Assessing architectural evolution: A case study

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach

An empirical study of aspect-oriented metrics

Metrics for aspect-oriented software have been proposed and used to investigate the benefits and the disadvantages of crosscutting concerns modularisation. Some of these metrics have not been rigorously defined nor analytically evaluated. Also, there are few empirical data showing typical values of these metrics in aspect-oriented software. In this paper, we provide rigorous definitions, usage guidelines, analytical evaluation, and empirical data from ten open source projects, determining the value of six metrics for aspect-oriented software (lines of code, weighted operations in module, depth of inheritance tree, number of children, crosscutting degree of an aspect, and coupling on advice execution). We discuss how each of these metrics can be used to identify shortcomings in existing aspect-oriented software. (C) 2012 Elsevier B.V. All rights reserved.CNPq [140046/06-2]; Project CNPQ-PROSUL [490478/06-9]; Capes-Grices [2051-05-2]; FAPERGS [10/0470-1]; FCT MCTESinfo:eu-repo/semantics/publishedVersio

Application of social networking algorithms in program analysis: understanding execution frequencies

2011 Summer.Includes bibliographical references.There may be some parts of a program that are more commonly used at runtime, whereas there may be other parts that are less commonly used or not used at all. In this exploratory study, we propose an approach to predict how frequently or rarely different parts of a program will get used at runtime without actually running the program. Knowledge of the most frequently executed parts can help identify the most critical and the most testable parts of a program. The portions predicted to be the less commonly executed tend to be hard to test parts of a program. Knowing the hard to test parts of a program can aid the early development of test cases. In our approach we statically analyse code or static models of code (like UML class diagrams), using quantified social networking measures and web structure mining measures. These measures assign ranks to different portions of code for use in predictions of the relative frequency that a section of code will be used. We validated these rank ordering of predictions by running the program with a common set of use cases and identifying the actual rank ordering. We compared the predictions with other measures that use direct coupling or lines of code. We found that our predictions fared better as they were statistically more correlated to the actual rank ordering than the other measures. We present a prototype tool written as an eclipse plugin, that implements and validates our approach. Given the source code of a Java program, our tool computes the values of the metrics required by our approach to present ranks of all classes in order of how frequently they are expected to get used. Our tool can also instrument the source code to log all the necessary information at runtime that is required to validate our predictions

