Software Engineering & Management 2015

239

Software-Engineering & Management 2015

Uwe Aßmann, Birgit Demuth, Thorsten Spitta, Georg Püschel, Ronny Kaiser (Hrsg.)

Software Engineering &

Management 2015

17.-20. März 2015 Dresden

Proceedings

This volume contains the contributions of the Software Engineering (SE) &

Management (SWM) 2015 conference held from March 17th to March 20th 2015 in Dresden, Germany. The SE proceedings part contains entries from the scientific program, the technology transfer program, the software &

systems engineering essentials, the doctoral symposium, as well as entries from workshops, tutorials, and software engineering ideas. The SWM 2015 is focused on requirements engineering & test management and provides

GI-Edition

Lecture Notes in Informatics

Gesellschaft für Informatik e.V. (GI)

publishes this series in order to make available to a broad public recent findings in informatics (i.e. computer science and informa- tion systems), to document conferences that are organized in co- operation with GI and to publish the annual GI Award dissertation.

Broken down into

• seminars

• proceedings

• dissertations

• thematics

current topics are dealt with from the vantage point of research and development, teaching and further training in theory and practice.

The Editorial Committee uses an intensive review process in order to ensure high quality contributions.

The volumes are published in German or English.

Information: http://www.gi.de/service/publikationen/lni/

ISSN 1617-5468

ISBN 978-3-88579-633-6

Uwe Aßmann, Birgit Demuth, Thorsten Spitta, Georg Püschel, Ronny Kaiser (Hrsg.)

Software Engineering & Management 2015

Multikonferenz der GI-Fachbereiche Softwaretechnik (SWT) und

Wirtschaftsinformatik (WI), FA WI-MAW 17. März – 20. März 2015

in Dresden

Gesellschaft für Informatik e.V. (GI)

Lecture Notes in Informatics (LNI) - Proceedings Series of the Gesellschaft für Informatik (GI) Volume P-239

ISBN 978-3-88579-633-6 ISSN 1617-5468

Volume Editors

Prof. Dr. Uwe Aßmann, Dr.-Ing. Birgit Demuth,

Dipl.-Inf. Georg Püschel, Dipl.-Medieninf. Ronny Kaiser

Fak. für Informatik, Technische Universität Dresden, Germany Email: uwe.assmann@tu-dresden.de, birgit.demuth@tu-dresden.de,

georg.pueschel1@tu-dresden.de, ronny.kaiser@tu-dresden.de Prof. em. Dr.-Ing. Thorsten Spitta, Angewandte Informatik /Wirtschaftsinformatik

Fak. für Wirtschaftswissenschaften, Universität Bielefeld, Germany E-Mail: thSpitta@wiwi.uni-bielefeld.de

Series Editorial Board

Heinrich C. Mayr, Alpen-Adria-Universität Klagenfurt, Austria (Chairman, mayr@ifit.uni-klu.ac.at)

Dieter Fellner, Technische Universität Darmstadt, Germany Ulrich Flegel, Hochschule für Technik, Stuttgart, Germany Ulrich Frank, Universität Duisburg-Essen, Germany

Johann-Christoph Freytag, Humboldt-Universität zu Berlin, Germany Michael Goedicke, Universität Duisburg-Essen, Germany

Ralf Hofestädt, Universität Bielefeld, Germany

Michael Koch, Universität der Bundeswehr München, Germany Axel Lehmann, Universität der Bundeswehr München, Germany Peter Sanders, Karlsruher Institut für Technologie (KIT), Germany Sigrid Schubert, Universität Siegen, Germany

Ingo Timm, Universität Trier, Germany

Karin Vosseberg, Hochschule Bremerhaven, Germany Maria Wimmer, Universität Koblenz-Landau, Germany Dissertations

Steffen Hölldobler, Technische Universität Dresden, Germany Seminars

Reinhard Wilhelm, Universität des Saarlandes, Germany Thematics

Andreas Oberweis, Karlsruher Institut für Technologie (KIT), Germany

” Gesellschaft für Informatik, Bonn 2015 printed by Köllen Druck+Verlag GmbH, Bonn

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Inhaltsverzeichnis

Software Engineering

Wissenschaftliches Programm

Modeling 1

Lars Hamann, Martin Gogolla

Endogene Metamodellierung der Semantik von neueren UML 2 Sprachmitteln... 31 Samuel Kounev, Fabian Brosig, Nikolaus Huber

The Descartes Modeling Language for Self-Aware Performance and Resource Ma- nagement... 33 Harald St¨orrle

On the Impact of Layout Quality to Understanding UML Diagrams: Not Just Pretty Pictures... 35 Grischa Liebel, Nadja Marko, Matthias Tichy, Andrea Leitner, J¨orgen Hansson Industrielle Praxis modellbasierter Entwicklung im Bereich eingebetteter Systeme... 37

Programming Languages and Type Systems

Tihomir Gvero, Viktor Kuncak, Ivan Kuraj, Ruzica Piskac

InSynth: A System for Code Completion using Types and Weights... 39 Heather Miller, Philipp Haller

A Type-Based Foundation for Closure-Passing in the Age of Concurrency and Dis- tribution... 41 Zvonimir Pavlinovic, Tim King, Thomas Wies

