Performance Analysis of Legacy Perl Software via Batch and Interactive Trace Visualization

Performing an analysis of established software usually is challenging. Based on reverse engineering through dynamic analysis, it is possible to perform a software performance analysis, in order to detect performance bottlenecks or issues. This process is often divided into two consecutive tasks. The first task concerns the monitoring of the legacy software, and the second task covers analysing and visualizing the results. Dynamic analysis is usually addressed via trace visualization, but finding an appropriate representation for a specific issue still remains a great challenge. In this paper we report on our performance analysis of the Perl-based open repository software EPrints, which has now been continuously developed for more than fifteen years. We analyse and evaluate the software using the Kieker monitoring framework, and apply and combine two types of visualization tools, namely Graphviz and Gephi. More precisely, we employ Kieker to reconstruct architectural models from recorded monitoring data, based on dynamic analysis, and Graphviz respectively Gephi for further analysis and visualization of our monitoring results. We acquired knowledge of the software through our instrumentation and analysis via Kieker and the combined visualization of the two aforementioned tools. This allowed us, in collaboration with the EPrints development team, to reverse engineer their software EPrints, to give new and unexpected insights, and to detect potential bottlenecks

Automated Cloud-to-Cloud Migration of Distributed Software Systems for Privacy Compliance

Mit der ständig wachsenden Zahl von verteilten Cloudanwendungen und immer mehr Datenschutzverordnungen wächst das Interesse an legalen Cloudanwendungen. Jedoch ist vielen Betreibern der Legalitätsstatus ihrer Anwendung nicht bekannt. In 2018 wird die neue EU Datenschutzverordnung in Kraft treten. Diese Verordnung beinhaltet empfindliche Strafen für Datenschutzverletzungen. Einer der wichtigsten Faktoren für die Einhaltung der Datenschutzverordnung ist die Verarbeitung von Stammdaten von EU-Bürgern innerhalb der EU. Wir haben für diese Regelung eine Privacy Analyse entwickelt, formalisiert, implementiert und evaluiert. Außerdem haben wir mit iObserve Privacy ein System nach dem MAPE-Prinzip entwickelt, das automatisch Datenschutzverletzungen erkennt und ein alternatives, datenschutzkonformes Systemhosting errechnet. Zudem migriert iObserve Privacy die Cloudanwendung entsprechend dem alternativen Hosting automatisch. Hierdurch können wir eine rechtskonforme Verteilung der Cloudanwendung gewährleisten, ohne das System in seiner Tiefe zu analysieren oder zu verstehen. Jedoch benötigen wir die Closed World Assumption. Wir benutzen PerOpteryx für die Generierung von rechtskonformen, alternativen Hostings. Basierend auf diesem Hosting errechnen wir eine Sequenz von Adaptionsschritten zur Wiedererlangung der Rechtskonformität. Wenn Fehler auftreten, nutzen wir das Operator-in-the-loop Prinzip von iObserve. Als Datengrundlage nutzen wir das Palladio Component Model. In dieser Arbeit beschreiben wir detailliert die Konzepte, weisen auf Implementierungsdetails hin und evaluieren iObserve nach Präzision und Skalierbarkeit

MAMBA: A Measurement Architecture for Model-Based Analysis

Model-based measurement techniques are relevant in the field of software analysis. Several meta models for the specification of quantitative measures have been proposed. However, they often focus either on static or dynamic aspects of a software system. Nevertheless, considering reengineering activities often both dimensions reveal valuable complementary insights. Existing meta models are also frequently bound to specific modeling languages, redefine underlying concepts for any new meta model, or provide only limited tool support for the automated computation of measurements from modeled measures. We present MAMBA, an integrated measurement architecture for model-based analysis---both static and dynamic---of software systems, that can be specified by arbitrary Ecore-based modeling languages. MAMBA extends the Structured Metrics Meta-Model (SMM) by additional modeling features, such as arbitrary statistical aggregate functions and periodic aggregate functions, e.g., for dynamic analysis at runtime. To consider measurements for querying system models, we outline the MAMBA Query Language (MQL) that employs SMM measures. Furthermore, we provide tool support that applies the measures specified in an (extended) SMM model and can integrate raw measurements provided by arbitrary static and dynamic analysis tools to produce the desired measurement model. We demonstrate the applicability of the approach based on three evaluation scenarios from different contexts: migration of software systems into the cloud, model-based engineering of railway control systems, and dynamic analysis for model-driven software modernization

Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

Many SaaS providers nowadays want to leverage the cloud's capabilities also for their existing applications, for example, to enable sound scalability and cost-effectiveness. This thesis provides the approach CloudMIG that supports SaaS providers to migrate those applications to IaaS and PaaS-based cloud environments. CloudMIG consists of a step-by-step process and focuses on two core components. (1) Restrictions imposed by specific cloud environments (so-called cloud environment constraints (CECs)), such as a limited file system access or forbidden method calls, can be validated by an automatic conformance checking approach. (2) A cloud deployment option (CDO) determines which cloud environment, cloud resource types, deployment architecture, and runtime reconfiguration rules for exploiting a cloud's elasticity should be used. The implied performance and costs can differ in orders of magnitude. CDOs can be automatically optimized with the help of our simulation-based genetic algorithm CDOXplorer. Extensive lab experiments and an experiment in an industrial context show CloudMIG's applicability and the excellent performance of its two core components

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen