A History-based Approach for Model Repair Recommendations in Software Engineering

Software is an everyday companion in today’s technology society that need to be evolved and maintained over long time periods. To manage the complexity of software projects, it has always been an effort to increase the level of abstraction during software development. Model-Driven Engineering (MDE) has shown to be a suitable method to raise abstraction levels during software development. Models are primary development artifacts in MDE that describe complex software systems from different viewpoints. In MDE software projects, models are heavily edited through all stages of the development process. During this editing process, the models can become inconsistent due to uncertainties in the software design or various editing mistakes. While most inconsistencies can be tolerated temporarily, they need to be resolved eventually. The resolution of an inconsistency affecting a model’s design is typically a creative process that requires a developer’s expertise. Model repair recommendation tools can guide the developer through this process and propose a ranked list of repairs to resolve the inconsistency. However, such tools will only be accepted in practice if the list of recommendations is plausible and understandable to a developer. Current approaches mainly focus on exhaustive search strategies to generate improved versions of an inconsistent model. Such resolutions might not be understandable to developers, may not reflect the original intentions of an editing process, or just undo former work. Moreover, those tools typically resolve multiple inconsistencies at a time, which might lead to an incomprehensible composition of repair proposals. This thesis proposes a history-based approach for model repair recommendations. The approach focuses on the detection and complementation of incomplete edit steps, which can be located in the editing history of a model. Edit steps are defined by consistency-preserving edit operations (CPEOs), which formally capture complex and error-prone modifications of a specific modeling language. A recognized incomplete edit step can either be undone or extended to a full execution of a CPEO. The final inconsistency resolution depends on the developer’s approval. The proposed recommendation approach is fully implemented and supported by our interactive repair tool called ReVision. The tool also includes configuration support to generate CPEOs by a semi-automated process. The approach is evaluated using histories of real-world models obtained from popular open-source modeling projects hosted in the Eclipse Git repository. Our experimental results confirm our hypothesis that most of the inconsistencies, namely 93.4%, can be resolved by complementing incomplete edits. 92.6% of the generated repair proposals are relevant in the sense that their effect can be observed in the models’ histories. 94.9% of the relevant repair proposals are ranked at the topmost position. Our empirical results show that the presented history-based model recommendation approach allows developers to repair model inconsistencies efficiently and effectively.Software ist in unserer heutigen Gesellschaft ein alltäglicher Begleiter. Diese wird ständig weiterentwickelt und überarbeitet. Model-Driven Engineering (MDE) hat sich als geeignete Methode erwiesen, um bei der Entwicklung komplexer Software von technischen Details zu abstrahieren. Hierbei werden Modelle als primäre Entwicklungsartefakte verwendet, welche ein Softwaresystem aus verschiedenen Sichten beschreiben. Modelle in MDE werden in allen Entwicklungsphasen einer Software fortlaufend überarbeitet. Während der Bearbeitung können die Modelle aufgrund von Unklarheiten im Design oder verschiedenen Bearbeitungsfehlern inkonsistent werden. Auch wenn Inkonsistenzen vorübergehend toleriert werden können, so müssen diese letztlich doch behoben werden. Die Behebung einer Inkonsistenz, welche sich auf das Design eines Modells auswirkt, ist meist ein kreativer Prozess, der das Fachwissen eines Entwicklers erfordert. Empfehlungswerkzeuge können den Entwickler mit Reparaturvorschlägen unterstützen. Damit solche Werkzeuge in der Praxis akzeptiert werden, müssen die Vorschläge plausible und nachvollziehbar sein. Die meisten aktuelle Ansätze verwenden Suchstrategien, welche Reparaturen durch systematisches Ausprobieren generieren. Die so generierten Reparaturen sind für Entwickler häufig schwer nachvollziehbar, da sie vorhergehende Bearbeitungsschritte nicht beachten oder diese einfach rückgängig machen. Darüber hinaus lösen diese Reparaturwerkzeuge in der Regel mehrere Inkonsistenzen gleichzeitig, was zu unverständlichen und umfangreichen Reparaturen führen kann. Diese Arbeit beschreibt einen Ansatz zum Erkennen und Ergänzen unvollständiger Bearbeitungsschritte, basierend auf der Bearbeitungshistorie eines Modells. Dazu werden konsistenzerhaltende Bearbeitungsoperationen definiert, die komplexe und fehleranfällige Änderungen einer bestimmten Modellierungssprache formal erfassen. Ein unvollständiger Bearbeitungsschritt kann dann entweder rückgängig gemacht oder zu einer konsistenzerhaltenden Bearbeitungsoperationen erweitert werden. Die endgültige Reparatur der Inkonsistenz hängt von der Einschätzung des Entwicklers ab. Der vorgeschlagene Ansatz wurde in unserem interaktiven Reparaturwerkzeug ReVision implementiert. Darüber hinaus umfasst das Werkzeug Unterstützung zum Generieren von konsistenzerhaltenden Bearbeitungsoperationen. Das Reparaturverfahren wurde anhand von Historien realer Modelle aus bekannten Open-Source-Modellierungsprojekten im Eclipse-Git-Repository bewertet. Die experimentellen Ergebnisse bestätigen unsere Hypothese, dass die meisten Inkonsistenzen, nämlich 93.4%, durch Ergänzung unvollständiger Bearbeitungen gelöst werden können. 92.6% der generierten Reparaturvorschläge könnten in der entsprechenden Modellhistorie beobachtet werden. Von diesen Reparaturvorschläge wurden 94.9% an erster Stelle vorgeschlagen. Unsere empirischen Ergebnisse zeigen, dass der vorgestellte historienbasierte Modellempfehlungsansatz es Entwicklern ermöglicht, Modellinkonsistenzen effizient und effektiv zu reparieren