Finding Minimum Type Error Sources... 43 Luminous Fennell, Peter Thiemann

Gradual Typing for Annotated Type Systems... 45

Static Analysis

Michael Pressler, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel Fast Software Performance Evaluation for Embedded Hardware in Component- based Embedded Systems... 47

Alexander von Rhein, Sven Apel

Strategies for Analyzing Configurable Systems... 49 Antonio Filieri, Corina P˘as˘areanu, Willem Visser, Jaco Geldenhuys

Statistical Symbolic Execution with Informed Sampling... 51 Ren´e Just, Michael D. Ernst, Gordon Fraser

Mutation Analysis for the Real World: Effectiveness, Efficiency, and Proper Tool Support... 53

Modeling 2 - Modeling and Software Product Lines

Mahdi Derakhshanmanesh, J ¨urgen Ebert, Thomas Iguchi, Gregor Engels

Model-Integrating Software Components... 55 Thomas Th ¨um, Sven Apel, Christian K¨astner, Ina Schaefer, Gunter Saake

Analysis Strategies for Software Product Lines: A Classification and Survey... 57 Clemens Dubslaff

Advances in Quantitative Software Product Line Analysis... 59 Matthias Kowal, Ina Schaefer, Mirco Tribastone

Family-Based Performance Analysis of Variant-Rich Software Systems... 61

Comprehension

Janet Siegmund, Sven Apel, Christian K¨astner, Chris Parnin, Anja Bethmann, Gunter Saake, Thomas Leich, Andr´e Brechmann

Measuring Program Comprehension with Functional Magnetic Resonance Imaging... 63 Walid Maalej, Rebecca Tiarks, Tobias R¨ohm, Rainer Koschke

On the Comprehension of Program Comprehension... 65 Franz Zieris, Lutz Prechelt

On Knowledge Transfer Skill in Pair Programming... 67 Sebastian Baltes, Stephan Diehl

Sketches and Diagrams in Practice... 69

Verification

Stephan Arlt, Sergio Feo Arenis, Andreas Podelski, Martin Wehrle

System Testing and Program Verification... 71 Dirk Beyer, Stefan L¨owe

Interpolation for Value Analysis... 73

Dennis Felsing, Sarah Grebing, Vladimir Klebanov, Philipp R ¨ummer, Mattias Ulbrich

Automating Regression Verification... 75 Ren´e Just, Michael D. Ernst, Suzanne Millstein

Collaborative Verification of Information Flow for a High-Assurance App Store... 77

Modeling 3 - Variability

Tanja Mayerhofer, Philip Langer, Gerti Kappel

Semantic Model Differencing Based on Execution Traces... 78 Thorsten Berger, Sarah Nadi

Variability Models in Large-Scale Systems: A Study and a Reverse-Engineering Technique... 80 Sandro Schulze, Ina Schaefer

Refactoring Delta-Oriented Software Product Lines... 82

Evolution

Stefan G¨artner, Thomas Ruhroth, Jens B ¨urger, Kurt Schneider, Jan J ¨urjens Towards Maintaining Long-Living Information Systems by Incorporating Security Knowledge... 83 Ingo Scholtes, Marcelo Serrano Zanetti, Claudio Juan Tessone, Frank Schweitzer Automated Software Remodularization Based on Move Refactoring - A Complex Systems Approach... 85 Johannes Neubauer

Higher-Order Process Engineering in the context of Active Continuous Quality Con- trol... 87

Synthesis

Boris Duedder, Moritz Martens, Jakob Rehof

Staged Composition Synthesis... 89 Joel Greenyer, Christian Brenner, Maxime Cordy, Patrick Heymans, Erika Gressi

Incrementally Synthesizing Controllers from Scenario-Based Product Line Specifi- cations... 91 Sebastian Erdweg, Tijs van der Storm, Yi Dai

Capture-Avoiding Program Transformations with name-fix... 93

Modeling 4 - Model Transformations

Anthony Anjorin, Karsten Saller, Malte Lochau, Andy Sch ¨urr

On Modularizing Triple Graph Grammars with Rule Refinement... 95 Daniel Str ¨uber, Gabriele Taentzer

Starting Model Development in Distributed Teams with Incremental Model Splitting . 97 Christian Krause, Matthias Tichy, Holger Giese

Implementing Graph Transformations in the Bulk Synchronous Parallel Model... 99 Alexander Bergmayr, Michael Grossniklaus, Manuel Wimmer, Gerti Kappel UML Profile Generation for Annotation-based Modeling... 101

Testing 1

Kim Herzig, Sascha Just, Andreas Zeller

It’s Not a Bug, It’s a Feature: How Misclassification Impacts Bug Prediction... 103 Kim Herzig, Nachiappan Nagappan

The Impact of Test Ownership and Team Structure on the Reliability, Effectiveness of Quality Test Runs... 105 Michael Pradel, Markus Huggler, Thomas Gross

Performance Regression Testing of Concurrent Classes... 107 Michael Felderer, Armin Beer

Requirements-based testing with defect taxonomies... 108

Software Architecture and Specification

Shahar Maoz, Jan Oliver Ringert, Bernhard Rumpe

Verifying Component and Connector Models against Crosscutting Structural Views.... 110 Antonio Filieri, Henr Hoffmann, Martina Maggio