A Reference Structure for Modular Model-based Analyses

Kontext: In dieser Arbeit haben wir die Evolvierbarkeit, Verständlichkeit und Wiederverwendbarkeit von modellbasierten Analysen untersucht. Darum untersuchten wir die Wechselbeziehungen zwischen Modellen und Analysen, insbesondere die Struktur und Abhängigkeiten von Artefakten und die Dekomposition und Komposition von modellbasierten Analysen. Herausforderungen: Softwareentwickler verwenden Modelle von Softwaresystemen, um die Evolvierbarkeit und Wiederverwendbarkeit eines Architekturentwurfs zu bestimmen. Diese Modelle ermöglichen die Softwarearchitektur zu analysieren, bevor die erste Zeile Code geschreiben wird. Aufgrund evolutionärer Veränderungen sind modellbasierte Analysen jedoch auch anfällig für eine Verschlechterung der Evolvierbarkeit, Verständlichkeit und Wiederverwendbarkeit. Diese Probleme lassen sich auf die Ko-Evolution von Modellierungssprache und Analyse zurückführen. Der Zweck einer Analyse ist die systematische Untersuchung bestimmter Eigenschaften eines zu untersuchenden Systems. Nehmen wir zum Beispiel an, dass Softwareentwickler neue Eigenschaften eines Softwaresystems analysieren wollen. In diesem Fall müssen sie Merkmale der Modellierungssprache und die entsprechenden modellbasierten Analysen anpassen, bevor sie neue Eigenschaften analysieren können. Merkmale in einer modellbasierten Analyse sind z.\,B. eine Analysetechnik, die eine solche Qualitätseigenschaft analysiert. Solche Änderungen führen zu einer erhöhten Komplexität der modellbasierten Analysen und damit zu schwer zu pflegenden modellbasierten Analysen. Diese steigende Komplexität verringert die Verständlichkeit der modellbasierten Analysen. Infolgedessen verlängern sich die Entwicklungszyklen, und die Softwareentwickler benötigen mehr Zeit, um das Softwaresystem an veränderte Anforderungen anzupassen. Stand der Technik: Derzeitige Ansätze ermöglichen die Kopplung von Analysen auf einem System oder über verteilte Systeme hinweg. Diese Ansätze bieten die technische Struktur für die Kopplung von Simulationen, nicht aber eine Struktur wie Komponenten (de)komponiert werden können. Eine weitere Herausforderung beim Komponieren von Analysen ist der Verhaltensaspekt, der sich darin äußert, wie sich die Analysekomponenten gegenseitig beeinflussen. Durch die Synchronisierung jeder beteiligten Simulation erhöht die Modularisierung von Simulationen den Kommunikationsbedarf. Derzeitige Ansätze erlauben es, den Kommunikationsaufwand zu reduzieren; allerdings werden bei diesen Ansätzen die Dekomposition und Komposition dem Benutzer überlassen. Beiträge: Ziel dieser Arbeit ist es, die Evolvierbarkeit, Verständlichkeit und Wiederverwendbarkeit von modellbasierten Analysen zu verbessern. Zu diesem Zweck wird die Referenzarchitektur für domänenspezifische Modellierungssprachen als Grundlage genommen und die Übertragbarkeit der Struktur der Referenzarchitektur auf modellbasierte Analysen untersucht. Die geschichtete Referenzarchitektur bildet die Abhängigkeiten der Analysefunktionen und Analysekomponenten ab, indem sie diese bestimmten Schichten zuordnet. Wir haben drei Prozesse für die Anwendung der Referenzarchitektur entwickelt: (i) Refactoring einer bestehenden modellbasierten Analyse, (ii) Entwurf einer neuen modellbasierten Analyse und (iii) Erweiterung einer bestehenden modellbasierten Analyse. Zusätzlich zur Referenzarchitektur für modellbasierte Analysen haben wir wiederkehrende Strukturen identifiziert, die zu Problemen bei der Evolvierbarkeit, Verständlichkeit und Wiederverwendbarkeit führen; in der Literatur werden diese wiederkehrenden Strukturen auch als Bad Smells bezeichnet. Wir haben etablierte modellbasierte Analysen untersucht und dreizehn Bad Smells identifiziert und spezifiziert. Neben der Spezifizierung der Bad Smells bieten wir einen Prozess zur automatischen Identifizierung dieser Bad Smells und Strategien für deren Refactoring, damit Entwickler diese Bad Smells vermeiden oder beheben können. In dieser Arbeit haben wir auch eine Modellierungssprache zur Spezifikation der Struktur und des Verhaltens von Simulationskomponenten entwickelt. Simulationen sind Analysen, um ein System zu untersuchen, wenn das Experimentieren mit dem bestehenden System zu zeitaufwändig, zu teuer, zu gefährlich oder einfach unmöglich ist, weil das System (noch) nicht existiert. Entwickler können die Spezifikation nutzen, um Simulationskomponenten zu vergleichen und so identische Komponenten zu identifizieren. Validierung: Die Referenzarchitektur für modellbasierte Analysen, haben wir evaluiert, indem wir vier modellbasierte Analysen in die Referenzarchitektur überführt haben. Wir haben eine szenariobasierte Evaluierung gewählt, die historische Änderungsszenarien aus den Repositories der modellbasierten Analysen ableitet. In der Auswertung können wir zeigen, dass sich die Evolvierbarkeit und Verständlichkeit durch die Bestimmung der Komplexität, der Kopplung und der Kohäsion verbessert. Die von uns verwendeten Metriken stammen aus der Informationstheorie, wurden aber bereits zur Bewertung der Referenzarchitektur für DSMLs verwendet. Die Bad Smells, die durch die Co-Abhängigkeit von modellbasierten Analysen und ihren entsprechenden DSMLs entstehen, haben wir evaluiert, indem wir vier modellbasierte Analysen nach dem Auftreten unserer schlechten Gerüche durchsucht und dann die gefundenen Bad Smells behoben haben. Wir haben auch eine szenariobasierte Auswertung gewählt, die historische Änderungsszenarien aus den Repositories der modellbasierten Analysen ableitet. Wir können zeigen, dass die Bad Smells die Evolvierbarkeit und Verständlichkeit negativ beeinflussen, indem wir die Komplexität, Kopplung und Kohäsion vor und nach der Refaktorisierung bestimmen. Den Ansatz zum Spezifizieren und Finden von Komponenten modellbasierter Analysen haben wir evaluiert, indem wir Komponenten von zwei modellbasierten Analysen spezifizieren und unseren Suchalgorithmus verwenden, um ähnliche Analysekomponenten zu finden. Die Ergebnisse der Evaluierung zeigen, dass wir in der Lage sind, ähnliche Analysekomponenten zu finden und dass unser Ansatz die Suche nach Analysekomponenten mit ähnlicher Struktur und ähnlichem Verhalten und damit die Wiederverwendung solcher Komponenten ermöglicht. Nutzen: Die Beiträge unserer Arbeit unterstützen Architekten und Entwickler bei ihrer täglichen Arbeit, um wartbare und wiederverwendbare modellbasierte Analysen zu entwickeln. Zu diesem Zweck stellen wir eine Referenzarchitektur bereit, die die modellbasierte Analyse und die domänenspezifische Modellierungssprache aufeinander abstimmt und so die Koevolution erleichtert. Zusätzlich zur Referenzarchitektur bieten wir auch Refaktorisierungsoperationen an, die es Architekten und Entwicklern ermöglichen, eine bestehende modellbasierte Analyse an die Referenzarchitektur anzupassen. Zusätzlich zu diesem technischen Aspekt haben wir drei Prozesse identifiziert, die es Architekten und Entwicklern ermöglichen, eine neue modellbasierte Analyse zu entwickeln, eine bestehende modellbasierte Analyse zu modularisieren und eine bestehende modellbasierte Analyse zu erweitern. Dies geschieht natürlich so, dass die Ergebnisse mit der Referenzarchitektur konform sind. Darüber hinaus ermöglicht unsere Spezifikation den Entwicklern, bestehende Simulationskomponenten zu vergleichen und sie bei Bedarf wiederzuverwenden. Dies erspart den Entwicklern die Neuimplementierung von Komponenten

