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Auflistung Softwaretechnik-Trends 39(4) - 2019 nach Erscheinungsdatum
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- KonferenzbeitragOn the Difficulties of Supervised Event Prediction based on Unbalanced Real-World Data in Multi-System Monitoring(Softwaretechnik-Trends Band 39, Heft 4, 2019) Schörgenhumer, Andreas; Kahlhofer, Mario; Chalupar, Peter; Mössenböck, Hanspeter; Grünbacher, PaulOnline failure prediction of performance-critical events is an important task in fault management of software systems. In this paper, we extend our previous multi-system event prediction by analyzing its performance on unbalanced, real-world data, which represents a realistic online scenario. We train a random forest classifier with different data preprocessing configurations, including data augmentation to cope with the extreme class imbalance. The results reveal that the prediction quality of the tested multi-system model drops significantly compared to the balanced scenario. Although our supervised event prediction approach as well as different data preprocessing configurations turned out to be ineffective, we consider the insights of our work valuable for the community.
- KonferenzbeitragModelling and Predicting Memory Behaviour in Parallel Systems with Network Links? Palladio-based Experiment Report(Softwaretechnik-Trends Band 39, Heft 4, 2019) Gruber, Philipp; Frank, MarkusThis work improves the capabilities of Palladio to predict the performance of parallel software in multicore environments. In previous work, we could show that the accuracy of the Palladio simulations is not sufficient for multicore systems. We assume that one reason for this is the memory bandwidth behaviour, which is not included in the Palladio Component Model and can become a bottleneck in parallel software. We present an approach to model the memory bandwidth behaviour by the means of an already existing network link concept. We can show that by using network link as a memory model we can improve our predictions up to 26% points using 16 cores on a machine and can receive an accuracy of 90% for our use case.
- KonferenzbeitragTowards Testing the Performance Influence of Hypervisor Hypercall Interface Behavior(Softwaretechnik-Trends Band 39, Heft 4, 2019) Beierlieb, Lukas; Iffländer, Lukas; Kounev, Samuel; Milenkoski, AleksandarWith the continuing rise of cloud technology hypervisors play a vital role in the performance and reliability of current services. Hypervisors offer so-called hypercall interfaces for communication with the hosted virtual machines. These interfaces require thorough robustness to assure performance, security, and reliability. Existing research focusses on finding hypercall-related vulnerabilities. In this work, we discuss open challenges regarding hypercall interfaces. To address these challenges, we propose an extensive framework architecture to perform robustness testing on hypercall interfaces. This framework supports test campaigns and modeling of hypercall interfaces.
- KonferenzbeitragOn Learning Parametric Dependencies from Monitoring Data(Softwaretechnik-Trends Band 39, Heft 4, 2019) Grohmann, Johannes; Eismann, Simon; Kounev, SamuelA common approach to predict system performance are so-called architectural performance models. In these models, parametric dependencies describe the relation between the input parameters of a component and its performance properties and therefore significantly increase the model expressiveness. However, manually modeling parametric dependencies is often infeasible in practice. Existing automated extraction approaches require either application source code or dedicated performance tests, which are not always available. We therefore introduced one approach for identification and one for characterization of parametric dependencies, solely based on run-time monitoring data. In this paper, we propose our idea on combining both techniques in order to create a holistic approach for the identification and characterization of parametric dependencies. Furthermore, we discuss challenges we are currently facing and potential ideas on how to overcome them.
- KonferenzbeitragOn the Validity of Performance Antipatterns at Code Level(Softwaretechnik-Trends Band 39, Heft 4, 2019) Reichelt, David Georg; Kühne, Stefan; Hasselbring, WilhelmPerformance antipatterns at code level should be avoided to assure good application performance. Performance antipatterns avoidance is hard, since it requires up-to-date knowledge of these antipatterns. Common lists of antipatterns, like the performance rules of the static code checker PMD, only contain limited information about versions and circumstances where the performance antipatterns are valid. We close this gap by prodiving a suite of 30 performance benchmarks. Each of this benchmarks checks whether the performance antipattern is measurable in Java 6, 7, 8, 11 and 12. We find that two of the 30 performance checks are not valid in the current OpenJDK 12.