Automated Design of Self-Adaptive Software with Control-Theoretical Formal

Guarantees... 112 Klaus-Benedikt Schultis, Christoph Elsner, Daniel Lohmann

Architecture Challenges for Internal Software Ecosystems: A Large-Scale Industry Case Study... 114 Reinhard von Hanxleden, Bj¨orn Duderstadt, Insa Fuhrmann, Christian Motika, Steven Smyth, Michael Mendler, Joaqu ´n Aguado, Stephen Loftus-Mercer, Owen O’Brien

Sequential Constructiveness, SCCharts for Safety-Critical Applications... 116

Software Analytics

Anna Lanzaro, Roberto Natella, Stefan Winter, Domenico Cotroneo, Neeraj Suri

Error models for the representative injection of software defects... 118 Patrick Rempel, Patrick M¨ader, Tobias Kuschke, Jane Cleland-Huang

Traceability Gap Analysis for Assessing the Conformance of Software Traceability to Relevant Guidelines... 120 Dominik Renzel, Ralf Klamma, Matthias Jarke

Requirements Bazaar: Experiences, Added-Value and Acceptance of Requirements Negotiation between End-Users and Open Source Software Developers... 122 Walid Maalej, Swapneel Sheth

Us and Them: A Study of Privacy Requirements Across North America, Asia, and Europe... 124 Andreas Vogelsang, Steffen Fuhrmann

Why Feature Dependencies Challenge the Requirements Engineering of Automotive Systems: An Empirical Study... 125 Walter Binder, Yudi Zheng, Lubomir Bulej, Haiyang Sun, Petr Tuma

Comprehensive Multi-Platform Dynamic Program Analysis for the Java and Dalvik Virtual Machines... 127

Testing 2

Antonio Carzaniga, Alberto Goffi, Alessandra Gorla, Andrea Mattavelli, Nicol`o Perino, Mauro Pezz`e, Paolo Tonella

Intrinsic software redundancy for self-healing software systems, automated oracle generation... 129 Michael Pradel, Parker Schuh, George Necula, Koushik Sen

EventBreak: Analyzing the Responsiveness of User Interfaces through Performance- Guided Test Generation... 131 Andrea Arcuri, Gordon Fraser, Juan Pablo Galeotti

Automatische Erzeugung von Unit Tests f¨ur Klassen mit Umgebungs-Abh¨angigkeiten. 132 Kaituo Li, Christoph Reichenbach, Christoph Csallner, Yannis Smaragdakis Residual Investigation: Predictive and Precise Bug Detection... 133 Georg P ¨uschel, Christian Piechnick, Uwe Aßmann

Generative und simulative Softwaretests f¨ur selbst-adaptive, cyber-physikalische Systeme... 135

Marcel B¨ohme, Soumya Paul

Uber die Effizienz des Automatischen Testens¨ ... 136

Quality of Service

S¨oren Frey, Florian Fittkau, Wilhelm Hasselbring

Optimizing the Deployment of Software in the Cloud... 138 Emitza Guzman, Walid Maalej

Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews... 140 Jons-Tobias Wamhoff, Stephan Diestelhort, Christoph Fetzer, Patrick Marlier, Pascal Felber, Dave Dice

The TURBO Diaries: Application-controlled Frequency Scaling Explained... 141 Martin Franz, Andreas Holzer, Stefan Katzenbeisser, Christian Schallhart, Helmut Veith

Compilation for Secure Two-Party Computations... 143 Eric Schmieders, Andreas Metzger, Klaus Pohl

Ein Laufzeitmodel-basierter Ansatz zur Datenschutz-Pr¨ufung von Cloud-Systemen... 145 Irina Todoran, Norbert Seyff, Martin Glinz

How Do Cloud Providers Elicit Consumer Requirements?... 147

Software Engineering Ideas

Vorwort... 151 David Georg Reichelt, Johannes Schmidt

Performanzanalyse von Softwaresystemversionen: Methode und erste Ergebnisse... 153 Walter F. Tichy, Mathias Landh¨außer, Sven J. K¨orner

nlrpBENCH: A Benchmark for Natural Language Requirements Processing... 159 Andreas Kaufmann, Dirk Riehle

Improving Traceability of Requirements Through Qualitative Data Analysis... 165 Johannes Meißner, Frederik Schulz, Wilhelm Rossak

Analyse der sozialen Teamstruktur in Softwareprojekten... 171 Florian Lautenschlager, Andreas Kumlehn, Josef Adersberger, Michael Philippsen Rahmenwerk zur Ausreißererkennung in Zeitreihen von Software-Laufzeitdaten... 177 Wolfgang Golubski, Gerrit Beine

Der Software-Architekt und sein Unwissen... 183 Alexander Wachtel, Sebastian Weigelt, Philipp Voigt, Walter F. Tichy

Prototyp einer nat¨urlichsprachlichen Schnittstelle f¨ur Tabellenkalkulation... 189

Christian Klauß

Towards API Usability Engineering as a Software Engineering Paradigm... 195 Patrik Feth, Thomas Bauer, Thomas Kuhn

Virtual Validation of Cyber Physical Systems... 201

Software & Systems Engineering Essentials

Vorwort... 209 Margit Fries, Herbert Dietrich

Integration der Normen zur Funktionalen Sicherheit in ein organisationsspezifisch angepasstes V-Modell XT und die Projektpraxis... 211 Schlomo Schapiro