Quality Assurance of Software Models - A Structured Quality Assurance Process Supported by a Flexible Tool Environment in the Eclipse Modeling Project

The paradigm of model-based software development (MBSD) has become more and more popular since it promises an increase in the efficiency and quality of software development. In this paradigm, software models play an increasingly important role and software quality and quality assurance consequently leads back to the quality and quality assurance of the involved models. The fundamental aim of this thesis is the definition of a structured syntax-oriented process for quality assurance of software models that can be adapted to project-specific and domain-specific needs. It is structured into two sub-processes: a process for the specification of project-specific model quality assurance techniques, and a process for applying them on concrete software models within a MBSD project. The approach concentrates on quality aspects to be checked on the abstract model syntax and is based on quality assurance techniques model metrics, smells, and refactorings well-known from literature. So far, these techniques are mostly considered in isolation only and therefore the proposed process integrates them in order to perform model quality assurance more systematically. Three example cases performing the process serve as proof-of-concept implementations and show its applicability, its flexibility, and hence its usefulness. Related to several issues concerning model quality assurance minor contributions of this thesis are (1) the definition of a quality model for model quality that consists of high-level quality attributes and low-level characteristics, (2) overviews on metrics, smells, and refactorings for UML class models including structured descriptions of each technique, and (3) an approach for composite model refactoring that concentrates on the specification of refactoring composition. Since manually reviewing models is time consuming and error prone, several tasks of the proposed process should consequently be automated. As a further main contribution, this thesis presents a flexible tool environment for model quality assurance which is based on the Eclipse Modeling Framework (EMF), a common open source technology in model-based software development. The tool set is part of the Eclipse Modeling Project (EMP) and belongs to the Eclipse incubation project EMF Refactor which is available under the Eclipse public license (EPL). The EMF Refactor framework supports both the model designer and the model reviewer by obtaining metrics reports, by checking for potential model deficiencies (called model smells) and by systematically restructuring models using refactorings. The functionality of EMF Refactor is integrated into standard tree-based EMF instance editors, graphical GMF-based editors as used by Papyrus UML, and textual editors provided by Xtext. Several experiments and studies show the suitability of the tools for supporting the techniques of the structured syntax-oriented model quality assurance process

