Spoon: A Library for Implementing Analyses and Transformations of Java Source Code

update for oadoi on Nov 02 2018International audienceThis paper presents SPOON, a library for the analysis and transformation of Java source code. SPOON enables Java developers to write a large range of domain-specific analyses and transformations in an easy and concise manner. SPOON analyses and transformations are written in plain Java. With SPOON, developers do not need to dive into parsing, to hack a compiler infrastructure, or to master a new formalism

Efficient execution of ATL model transformations using static analysis and parallelism

Although model transformations are considered to be the heart and soul of Model Driven Engineering (MDE), there are still several challenges that need to be addressed to unleash their full potential in industrial settings. Among other shortcomings, their performance and scalability remain unsatisfactory for dealing with large models, making their wide adoption difficult in practice. This paper presents A2L, a compiler for the parallel execution of ATL model transformations, which produces efficient code that can use existing multicore computer architectures, and applies effective optimizations at the transformation level using static analysis. We have evaluated its performance in both sequential and multi-threaded modes obtaining significant speedups with respect to current ATL implementations. In particular, we obtain speedups between 2.32x and 38.28x for the A2L sequential version, and between 2.40x and 245.83x when A2L is executed in parallel, with expected average speedups of 8.59x and 22.42x, respectively.Spanish Research Projects PGC2018-094905-B-I00, TIN2015-73968-JIN (AEI/FEDER/UE), Ramón y Cajal 2017 research grant, TIN2016-75944-R. Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, and by the FWF under the Grant Numbers P28519-N31 and P30525-N31

Project-Team RMoD (Analyses and Language Constructs for Object-Oriented Application Evolution) 2009 Activity Report

This is the yearly report of the RMOD team. A good way to understand what we are doing

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Adaptation-Aware Architecture Modeling and Analysis of Energy Efficiency for Software Systems

This thesis presents an approach for the design time analysis of energy efficiency for static and self-adaptive software systems. The quality characteristics of a software system, such as performance and operating costs, strongly depend upon its architecture. Software architecture is a high-level view on software artifacts that reflects essential quality characteristics of a system under design. Design decisions made on an architectural level have a decisive impact on the quality of a system. Revising architectural design decisions late into development requires significant effort. Architectural analyses allow software architects to reason about the impact of design decisions on quality, based on an architectural description of the system. An essential quality goal is the reduction of cost while maintaining other quality goals. Power consumption accounts for a significant part of the Total Cost of Ownership (TCO) of data centers. In 2010, data centers contributed 1.3% of the world-wide power consumption. However, reasoning on the energy efficiency of software systems is excluded from the systematic analysis of software architectures at design time. Energy efficiency can only be evaluated once the system is deployed and operational. One approach to reduce power consumption or cost is the introduction of self-adaptivity to a software system. Self-adaptive software systems execute adaptations to provision costly resources dependent on user load. The execution of reconfigurations can increase energy efficiency and reduce cost. If performed improperly, however, the additional resources required to execute a reconfiguration may exceed their positive effect. Existing architecture-level energy analysis approaches offer limited accuracy or only consider a limited set of system features, e.g., the used communication style. Predictive approaches from the embedded systems and Cloud Computing domain operate on an abstraction that is not suited for architectural analysis. The execution of adaptations can consume additional resources. The additional consumption can reduce performance and energy efficiency. Design time quality analyses for self-adaptive software systems ignore this transient effect of adaptations. This thesis makes the following contributions to enable the systematic consideration of energy efficiency in the architectural design of self-adaptive software systems: First, it presents a modeling language that captures power consumption characteristics on an architectural abstraction level. Second, it introduces an energy efficiency analysis approach that uses instances of our power consumption modeling language in combination with existing performance analyses for architecture models. The developed analysis supports reasoning on energy efficiency for static and self-adaptive software systems. Third, to ease the specification of power consumption characteristics, we provide a method for extracting power models for server environments. The method encompasses an automated profiling of servers based on a set of restrictions defined by the user. A model training framework extracts a set of power models specified in our modeling language from the resulting profile. The method ranks the trained power models based on their predicted accuracy. Lastly, this thesis introduces a systematic modeling and analysis approach for considering transient effects in design time quality analyses. The approach explicitly models inter-dependencies between reconfigurations, performance and power consumption. We provide a formalization of the execution semantics of the model. Additionally, we discuss how our approach can be integrated with existing quality analyses of self-adaptive software systems. We validated the accuracy, applicability, and appropriateness of our approach in a variety of case studies. The first two case studies investigated the accuracy and appropriateness of our modeling and analysis approach. The first study evaluated the impact of design decisions on the energy efficiency of a media hosting application. The energy consumption predictions achieved an absolute error lower than 5.5% across different user loads. Our approach predicted the relative impact of the design decision on energy efficiency with an error of less than 18.94%. The second case study used two variants of the Spring-based community case study system PetClinic. The case study complements the accuracy and appropriateness evaluation of our modeling and analysis approach. We were able to predict the energy consumption of both variants with an absolute error of no more than 2.38%. In contrast to the first case study, we derived all models automatically, using our power model extraction framework, as well as an extraction framework for performance models. The third case study applied our model-based prediction to evaluate the effect of different self-adaptation algorithms on energy efficiency. It involved scientific workloads executed in a virtualized environment. Our approach predicted the energy consumption with an error below 7.1%, even though we used coarse grained measurement data of low accuracy to train the input models. The fourth case study evaluated the appropriateness and accuracy of the automated model extraction method using a set of Big Data and enterprise workloads. Our method produced power models with prediction errors below 5.9%. A secondary study evaluated the accuracy of extracted power models for different Virtual Machine (VM) migration scenarios. The results of the fifth case study showed that our approach for modeling transient effects improved the prediction accuracy for a horizontally scaling application. Leveraging the improved accuracy, we were able to identify design deficiencies of the application that otherwise would have remained unnoticed