Test Driven Infrastructure... 215 Tobias Baum

Leveraging pre-commit hooks for context-sensitive checklists: a case study... 219 Edward Fischer

Kompakte Anforderungsverfolgung in Modellen - ein Praxisbericht... 223

Technologietransferprogramm

Vorwort zum Track Technologietransfer ... 229 Wolfgang B¨ohm, Maximilian Junker

Siemens Rail - Industrial Case Study: Model-based Development of a Train Guard MT Function... 231 Vincent Aravantinos, Kenji Miyamoto, Zaur Molotnikov, Nikolaus Regnat, Bernhard Sch¨atz

Textual model-based software/system architecture documentation using MPS... 232 Michael Felderer, Armin Beer

Mutual knowledge transfer between industry and academia to improve testing with defect taxonomies... 238 Timm Bußhaus, Stefan Fischer, Franziska K ¨uhn, Martin Leucker, Alexander Mildner, Malte Schmitz

Vom Forschungsprototypen zur industriellen Nutzung einer qualit¨atsgesicherten me- dizinischen Softwarekomponente - Technologietransfer im CMSSE... 243 Eugen Reiswich, Heinz Z ¨ullighoven

GeneAL - von einer Leitstandarchitektur zu innovativen Interaktionsformen... 249

Benjamin Nagel, Klaus Schr¨oder, Steffen Becker, Stefan Sauer, Gregor Engels Kooperative Methoden- und Werkzeugentwicklung zur Cloudmigration von propriet¨aren Anwendungskomponenten... 255

Startup-Programm

August-Wilhelm Scheer

Keynote: Tipps f¨ur Start-ups in der Industrie 4.0... 263 Michael W ¨urtenberger

Keynote: Changing Automotive Industrie... 264

Workshops

Robert Heinrich, Reiner Jung, Marco Konersmann, Eric Schmieders

2nd Collaborative Workshop on Evolution and Maintenance of Long-Living Systems (EML)... 267 Alexander Schlaefer, Sibylle Schupp

Fail Safety in Medical Cyber-Physical Systems (FS-MCPS)... 268 Clemens Grelck, Baltasar Tranc´on Widemann

8. Arbeitstagung Programmiersprachen (ATPS 2015)... 269 Ottmar Bender, Wolfgang B¨ohm, Frank Houdek, Stefan Henkler, Andreas Vogelsang, Thorsten Weyer

F¨unfter Workshop zur Zukunft der Entwicklung softwareintensiver eingebetteter Sys- teme (ENVISION2020)... 271 Ronald Scholz, Lars Martin

Eclipse Internet of Things (Eclipse IoT)... 273

Tutorien

Antonio Barresi, Mathias Payer, Thomas Gross

Control-Flow Integrity... 277 Markku Lammerz, Dennis Michielse

C# durch die Brille des Software-Entwicklers... 278 Harry Sneed

Migrating to a Service-Oriented Architecture... 279 Stefan Oehm, Moritz Eysholdt

Xtext - Werkzeugunterst¨utzung f¨ur bestehende sowie eigene Sprachen einfach

entwickeln... 280

Doktorandensymposium

Vorwort... 285 Felix Willnecker

Optimization of Component Allocations in Middleware Platforms using Performance Models... 287 Axel Busch

Automated Decision Support for Recurring Design Decisions Considering Non- Functional Requirements... 291 Mustafa Al-Hajjaji

Scalable Sampling and Prioritization for Product-Line Testing... 295 Oliver Norkus

Ein Ansatz zur Standardisierung von Business Intelligence in der Cloud... 299

Software Management

Andreas Spillner

Keynote: Pair - Requirements Engineering... 305

Wissenschaftliches Programm

Requirements

Ursula Schmitt-Wagner, Alexander van der Vekens

Evolution¨are Entwicklung einer Web-Anwendung im kirchlichen Umfeld... 307 Jens Nerche

Ausf¨uhrbare Spezifikationen im Projektalltag — Ein Erfahrungsbericht... 319 Roman Roelofsen, Stephan Wilczek

Markup-basiertes Spezifikations- und Anforderungsmanagement in agilen Softwa- reprojekten... 334

Test

Jan D ¨uttmann, Stephan Kleuker

Gegenseitige Beeinflussungen von Testautomatisierung, Testmanagement und Ent- wicklung... 346 Anne G¨othlich, Karin Eisenbl¨atter, Michael Kroll, Johannes Schad, Heike Vocke Ein generativer Ansatz f¨ur den automatisierten Software-Test... 362

Maximilian Azimi, Jens-Rainer Felske, Sebastian Lauber, Jan-Henrich Mattfeld, Pascal Schneider, Krischan Stapelfeldt, Timm Suhl, Nils Techau, Karin Vosseberg Testautomatisierung Gute Qualit¨at f¨allt nicht vom Himmel... 378

Qualit¨atssicherung

Harry M. Sneed

Aufwandssch¨atzung der Softwarewartung und -evolution... 386 Thomas Wolfenstetter, Jonas Zitzelsberger, Markus B¨ohm, Helmut Krcmar

Traceability von Anforderungen und Tests in agilen Softwareentwicklungsprojekten.... 403 Jens Nerche