Assessing and improving the quality of model transformations

Software is pervading our society more and more and is becoming increasingly complex. At the same time, software quality demands remain at the same, high level. Model-driven engineering (MDE) is a software engineering paradigm that aims at dealing with this increasing software complexity and improving productivity and quality. Models play a pivotal role in MDE. The purpose of using models is to raise the level of abstraction at which software is developed to a level where concepts of the domain in which the software has to be applied, i.e., the target domain, can be expressed e??ectively. For that purpose, domain-speci??c languages (DSLs) are employed. A DSL is a language with a narrow focus, i.e., it is aimed at providing abstractions speci??c to the target domain. This makes that the application of models developed using DSLs is typically restricted to describing concepts existing in that target domain. Reuse of models such that they can be applied for di??erent purposes, e.g., analysis and code generation, is one of the challenges that should be solved by applying MDE. Therefore, model transformations are typically applied to transform domain-speci??c models to other (equivalent) models suitable for di??erent purposes. A model transformation is a mapping from a set of source models to a set of target models de??ned as a set of transformation rules. MDE is gradually being adopted by industry. Since MDE is becoming more and more important, model transformations are becoming more prominent as well. Model transformations are in many ways similar to traditional software artifacts. Therefore, they need to adhere to similar quality standards as well. The central research question discoursed in this thesis is therefore as follows. How can the quality of model transformations be assessed and improved, in particular with respect to development and maintenance? Recall that model transformations facilitate reuse of models in a software development process. We have developed a model transformation that enables reuse of analysis models for code generation. The semantic domains of the source and target language of this model transformation are so far apart that straightforward transformation is impossible, i.e., a semantic gap has to be bridged. To deal with model transformations that have to bridge a semantic gap, the semantics of the source and target language as well as possible additional requirements should be well understood. When bridging a semantic gap is not straightforward, we recommend to address a simpli??ed version of the source metamodel ??rst. Finally, the requirements on the transformation may, if possible, be relaxed to enable automated model transformation. Model transformations that need to transform between models in di??erent semantic domains are expected to be more complex than those that merely transform syntax. The complexity of a model transformation has consequences for its quality. Quality, in general, is a subjective concept. Therefore, quality can be de??ned in di??erent ways. We de??ned it in the context of model transformation. A model transformation can either be considered as a transformation de??nition or as the process of transforming a source model to a target model. Accordingly, model transformation quality can be de??ned in two di??erent ways. The quality of the de??nition is referred to as its internal quality. The quality of the process of transforming a source model to a target model is referred to as its external quality. There are also two ways to assess the quality of a model transformation (both internal and external). It can be assessed directly, i.e., by performing measurements on the transformation de??nition, or indirectly, i.e., by performing measurements in the environment of the model transformation. We mainly focused on direct assessment of internal quality. However, we also addressed external quality and indirect assessment. Given this de??nition of quality in the context of model transformations, techniques can be developed to assess it. Software metrics have been proposed for measuring various kinds of software artifacts. However, hardly any research has been performed on applying metrics for assessing the quality of model transformations. For four model transformation formalisms with di??fferent characteristics, viz., for ASF+SDF, ATL, Xtend, and QVTO, we de??ned sets of metrics for measuring model transformations developed with these formalisms. While these metric sets can be used to indicate bad smells in the code of model transformations, they cannot be used for assessing quality yet. A relation has to be established between the metric sets and attributes of model transformation quality. For two of the aforementioned metric sets, viz., the ones for ASF+SDF and for ATL, we conducted an empirical study aiming at establishing such a relation. From these empirical studies we learned what metrics serve as predictors for di??erent quality attributes of model transformations. Metrics can be used to quickly acquire insights into the characteristics of a model transformation. These insights enable increasing the overall quality of model transformations and thereby also their maintainability. To support maintenance, and also development in a traditional software engineering process, visualization techniques are often employed. For model transformations this appears as a feasible approach as well. Currently, however, there are few visualization techniques available tailored towards analyzing model transformations. One of the most time-consuming processes during software maintenance is acquiring understanding of the software. We expect that this holds for model transformations as well. Therefore, we presented two complementary visualization techniques for facilitating model transformation comprehension. The ??rst-technique is aimed at visualizing the dependencies between the components of a model transformation. The second technique is aimed at analyzing the coverage of the source and target metamodels by a model transformation. The development of the metric sets, and in particular the empirical studies, have led to insights considering the development of model transformations. Also, the proposed visualization techniques are aimed at facilitating the development of model transformations. We applied the insights acquired from the development of the metric sets as well as the visualization techniques in the development of a chain of model transformations that bridges a number of semantic gaps. We chose to solve this transformational problem not with one model transformation, but with a number of smaller model transformations. This should lead to smaller transformations, which are more understandable. The language on which the model transformations are de??ned, was subject to evolution. In particular the coverage visualization proved to be bene??cial for the co-evolution of the model transformations. Summarizing, we de??ned quality in the context of model transformations and addressed the necessity for a methodology to assess it. Therefore, we de??ned metric sets and performed empirical studies to validate whether they serve as predictors for model transformation quality. We also proposed a number of visualizations to increase model transformation comprehension. The acquired insights from developing the metric sets and the empirical studies, as well as the visualization tools, proved to be bene??cial for developing model transformations