Project-Team RMoD (Analyses and Language Constructs for Object-Oriented Application Evolution) 2011 Activity Report

This is the yearly report of the RMOD team (http://rmod.lille.inria.fr/). A good way to understand what we are doing

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering, FASE 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 23 full papers, 1 tool paper and 6 testing competition papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers cover topics such as requirements engineering, software architectures, specification, software quality, validation, verification of functional and non-functional properties, model-driven development and model transformation, software processes, security and software evolution

Software engineering perspectives on physiological computing

Physiological computing is an interesting and promising concept to widen the communication channel between the (human) users and computers, thus allowing an increase of software systems' contextual awareness and rendering software systems smarter than they are today. Using physiological inputs in pervasive computing systems allows re-balancing the information asymmetry between the human user and the computer system: while pervasive computing systems are well able to flood the user with information and sensory input (such as sounds, lights, and visual animations), users only have a very narrow input channel to computing systems; most of the time, restricted to keyboards, mouse, touchscreens, accelerometers and GPS receivers (through smartphone usage, e.g.). Interestingly, this information asymmetry often forces the user to subdue to the quirks of the computing system to achieve his goals -- for example, users may have to provide information the software system demands through a narrow, time-consuming input mode that the system could sense implicitly from the human body. Physiological computing is a way to circumvent these limitations; however, systematic means for developing and moulding physiological computing applications into software are still unknown. This thesis proposes a methodological approach to the creation of physiological computing applications that makes use of component-based software engineering. Components help imposing a clear structure on software systems in general, and can thus be used for physiological computing systems as well. As an additional bonus, using components allow physiological computing systems to leverage reconfigurations as a means to control and adapt their own behaviours. This adaptation can be used to adjust the behaviour both to the human and to the available computing environment in terms of resources and available devices - an activity that is crucial for complex physiological computing systems. With the help of components and reconfigurations, it is possible to structure the functionality of physiological computing applications in a way that makes them manageable and extensible, thus allowing a stepwise and systematic extension of a system's intelligence. Using reconfigurations entails a larger issue, however. Understanding and fully capturing the behaviour of a system under reconfiguration is challenging, as the system may change its structure in ways that are difficult to fully predict. Therefore, this thesis also introduces a means for formal verification of reconfigurations based on assume-guarantee contracts. With the proposed assume-guarantee contract framework, it is possible to prove that a given system design (including component behaviours and reconfiguration specifications) is satisfying real-time properties expressed as assume-guarantee contracts using a variant of real-time linear temporal logic introduced in this thesis - metric interval temporal logic for reconfigurable systems. Finally, this thesis embeds both the practical approach to the realisation of physiological computing systems and formal verification of reconfigurations into Scrum, a modern and agile software development methodology. The surrounding methodological approach is intended to provide a frame for the systematic development of physiological computing systems from first psychological findings to a working software system with both satisfactory functionality and software quality aspects. By integrating practical and theoretical aspects of software engineering into a self-contained development methodology, this thesis proposes a