Erfahrungsbericht Datenbankbasierte Metrikverarbeitung f¨ur Clean Code Develop- ment in Brownfieldprojekten... 419

IT-Management in Hochschulen

Meik Teßmer

Literate Programming zur Dokumentation in der Systemadministration... 433 Gunnar Auth

Prozessorientierte Anforderungsanalyse f¨ur die Einf¨uhrung integrierter Campus- Management-Systeme... 446 Ivonne Erfurth, Christian Erfurth

Requirements Engineering aus Sicht von Hochschulrechenzentren – Analyse und Entwurf von IT-Diensten an Hochschulen... 462 Ronny Kaiser, Georg P ¨uschel, Sebastian G¨otz, Katrin Kahle, Uwe Aßmann

Von der Software-Dissertation zum Lean Startup... 470

Tutorials

Harry M. Sneed

Test-Driven Requirements Management... 484 Jens Nerche

Ausf¨uhrbare Spezifikationen mit der Language Workbench MPS... 485

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Wissenschaftliches Programm

Endogene Metamodellierung der Semantik von neueren UML 2 Sprachmitteln

Lars Hamann AG Datenbanksysteme

Universität Bremen lhamann@tzi.de

Martin Gogolla AG Datenbanksysteme

Universität Bremen gogolla@tzi.de

Abstract:Seit dem Aufkommen der Unified Modeling Language (UML) wurden un- terschiedliche Ansätze vorgestellt diese formal zu spezifizieren. Eine wohldefinierte formale Semantik der UML führt unter anderem zu einer höheren Interoperabilität zwischen verschiedenen Modellierungswerkzeugen, da Intepretationsspielräume ver- ringert werden. Die hier zusammengefasste Arbeit beschreibt einen endogenen Ansatz zur Metamodellierung der Semantik von zentralen UML Elementen.

Eine wohldefinierte formale Semantik der UML führt zum einen zu einer verbesserten Austauschbarkeit von Werkzeugen, was die Flexibilität eines modellgetriebenen Entwick- lungsprozesses erhöht, zum anderen können Werkzeugketten aufgebaut werden, die ver- schiedene spezialisierte Werkzeuge, z. B. für Modell-zu-Modell- und Modell-zu-Text- Transformationen, verwenden. Die Semantik von zentralen Konzepten der UML, wie Klas- sen, Assoziationen und Generalisierung, wurden z. B. mit mengentheoretischen oder graph- basierten Methoden definiert. Diesen Ansätzen ist gemein, dass sie den Sprachraum der UML verlassen und somit zusätzliche (formale) Beschreibungsmittel benötigen.

Die in hier vorgestellte Arbeit [HG13] stellt einen endogenen, werkzeuggestützten An- satz vor, der die Laufzeitsemantik der UML ausschließlich mit den Mitteln der im UML- Kontext bekannten Sprachmitteln beschreibt. Der Ansatz basiert dabei auf den Grundlagen der endogenen Metamodellierung von Semantik aus [Kle09]. Dabei werden zwei Metamo- delle für eine Modellierungssprache definiert: das der abstrakten Syntax (Abstact Syntax Model- ASM) und das der Semantik (Semantic Domain Model- SDM). Das ASM defi- niert die gültigen Strukturen eines Modells der Sprache, während das SDM die Bedeutung dieser Strukturen festlegt. Bei einer endogenen Metamodellierung wird dabei die zu be- schreibende Sprache selbst für die Beschreibung verwendet.

Die Spezifikation der UML verwendet bereits einen endogenen Ansatz bestehend aus Klassendiagrammen und zusätzlichen Einschränkungen in OCL (Object Constraint La- nugage), um die abstrakte Syntax der Sprache (das ASM), zu definieren, klammert aber explizit die Definition der Laufzeitsemantik (das SDM) aus. Aus unserer Sicht bedarf es aber zumindest für zentrale Modellierungselemente einer wohl definierten Semantik. So wird z. B. für die Definition der abstrakten Syntax der UML die subsets-Beziehungen zwi- schen Assoziationsenden häufig verwendet. Die Bedeutung dieser Beziehung ist allerdings nur informell beschrieben. Intuitiv lässt sich die Bedeutung dieser Beziehung am Beispiel aus Abb. 1 erläutern. Die Markierung des Assoziationsendesfrontals eine Teilmenge

Class diagram

Wheel Car

Vehicle part {union} VehiclePart

inVehicle {union} 1..*

1

front {subsets part}

2 inCarAsFront {subsets inVehicle}

1

Abbildung 1: Beispiel einer einfachen subsets-Beziehung

des Assoziationsendespartbesagt, dass die Vorderräder eines Autos zu der Gesamtmen- ge der Fahrzeugteile gehört. Die Auszeichnungunionam Assoziationsendepartwird häufig in Verbindung mit diesen Teilmengenbeziehungen verwendet, um zu festzulegen, dass die verbundenen Objekte sich ausschließlich aus den definierten Teilmengen erge- ben. Für komplexere Klassendiagramme, wie sie z. B. im UML-Metamodell vorkommen, die diese Beziehung über mehrere Vererbungsstufen verwenden, lassen sich die aus der Modellierung resultierenden Konsequenzen für das Laufzeitverhalten allerdings schwer ableiten. Ist zusätzlich zum ASM ein Modell der Semantik vorhanden, können diese Kon- sequenzen werkzeuggestützt untersucht werden, wie es in diesem Beitrag mit einem Mo- dellierungswerkzeug [USE] gezeigt wird.

