Claas Wilke

Towards modeling a variable architecture for multi-tenant SaaS-applications

A widespread business model in cloud computing is to offer software as a service (SaaS) over the Internet. Such applications are often multi-tenant aware, which means that multiple tenants share hardware and software resources of the same application instance. However, SaaS stakeholders have different or even contradictious requirements and interests: For a user, the applications quality and non-functional properties have to be maximized (e.g., choosing the fastest available algorithm for a computation at runtime). In contrast, a resource or application provider is interested in minimizing the operating costs while maximizing his profit. Finally, tenants are interested in offering a customized functionality to their users. To identify an optimal compromise for all these objectives, multiple levels of variability have to be supported by reference architectures for multi-tenant SaaS applications. In this paper, we identify requirements for such a runtime architecture addressing the individual interests of all involved stakeholders. Furthermore, we show how our existing architecture for dynamically adaptive applications can be extended for the development and operation of multi-tenant applications.

JouleUnit: a generic framework for software energy profiling and testing

Energy consumption has become an important characteristic of nowadays information and communication technology (ICT) applications, especially for mobile devices, whose uptime is limited by the available battery capacity. Hence, ICT applications are optimized to provide the best possible user satisfaction for the least possible energy budget. An inevitable prerequisite for such optimizations is the ability to analyze softwares energy consumption. In consequence, many energy profiling frameworks have been developed. The problem we address in this paper is that profiling frameworks are device- and application-specific and, hence, cannot be reused. We analyze the key requirements of energy profiling frameworks and propose a generic framework reusable for different devices and applications, designed according to these requirements. We evaluate the presented framework using two case studies showing the reusability in two significantly different scenarios.

Comparing mobile applications' energy consumption

As mobile devices are nowadays used regularly and everywhere, their energy consumption has become a central concern. However, todays mobile applications often do not consider energy requirements and users lack information on their energy consumption before they install and try them. In this paper, we compare mobile applications from two domains and show that they reveal different energy consumption while providing similar services. We define microbenchmarks for emailing and web browsing and evaluate apps from these domains. We show that non-functional features such as web page caching can but not have to have a positive influence on an applications energy consumption.

Extending variability for OCL interpretation

In recent years, OCL advanced from a language used to constrain UML models to a constraint language that is applied to various modelling languages. This includes Domain Specific Languages (DSLs) and meta-modelling languages like MOF or Ecore. Consequently, it is rather common to provide variability for OCL parsers to work with different modelling languages. A second variability dimension relates to the technical space that models are realised in. Current OCL interpreters do not support such variability as their implementation is typically bound to a specific technical space like Java, Ecore, or a specific model repository. In this paper we propose a generic adaptation architecture for OCL that hides models and model instances behind well-defined interfaces. We present how the implementation of such an architecture for DresdenOCL enables reuse of the same OCL interpreter for various technical spaces and evaluate our approach in three case studies.

DropsBox: the Dresden Open Software Toolbox

The Dresden Open Software Toolbox (DropsBox) is a software modelling toolbox consisting of a set of open source tools developed by the Software Technology Group at TU Dresden. The DropsBox is built on top of the Eclipse Platform and the Eclipse Modeling Framework. The DropsBox contributes to the development and application of domain-specific language changes (DSLs) in model-driven software development. It can be customised by tool and language developers to support various activities of a DSL’s life cycle ranging from language design to language application and evolution. In this paper, we provide an overview of the DSL life cycle, the DropsBox tools, and their interaction on a common example. Furthermore, we discuss our experiences in developing and integrating tools for DropsBox in an academic environment.

Integrating OCL and textual modelling languages

In the past years, many OCL tools achieved a transition of OCL from a language meant to constrain UML models to a universal constraint language applied to various modelling and metamodelling languages. However, OCL users still experience a discrepancy between the now highly extensible parsing and evaluation backend of OCL tools and the lack of appropriate frontend tooling like advanced OCL editors that adapt to the different application scenarios. We argue that this has to be addressed both at a technical and methodological level. Therefore, this paper provides an overview of the technical foundations to provide an integrated OCL tooling frontend and backend for arbitrary textual modelling languages and contributes a stepwise process for such an integration. We distinguish two kinds of integration: external definition of OCL constraints and embedded definition of OCL constraints. Due to the textual notation of OCL the second kind provides particularly deep integration with textual modelling languages. We apply our approach in two case studies and discuss the benefits and limitations of the approach in general and both integration kinds in particular.

UML is still inconsistent! How to improve OCL Constraints in the UML 2.3 Superstructure

Since the first OMG specification of the Unified Modeling Language (UML), the Object Constraint Language (OCL) has been used for the definition of well-formedness rules in the UML specification. These rules have been specified within the early OCL years, when no appropriate tooling existed. Thus, they could not be checked for syntactical and static semantics correctness. In this paper we present an analysis of the static correctness of all OCL rules specified in the UML 2.3 superstructure document. We categorise found errors and propose changes for both the UML specification process and the OCL language to improve the UML specification’s correctness in future versions.

Tool supported OCL refactoring catalogue

The Object Constraint Language (OCL) as the primary constraint language in model-driven software development is heavily used to specify static semantics of arbitrary languages and models. Models and constraints are therefore interconnected and depend on each other. On the one hand, daily work with models enjoys a good tool support, whereas, on the other hand, mature OCL tools are not widely spread but a niche. Unfortunately, during their life-time, the complexity of models rises and so do their OCL constraints. Thus, the gap between conventional modelling and OCL tools becomes obvious. This fact demands for OCL tool support to cope with the complexity. To bridge this gap, refactoring is well-suited and mighty. In this paper we discuss existing work, present a revised catalogue of OCL-exclusive refactorings and provide an implementation. We do not consider co-refactorings of OCL constraints and their constrained models.

Towards Energy Auto Tuning.

Energy efficiency is gaining more and more importance, since well-known ecological reasons lead to rising energy costs. In consequence, energy consumption is now also an important economical criterion. Energy consumption of single hardware resources has been thoroughly optimized for years. Now software becomes the major target of energy optimization. In this paper we introduce an approach called energy auto-tuning (EAT), which optimizes energy efficiency of software systems running on multiple resources. The optimization of more than one resource leads to higher energy savings, because communication costs can be taken into account. E.g., if two components run on the same resource, the communication costs are likely to be less, compared to be running on different resources. The best results can be achieved in heterogeneous environments as different resource characteristics enlarge the synergy effects gainable by our optimization technique. EAT software systems derive all possible distributions of themselves on a given set of hardware resources and reconfigure themselves to achieve the lowest energy consumption possible at any time. In this paper we describe our software architecture to implement EAT.

Vision paper: towards model-based energy testing

Today, energy consumption is one of the major challenges for optimisation of future software applications and ICT infrastructures. To develop software w.r.t. its energy consumption, testing is an essential activity, since testing allows quality assurance and thus, energy consumption reduction during the softwares development. Although first approaches measuring and predicting softwares energy consumption for its execution on a specific hardware platform exist, no model-based testing approach has been developed, yet. In this paper we present our vision of a model-based energy testing approach that uses a combination of abstract interpretation and run-time profiling to predict the energy consumption of software applications and to derive energy consumption test cases.