- KonferenzbeitragUnderstanding the Performance of Distributed Database Management Systems in Volatile Environments(Softwaretechnik-Trends Band 39, Heft 4, 2019) Domaschka, Jörg; Seybold, DanielCloud computing provides scalability and elasticity mechanisms on resource level and has become the preferred operational model for many applications. These, in turn, are based on distributed architectures trusting that this leads to scalability and elasticity and hence, good performance. Many applications rely on one or multiple database management systems (DBMS) as storage backends in order to manage their persistent state. Hence, the selection of a DBMS for a specific use case is crucial for performance and other non-functional properties. Yet, the choice is cumbersome due to the large number of available systems and the many impact factors ranging from the size of virtual resources, the type of the DBMS, and its architecture and scaling factor. In this paper, we summarise our experiences with performance evaluation for cloud-hosted DBMS in order to find well-suited configurations for specific use cases. We demonstrate that the overall performance of a distributed DBMS depends on three major domains (workload, cloud environment, and DBMS) with various parameters for each dimension.
- KonferenzbeitragUsing OPEN.xtrace and Architecture-Level Models to Predict Workload Performance on In-Memory Database Systems(Softwaretechnik-Trends Band 39, Heft 4, 2019) Barnert, Maximilian; Streitz, Adrian; Rank, Johannes; Kienegger, Harald; Krcmar, HelmutIn-Memory Database Systems (IMDB) come into operation on highly dynamic on-premise and cloud environments. Existing approaches use classical modeling notations such as queuing network models (QN) to reflect performance on IMDB. Changes to workload or hardware come along with a recreation of entire models. At the same time, new paradigms for IMDB increase parallelism within database workload, which intensifies the effort to create and parameterize models. To simplify and reduce the effort for researchers and practitioners to model workload performance on IMDB, we propose the use of architecture level performance models and present a model creation process, which transforms database traces of SAP HANA to the Palladio Component Model (PCM). We evaluate our approach based on experiments using analytical workload. We receive prediction errors for response time and throughput below 4 %.
- KonferenzbeitragData Stream Operations as First-Class Entities in Palladio(Softwaretechnik-Trends Band 39, Heft 4, 2019) Werle, Dominik; Seifermann, Stephan; Koziolek, AnneThe Palladio Component Model (PCM) is an approach to simulate the performance of software systems using a component-based modeling language. When simulating PCM models, requests only influence each other if they compete for the same resources. However, for some applications, such as data stream processing, it is not realistic for requests to be this independent. For example, it is common to group requests in windows over time or to join data streams. Modeling the resulting behavior and resource demands in the system via stochastic approximations is possible but has drawbacks. It requires additional effort for determining the approximation and it may require spreading information across model elements that should be encapsulated in one place. In this paper, we propose a way of modeling interaction between requests that is similar to query languages for data streams. Thus, we introduce state into models without sacrificing the understandability and composability of the model.
- KonferenzbeitragMemory Leak Visualization using Evolving Software Cities(Softwaretechnik-Trends Band 39, Heft 4, 2019) Weninger, Markus; Makor, Lukas; Mössenböck, HanspeterMemory leaks occur when no longer needed objects are unnecessarily kept alive. They can have a significant performance impact, possibly leading to a crash of the application in the worst case. Most state-of-the-art memory monitoring tools lack visualizations of memory growth over time. However, domains such as software evolution and program comprehension have shown that graphically visualizing the growth and evolution of a system can help users in understanding and interpreting this growth. In this paper, we present ongoing research on how to visualize an application’s memory evolution over time using the software city metaphor. While software cities are typically used to visualize static artifacts of a software system such as classes, we use them to visualize the dynamic memory behavior of an application. In our approach, heap objects can be grouped by arbitrary properties such as their types or their allocating threads. These groups are visualized as buildings arranged in districts, where the size of a building corresponds to the number of objects it represents. Continuously updating the city over time creates the feeling of an evolving city. Users can then identify and inspect those buildings, i.e., object groups, that grow the most. We integrated our approach into AntTracks, a trace-based memory monitoring tool developed by us, to prove its feasibility.
- KonferenzbeitragMapping Data Flow Models to the Palladio Component Model(Softwaretechnik-Trends Band 39, Heft 4, 2019) Seifermann, Stephan; Werle, Dominik; Ebada, MazenPredicting quality properties such as privacy are reasonable use cases for Data Flow Models (DFMs). For other use cases such as performance prediction, component-based software architecture models focusing on control flows are more suitable. Designers can derive a Control Flow Model (CFM) from a DFM but they have to make numerous design decisions like defining operation signatures. Currently, this derivation is a creative process without a clear design space and without guidelines for navigating this space. In this paper, we present design alternatives for given data flow examples and derive mapping rules that allow to choose between reasonable alternatives. Our results are a first step towards a catalogue of rules for deriving CFMs from DFMs in a systematic way and providing semi-automated transformations.