Bei der Entwicklung des in [HG13] vorgestellten Auszugs eines SDM für die UML hat sich zusätzlich die Visualisierung von abgeleiteten Eigenschaften als hilfreich erwiesen, um das Laufzeitverhalten von Modellen besser verstehen zu können. Beispielsweise kön- nen die abgeleiteten Verbindungen aus einem als unionmarkierten Assoziationsende (siehe Abb. 1) direkt dem Benutzer angezeigt werden. Komplexere abgeleitete Eigenschaf- ten können in UML-Modellen mit Hilfe von OCL-Ausdrücken definiert werden. Dadurch können komplizierte Strukturen dem Anwender vereinfacht dargestellt werden und zusätz- lich durch die Vergabe eines Namens für die Eigenschaft mit einer Bedeutung versehen werden. Der hier beschriebene Konferenzbeitrag beschäftigt sich ausführlich mit den für eine automatische Auswertung zu berücksichtigenden Anforderungen, bis hin zur Aus- wertung von abgeleiteten Assoziationen mit mehr als zwei Assoziationsenden.

Literatur

[HG13] Lars Hamann und Martin Gogolla. Endogenous Metamodeling Semantics for Structural UML 2 Concepts. In Ana Moreira, Bernhard Schätz, Jeff Gray, Antonio Vallecillo und Peter J. Clarke, Hrsg.,Proceedings of 16th International Conference Model-Driven Engi- neering Languages and Systems (MODELS’2013), Miami, FL, USA, September 29 - Octo- ber 4, 2013., Seiten 488–504. Springer, Berlin, LNCS 8107, 2013.

[Kle09] Anneke Kleppe. Object Constraint Language: Metamodeling Semantics. In Kevin Lano, Hrsg.,UML 2 Semantics and Applications, Seiten 163–178. John Wiley & Sons, Inc., 2009.

[USE] A UML-based Specification Environment. http://sourceforge.net/projects/useocl/.

The Descartes Modeling Language for

Self-Aware Performance and Resource Management

Samuel Kounev, Fabian Brosig, Nikolaus Huber Department of Computer Science, University of W¨urzburg

Am Hubland, 97074 W¨urzburg

{samuel.kounev,fabian.brosig,nikolaus.huber}@uni-wuerzburg.de Abstract:The Descartes Modeling Language (DML) is a novel architecture-level lan- guage for modeling performance and resource management related aspects of modern dynamic software systems and IT infrastructures. Technically, DML is comprised of several sub-languages, each of them specified using OMG’s Meta-Object Facil- ity (MOF) and referred to as meta-model in OMG’s terminology. The various sub- languages can be used both in offline and online settings for application scenarios like system sizing, capacity planning and trade-off analysis, as well as for self-aware resource management during operation.

Modern software systems have increasingly distributed architectures composed of loosely- coupled services that are typically deployed on virtualized infrastructures. Such system architectures provide increased flexibility by abstracting from the physical infrastructure, which can be leveraged to improve system efficiency. However, these benefits come at the cost of higher system complexity and dynamics. The inherent semantic gap between application-level metrics, on the one hand, and resource allocations at the physical and virtual layers, on the other hand, significantly increase the complexity of managing end- to-end application performance.

To address this challenge, techniques foronline performance predictionare needed. Such techniques should make it possible to continuously predict at runtime: a) changes in the application workloads [HHKA14], b) the effect of such changes on the system perfor- mance, and c) the expected impact of system adaptation actions [BHK14]. Online per- formance prediction can be leveraged to design systems thatproactivelyadapt to chang- ing operating conditions, thus enabling what we refer to asself-aware¹performance and resource management [KBH14, HvHK⁺14, KBHR10]. Existing approaches to perfor- mance and resource management in the research community are mostly based on coarse- grained performance models that typically abstract systems and applications at a high level, e.g., [JHJ⁺10, ZCS07, CAAS07]. Such models do not explicitly model the software architecture and execution environment, distinguishing performance-relevant behavior at the virtualization level vs. at the level of applications hosted inside the running VMs. Thus, their online prediction capabilities are limited and do not support complex scenarios such as, for example, predicting how changes in application workloads propagate through the

1Self-awareness is understood as adopted for Dagstuhl Seminar 15041(http://www.dagstuhl.de/15041)

layers and tiers of the system architecture down to the physical resource layer, or predict- ing the effect on the response times of different services, if a VM in a given application tier is to be replicated or migrated to another host, possibly of a different type.

To enable online performance prediction in scenarios such as the above, architecture- levelmodeling techniques are needed, specifically designed for use inonlinesettings. We present a new architecture-level language, called Descartes Modeling Language (DML)², which provides appropriate modeling abstractions to describe the resource landscape, the application architecture, the adaptation space, and the adaptation processes of a software system and its IT infrastructure [BHK14, HvHK⁺14]. We present an overview of the different constituent parts of DML and describe how they can be leveraged to enable on- line performance prediction and proactive model-based system adaptation. The complete DML specification is available as a technical report [KBH14]. A set of related tools and libraries are available from the DML website athttp://descartes.tools/dml.

