price of Anarchy is conjectured to be constant and where resolving this is a major open problem, we prove a tight non-constant bound on the Price of Anarchy for the metric version and a slightly weaker upper bound for the non-metric case. Moreover, we analyze the existence of equilibria, the computational hardness and the game dynamics for several natural metrics. The model we propose can be seen as the game-theoretic analogue of a variant of the classical Network Design Problem. Thus, low-cost equilibria of our game correspond to decentralized and stable approximations of the optimum network design.}, language = {en} } @misc{GonzalezLopezPufahl2019, author = {Gonzalez-Lopez, Fernanda and Pufahl, Luise}, title = {A Landscape for Case Models}, series = {Enterprise, Business-Process and Information Systems Modeling}, volume = {352}, journal = {Enterprise, Business-Process and Information Systems Modeling}, publisher = {Springer}, address = {Berlin}, isbn = {978-3-030-20618-5}, issn = {1865-1348}, doi = {10.1007/978-3-030-20618-5_6}, pages = {87 -- 102}, year = {2019}, abstract = {Case Management is a paradigm to support knowledge-intensive processes. The different approaches developed for modeling these types of processes tend to result in scattered models due to the low abstraction level at which the inherently complex processes are therein represented. Thus, readability and understandability is more challenging than that of traditional process models. By reviewing existing proposals in the field of process overviews and case models, this paper extends a case modeling language - the fragment-based Case Management (fCM) language - with the goal of modeling knowledge-intensive processes from a higher abstraction level - to generate a so-called fCM landscape. This proposal is empirically evaluated via an online experiment. Results indicate that interpreting an fCM landscape might be more effective and efficient than interpreting an informationally equivalent case model.}, language = {en} } @article{SchlosserWaltherBoissieretal.2019, author = {Schlosser, Rainer and Walther, Carsten and Boissier, Martin and Uflacker, Matthias}, title = {Automated repricing and ordering strategies in competitive markets}, series = {AI communications : AICOM ; the European journal on artificial intelligence}, volume = {32}, journal = {AI communications : AICOM ; the European journal on artificial intelligence}, number = {1}, publisher = {IOS Press}, address = {Amsterdam}, issn = {0921-7126}, doi = {10.3233/AIC-180603}, pages = {15 -- 29}, year = {2019}, abstract = {Merchants on modern e-commerce platforms face a highly competitive environment. They compete against each other using automated dynamic pricing and ordering strategies. Successfully managing both inventory levels as well as offer prices is a challenging task as (i) demand is uncertain, (ii) competitors strategically interact, and (iii) optimized pricing and ordering decisions are mutually dependent. We show how to derive optimized data-driven pricing and ordering strategies which are based on demand learning techniques and efficient dynamic optimization models. We verify the superior performance of our self-adaptive strategies by comparing them to different rule-based as well as data-driven strategies in duopoly and oligopoly settings. Further, to study and to optimize joint dynamic ordering and pricing strategies on online marketplaces, we built an interactive simulation platform. To be both flexible and scalable, the platform has a microservice-based architecture and allows handling dozens of competing merchants and streams of consumers with configurable characteristics.}, language = {en} } @misc{HalfpapSchlosser2019, author = {Halfpap, Stefan and Schlosser, Rainer}, title = {Workload-Driven Fragment Allocation for Partially Replicated Databases Using Linear Programming}, series = {2019 IEEE 35th International Conference on Data Engineering (ICDE)}, journal = {2019 IEEE 35th International Conference on Data Engineering (ICDE)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-7474-1}, issn = {1084-4627}, doi = {10.1109/ICDE.2019.00188}, pages = {1746 -- 1749}, year = {2019}, abstract = {In replication schemes, replica nodes can process read-only queries on snapshots of the master node without violating transactional consistency. By analyzing the workload, we can identify query access patterns and replicate data depending to its access frequency. In this paper, we define a linear programming (LP) model to calculate the set of partial replicas with the lowest overall memory capacity while evenly balancing the query load. Furthermore, we propose a scalable decomposition heuristic to calculate solutions for larger problem sizes. While guaranteeing the same performance as state-of-the-art heuristics, our decomposition approach calculates allocations with up to 23\% lower memory footprint for the TPC-H benchmark.}, language = {en} } @misc{HalfpapSchlosser2019, author = {Halfpap, Stefan and Schlosser, Rainer}, title = {A Comparison of Allocation Algorithms for Partially Replicated Databases}, series = {2019 IEEE 35th International Conference on Data Engineering (ICDE)}, journal = {2019 IEEE 35th International Conference on Data Engineering (ICDE)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-7474-1}, issn = {1084-4627}, doi = {10.1109/ICDE.2019.00226}, pages = {2008 -- 2011}, year = {2019}, abstract = {Increasing demand for analytical processing capabilities can be managed by replication approaches. However, to evenly balance the replicas' workload shares while at the same time minimizing the data replication factor is a highly challenging allocation problem. As optimal solutions are only applicable for small problem instances, effective heuristics are indispensable. In this paper, we test and compare state-of-the-art allocation algorithms for partial replication. By visualizing and exploring their (heuristic) solutions for different benchmark workloads, we are able to derive structural insights and to detect an algorithm's strengths as well as its potential for improvement. Further, our application enables end-to-end evaluations of different allocations to verify their theoretical performance.}, language = {en} } @article{FriedrichKrejcaRothenbergeretal.2019, author = {Friedrich, Tobias and Krejca, Martin Stefan and Rothenberger, Ralf and Arndt, Tobias and Hafner, Danijar and Kellermeier, Thomas and Krogmann, Simon and Razmjou, Armin}, title = {Routing for on-street parking search using probabilistic data}, series = {AI communications : AICOM ; the European journal on artificial intelligence}, volume = {32}, journal = {AI communications : AICOM ; the European journal on artificial intelligence}, number = {2}, publisher = {IOS Press}, address = {Amsterdam}, issn = {0921-7126}, doi = {10.3233/AIC-180574}, pages = {113 -- 124}, year = {2019}, abstract = {A significant percentage of urban traffic is caused by the search for parking spots. One possible approach to improve this situation is to guide drivers along routes which are likely to have free parking spots. The task of finding such a route can be modeled as a probabilistic graph problem which is NP-complete. Thus, we propose heuristic approaches for solving this problem and evaluate them experimentally. For this, we use probabilities of finding a parking spot, which are based on publicly available empirical data from TomTom International B.V. Additionally, we propose a heuristic that relies exclusively on conventional road attributes. Our experiments show that this algorithm comes close to the baseline by a factor of 1.3 in our cost measure. Last, we complement our experiments with results from a field study, comparing the success rates of our algorithms against real human drivers.}, language = {en} }