A graph-based aspect interference detection approach for UML-based aspect-oriented models

Aspect Oriented Modeling (AOM) techniques facilitate separate modeling of concerns and allow for a more flexible composition of these than traditional modeling technique. While this improves the understandability of each submodel, in order to reason about the behavior of the composed system and to detect conflicts among submodels, automated tool support is required. Current techniques for conflict detection among aspects generally have at least one of the following weaknesses. They require to manually model the abstract semantics for each system; or they derive the system semantics from code assuming one specific aspect-oriented language. Defining an extra semantics model for verification bears the risk of inconsistencies between the actual and the verified design; verifying only at implementation level hinders fixng errors in earlier phases. We propose a technique for fully automatic detection of conflicts between aspects at the model level; more specifically, our approach works on UML models with an extension for modeling pointcuts and advice. As back-end we use a graph-based model checker, for which we have defined an operational semantics of UML diagrams, pointcuts and advice. In order to simulate the system, we automatically derive a graph model from the diagrams. The result is another graph, which represents all possible program executions, and which can be verified against a declarative specification of invariants.\ud To demonstrate our approach, we discuss a UML-based AOM model of the "Crisis Management System" and a possible design and evolution scenario. The complexity of the system makes con°icts among composed aspects hard to detect: already in the case of two simulated aspects, the state space contains 623 di®erent states and 9 different execution paths. Nevertheless, in case the right pruning methods are used, the state-space only grows linearly with the number of aspects; therefore, the automatic analysis scales

Workshop proceedings of the 1st workshop on quality in modeling

Quality assessment and assurance constitute an important part of software engineering. The issues of software quality management are widely researched and approached from multiple perspectives and viewpoints. The introduction of a new paradigm in software development – namely Model Driven Development (MDD) and its variations (e.g., MDA [Model Driven Architecture], MDE [Model Driven Engineering], MBD [Model Based Development], MIC [Model Integrated Computing]) – raises new challenges in software quality management, and as such should be given a special attention. In particular, the issues of early quality assessment, based on models at a high abstraction level, and building (or customizing the existing) prediction models for software quality based on model metrics are of central importance for the software engineering community. The workshop is continuation of a series of workshops on consistency that have taken place during the subsequent annual UML conferences and recently MDA-FA. The idea behind this workshop is to extend the scope of interests and address a wide spectrum of problems related to MDD. It is also in line with the overall initiative of the shift from UML to MoDELS. The goal of this workshop is to gather researchers and practitioners interested in the emerging issues of quality in the context of MDD. The workshop is intended to provide a premier forum for discussions related to software quality and MDD. And the aims of the workshop are: - Presenting ongoing research related to quality in modeling in the context of MDD, - Defining and organizing issues related to quality in the MDD. The format of the workshop consists of two parts: presentation and discussion. The presentation part is aimed at reporting research results related to quality aspects in modeling. Seven papers were selected for the presentation out of 16 submissions; the selected papers are included in these proceedings. The discussion part is intended to be a forum for exchange of ideas related to understanding of quality and approaching it in a systematic way

Workshop proceedings of the 1st workshop on quality in modeling

Quality assessment and assurance constitute an important part of software engineering. The issues of software quality management are widely researched and approached from multiple perspectives and viewpoints. The introduction of a new paradigm in software development – namely Model Driven Development (MDD) and its variations (e.g., MDA [Model Driven Architecture], MDE [Model Driven Engineering], MBD [Model Based Development], MIC [Model Integrated Computing]) – raises new challenges in software quality management, and as such should be given a special attention. In particular, the issues of early quality assessment, based on models at a high abstraction level, and building (or customizing the existing) prediction models for software quality based on model metrics are of central importance for the software engineering community. The workshop is continuation of a series of workshops on consistency that have taken place during the subsequent annual UML conferences and recently MDA-FA. The idea behind this workshop is to extend the scope of interests and address a wide spectrum of problems related to MDD. It is also in line with the overall initiative of the shift from UML to MoDELS. The goal of this workshop is to gather researchers and practitioners interested in the emerging issues of quality in the context of MDD. The workshop is intended to provide a premier forum for discussions related to software quality and MDD. And the aims of the workshop are: - Presenting ongoing research related to quality in modeling in the context of MDD, - Defining and organizing issues related to quality in the MDD. The format of the workshop consists of two parts: presentation and discussion. The presentation part is aimed at reporting research results related to quality aspects in modeling. Seven papers were selected for the presentation out of 16 submissions; the selected papers are included in these proceedings. The discussion part is intended to be a forum for exchange of ideas related to understanding of quality and approaching it in a systematic way