Finally, we present some exemplary results from an industrial case study showing the ap- plicability of our approach in a real-life setting [HvHK⁺14].

References

[BHK14] F. Brosig, N. Huber, and S. Kounev. Architecture-Level Software Performance Ab- stractions for Online Performance Prediction.Elsevier Science of Computer Program- ming Journal (SciCo), Vol. 90, Part B:71–92, 2014.

[CAAS07] I. Cunha, J Almeida, V. Almeida, and M. Santos. Self-Adaptive Capacity Management for Multi-Tier Virtualized Environments. InIFIP/IEEE Int. Symposium on Integrated Network Management, pages 129–138, 2007.

[HHKA14] N. Herbst, N. Huber, S. Kounev, and E. Amrehn. Self-Adaptive Workload Classifica- tion and Forecasting for Proactive Resource Provisioning. Concurrency and Compu- tation - Practice and Experience, John Wiley and Sons, 26(12):2053–2078, 2014.

[HvHK⁺14] N. Huber, A. van Hoorn, A. Koziolek, F. Brosig, and S. Kounev. Modeling Run-Time Adaptation at the System Architecture Level in Dynamic Service-Oriented Environ- ments.Service Oriented Computing and Applications Journal, 8(1):73–89, 2014.

[JHJ⁺10] Gueyoung Jung, M.A. Hiltunen, K.R. Joshi, R.D. Schlichting, and C. Pu. Mistral:

Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infras- tructures. InIEEE Int. Conf. on Distributed Computing Systems, pages 62 –73, 2010.

[KBH14] S. Kounev, F. Brosig, and N. Huber. The Descartes Modeling Language. Technical report, Department of Computer Science, University of Wuerzburg, October 2014.

http://nbn-resolving.org/urn:nbn:de:bvb:20-opus-104887.

[KBHR10] S. Kounev, F. Brosig, N. Huber, and R. Reussner. Towards self-aware performance and resource management in modern service-oriented systems. In7th IEEE International Conference on Services Computing (SCC 2010), 2010.

[ZCS07] Qi Zhang, Ludmila Cherkasova, and Evgenia Smirni. A Regression-Based Analytic Model for Dynamic Resource Provisioning of Multi-Tier Applications. InProceedings of the 4th International Conference on Autonomic Computing, 2007.

2http://descartes.tools/dml

On the Impact of Layout Quality to Understanding of UML Diagrams: Not Just Pretty Pictures

Harald St¨orrle

Department of Applied Mathematics and Computer Science Technical University of Denmark

Matematiktorvet, 2800 Lyngby, Denmark hsto@dtu.dk

Abstract:In a string of empirical studies, we show that the layout of UML diagrams contributes significantly to understanding the underlying model. This effect extends over different factors such as diagram type & size, and expertise.

Status Quo The Unified Modeling Language (UML) has been called the “lingua franca of software engineering” for over a decade now. It is widely believed that, to a sizable degree, its popularity is rooted in the predominantly visual nature of UML models. The advantage of visual over textual notations is, generally speaking, that they support human perceptual and thought processes, making diagrams a more cognitively efficient medium than, say, prose.

Practical experience suggests that the usage and understanding of UML diagrams is greatly affected by the quality of their layout. While existing research failed to provide conclu- sive evidence in support of this hypothesis, our own work [St¨o11, St¨o12, St¨o14] provided substantial evidence to this effect.

Size Matters When analyzing the impact factors, we find that diagram size is an impor- tant factor to diagram understanding; this is consistent with previous findings [MRC07].

Other factors like expertise level are important, too, though to a lesser degree, and some factors appear to be irrelevant, such as diagram type. Since there was no adequate def- inition of this notion, we had to defined diagram size metrics first. It turns out that the most trivial notion of simply counting diagrammatic elements is highly correlated to more complex notions, an effect known from program size metrics. By Occams razor, thus, we conclude that the size of a diagram should be measured as the number of diagram elements (i.e., geometric shapes, annotations, and line segments).

Studying the impact of diagram size to diagram understanding by modelers, we find that there is a strong negative correlation between size and performance as well as preference.

Our results are statistically highly significant and far exceed earlier work in terms of va- lidity in several dimensions.

We utilize these results to derive recommendations on diagram sizes that are optimal for model understanding. More recent work has begun to uncover the cognitive mechanisms involved in the understanding of UML diagrams [Mai14, SBCM14].

Generalizations It is a common misunderstanding is to confuse or identify “model”

with “diagram”: themodelis the underlying data structure while thediagramis its visual representation. Our work refers exclusively to diagrams. From a visual languages point of view, there are only minor differences between the notations of many of the popular modeling languages, and diagram type does not seem to be an important factor of modeler understanding, anyway. Thus, our results are probably generalizable to BPMN, EPCs and so on. The substantial differences between such modeling languages on the conceptual, semantic, and pragmatic levels are largely irrelevant for the aspects studied in our work.