roadmap and guidelines for the creation of new physiological computing applications.Physiologisches Rechnen ist ein interessantes und vielversprechendes Konzept zur Erweiterung des Kommunikationskanals zwischen (menschlichen) Nutzern und Rechnern, und dadurch die Berücksichtigung des Nutzerkontexts in Software-Systemen zu verbessern und damit Software-Systeme intelligenter zu gestalten, als sie es heute sind. Physiologische Eingangssignale in ubiquitären Rechensystemen zu verwenden, ermöglicht eine Neujustierung der Informationsasymmetrie, die heute zwischen Menschen und Rechensystemen existiert: Während ubiquitäre Rechensysteme sehr wohl in der Lage sind, den Menschen mit Informationen und sensorischen Reizen zu überfluten (z.B. durch Töne, Licht und visuelle Animationen), hat der Mensch nur sehr begrenzte Einflussmöglichkeiten zu Rechensystemen. Meistens stehen nur Tastaturen, die Maus, berührungsempfindliche Bildschirme, Beschleunigungsmesser und GPS-Empfänger (zum Beispiel durch Mobiltelefone oder digitale Assistenten) zur Verfügung. Diese Informationsasymmetrie zwingt die Benutzer zur Unterwerfung unter die Usancen der Rechensysteme, um ihre Ziele zu erreichen - zum Beispiel müssen Nutzer Daten manuell eingeben, die auch aus Sensordaten des menschlichen Körpers auf unauffällige weise erhoben werden können. Physiologisches Rechnen ist eine Möglichkeit, diese Beschränkung zu umgehen. Allerdings fehlt eine systematische Methodik für die Entwicklung physiologischer Rechensysteme bis zu fertiger Software. Diese Dissertation präsentiert einen methodischen Ansatz zur Entwicklung physiologischer Rechenanwendungen, der auf der komponentenbasierten Softwareentwicklung aufbaut. Der komponentenbasierte Ansatz hilft im Allgemeinen dabei, eine klare Architektur des Software-Systems zu definieren, und kann deshalb auch für physiologische Rechensysteme angewendet werden. Als zusätzlichen Vorteil erlaubt die Komponentenorientierung in physiologischen Rechensystemen, Rekonfigurationen als Mittel zur Kontrolle und Anpassung des Verhaltens von physiologischen Rechensystemen zu verwenden. Diese Adaptionstechnik kann genutzt werden um das Verhalten von physiologischen Rechensystemen an den Benutzer anzupassen, sowie an die verfügbare Recheninfrastruktur im Sinne von Systemressourcen und Geräten - eine Maßnahme, die in komplexen physiologischen Rechensystemen entscheidend ist. Mit Hilfe der Komponentenorientierung und von Rekonfigurationen wird es möglich, die Funktionalität von physiologischen Rechensystemen so zu strukturieren, dass das System wartbar und erweiterbar bleibt. Dadurch wird eine schrittweise und systematische Erweiterung der Funktionalität des Systems möglich. Die Verwendung von Rekonfigurationen birgt allerdings Probleme. Das Systemverhalten eines Software-Systems, das Rekonfigurationen unterworfen ist zu verstehen und vollständig einzufangen ist herausfordernd, da das System seine Struktur auf schwer vorhersehbare Weise verändern kann. Aus diesem Grund führt diese Arbeit eine Methode zur formalen Verifikation von Rekonfigurationen auf Grundlage von Annahme-Zusicherungs-Verträgen ein. Mit dem vorgeschlagenen Annahme-Zusicherungs-Vertragssystem ist es möglich zu beweisen, dass ein gegebener Systementwurf (mitsamt Komponentenverhalten und Spezifikation des Rekonfigurationsverhaltens) eine als Annahme-Zusicherungs-Vertrag spezifizierte Echtzeiteigenschaft erfüllt. Für die Spezifikation von Echtzeiteigenschaften kann eine Variante von linearer Temporallogik für Echtzeit verwendet werden, die in dieser Arbeit eingeführt wird: Die metrische Intervall-Temporallogik für rekonfigurierbare Systeme. Schließlich wird in dieser Arbeit sowohl ein praktischer Ansatz zur Realisierung von physiologischen Rechensystemen als auch die formale Verifikation von Rekonfigurationen in Scrum eingebettet, einer modernen und agilen Softwareentwicklungsmethodik. Der methodische Ansatz bietet einen Rahmen für die systematische Entwicklung physiologischer Rechensysteme von Erkenntnissen zur menschlichen Physiologie hin zu funktionierenden physiologischen Softwaresystemen mit zufriedenstellenden funktionalen und qualitativen Eigenschaften. Durch die Integration sowohl von praktischen wie auch theoretischen Aspekten der Softwaretechnik in eine vollständige Entwicklungsmethodik bietet diese Arbeit einen Fahrplan und Richtlinien für die Erstellung neuer physiologischer Rechenanwendungen