Next Steps We are currently working on two threads to continue this research. First, we are in the final stages of a systematic literature review on the field of UML diagram layout knowledge, so as to complement and frame our own findings in a scientifically reliable way. Second, we would like to increase the validity of our findings through independent replications. To this end, we are creating an online test implementing the experimental setup used in our work. It will allow anybody to administer, or individually participate in our experiment. Over time, we hope to acquire data from a large enough population so that we can find general averages. Thus, effectively, our experiment might evolve into a personal performance inventory not unlike existing IQ tests. This could be used as a diagnostic instrument, e.g., for self-assessment and as an experimental pre-testw.

References

[Mai14] Maier, Anja M. and Baltsen, Nick and Christoffersen, Henrik and St¨orrle, Harald. To- wards Diagram Understanding: A Pilot-Study Measuring Cognitive Workload Through Eye-Tracking. InProc. Intl. Conf. Human Behavior in Design, 2014.

[MRC07] Jan Mendling, Hajo A. Reijers, and Jorge Cardoso. What Makes Process Models Un- derstandable? In G. Alonso, Peter Dadam, and Michael Rosemann, editors,Proc. Intl.

Conf. Business Process Management (BPM), pages 48–63. Springer Verlag, 2007.

[SBCM14] Harald St¨orrle, Nick Baltsen, Henrik Christoffersen, and Anja M. Maier. On the Im- pact of Diagram Layout: How Are Models Actually Read? In S. Sauer, M. Wimmer, M. Genero, and S. Qadeer, editors,Joint Proc. MODELS 2014 Poster Session and ACM Student Research Competition, volume 1258, pages 31–35. CEUR, 2014.

[St¨o11] Harald St¨orrle. On the Impact of Layout Quality to Unterstanding UML Diagrams.

InProc. IEEE Symp. Visual Languages and Human-Centric Computing (VL/HCC’11), pages 135–142. IEEE Computer Society, 2011.

[St¨o12] Harald St¨orrle. On the Impact of Layout Quality to Unterstanding UML Diagrams: Di- agram Type and Expertise. In G. Costagliola, A. Ko, A. Cypher, J. Nichols, C. Scaffidi, C. Kelleher, and B. Myers, editors,Proc. IEEE Symp. Visual Languages and Human- Centric Computing (VL/HCC’12), pages 195–202. IEEE Computer Society, 2012.

[St¨o14] Harald St¨orrle. On the Impact of Layout Quality to Understanding UML Diagrams:

Size Matters. In J¨urgen Dingel, Wolfram Schulte, Isidro Ramos, and Emilio Abrahao, Silviaand Insfran, editors,Proc. 17th Intl. Conf. Model Driven Engineering Languages and Systems (MoDELS’14), number 8767 in LNCS, pages 518–534. Springer Verlag, 2014.

Industrielle Praxis modellbasierter Entwicklung im Bereich eingebetteter Systeme

Grischa Liebel¹, Nadja Marko², Matthias Tichy¹, Andrea Leitner², Jörgen Hansson³

1Software Engineering Division, Chalmers/University of Gothenburg, Sweden grischa@chalmers.se|matthias.tichy@cse.gu.se

2E/E und Software, Virtual Vehicle Research Center, Graz, Austria nadja.marko@v2c2.at|andrea.leitner@v2c2.at

3School of Informatics, University of Skövde, Sweden jorgen.hansson@his.se

Abstract: Modellbasierte Entwicklung (MBE) ist eine verbreitete Entwicklungsmethode, die die Produktentwicklung verbessern soll. Es existieren nur wenige empirische Untersuchungen in Bezug auf MBE für eingebettete Systeme. Daraus motiviert sich unsere Umfrage zur industriellen Praxis in diesem Bereich. Die Umfrage beinhaltete neben demographischen Fragen, auch Fragen zu den angewandten Sprachen und Werkzeugen, den Gründen für die Einführung von MBE, den positiven und negativen Auswirkungen, sowie Problemen bei der Nutzung.

1 Studienteilnehmer und Forschungsfragen

Die Studie umfasst 112 verwertbare Antworten, mehrheitlich von erfahrenen, industriellen Anwendern. Teilnehmer der Umfrage kommen hauptsächlich aus den Sparten Automobil, Luftfahrt, Gesundheitswesen, Verteidigung und Bahn und arbeiten mehrheitlich in Großunternehmen mit mehr als 250 Mitarbeitern. Unter den Befragten befinden sich unter anderem Softwareentwickler, Architekten, Tester, Designer, Anforderungsingenieure, Projekt Manager und Safety Manager, die MBE regelmäßig einsetzen. Forschungsfragen, die die Studie beantwortet, sind: Wie sieht die angewandte Praxis und Beurteilung von MBE bei eingebetteten Systemen aus?und Gibt es bei der Benutzung und Bewertung von MBE Unterschiede zwischen unterschiedlichen demographischen Subgruppen?

2 Industrielle Praxis und Beurteilung von MBE

Die Umfrage zeigt, dass die meistverwendeten Werkzeuge für MBE Matlab/Simulink und Eclipse-basierte Anwendungen sind. Zustandsmaschinen, Sequenzbasierte Modelle und Block-Modelle werden bei der Modellierung am häufigsten verwendet. Vorrangig werden die Modelle für Simulation, Code Generierung und zu Informations- und Dokumentationszwecken genutzt. Um die wahrgenommenen Vor- und Nachteile von MBE zu erfassen, befragten wir die Teilnehmer über die Einführungsgründe, positive