Closing the gap between guidance and practice, an investigation of the relevance of design guidance to practitioners using object-oriented technologies

This thesis investigates if object oriented guidance is relevant in practice, and how this affects software that is produced. This is achieved by surveying practitioners and studying how constructs such as interfaces and inheritance are used in open-source systems. Surveyed practitioners framed 'good design' in terms of impact on development and maintenance. Recognition of quality requires practitioner judgement (individually and as a group), and principles are valued over rules. Time constraints heighten sensitivity to the rework cost of poor design decisions. Examination of open source systems highlights the use of interface and inheritance. There is some evidence of 'textbook' use of these structures, and much use is simple. Outliers are widespread indicating a pragmatic approach. Design is found to reflect the pressures of practice - high-level decisions justify 'designed' structures and architecture, while uncertainty leads to deferred design decisions - simpler structures, repetition, and unconsolidated design. Sub-populations of structures can be identified which may represent common trade-offs. Useful insights are gained into practitioner attitude to design guidance. Patterns of use and structure are identified which may aid in assessment and comprehension of object oriented systems.This thesis investigates if object oriented guidance is relevant in practice, and how this affects software that is produced. This is achieved by surveying practitioners and studying how constructs such as interfaces and inheritance are used in open-source systems. Surveyed practitioners framed 'good design' in terms of impact on development and maintenance. Recognition of quality requires practitioner judgement (individually and as a group), and principles are valued over rules. Time constraints heighten sensitivity to the rework cost of poor design decisions. Examination of open source systems highlights the use of interface and inheritance. There is some evidence of 'textbook' use of these structures, and much use is simple. Outliers are widespread indicating a pragmatic approach. Design is found to reflect the pressures of practice - high-level decisions justify 'designed' structures and architecture, while uncertainty leads to deferred design decisions - simpler structures, repetition, and unconsolidated design. Sub-populations of structures can be identified which may represent common trade-offs. Useful insights are gained into practitioner attitude to design guidance. Patterns of use and structure are identified which may aid in assessment and comprehension of object oriented systems

Cohesion Metrics for Improving Software Quality

Abstract Software product metrics aim at measuring the quality of software. Modu- larity is an essential factor in software quality. In this work, metrics related to modularity and especially cohesion of the modules, are considered. The existing metrics are evaluated, and several new alternatives are proposed. The idea of cohesion of modules is that a module or a class should consist of related parts. The closely related principle of coupling says that the relationships between modules should be minimized. First, internal cohesion metrics are considered. The relations that are internal to classes are shown to be useless for quality measurement. Second, we consider external relationships for cohesion. A detailed analysis using design patterns and refactorings confirms that external cohesion is a better quality indicator than internal. Third, motivated by the successes (and problems) of external cohesion metrics, another kind of metric is proposed that represents the quality of modularity of software. This metric can be applied to refactorings related to classes, resulting in a refactoring suggestion system. To describe the metrics formally, a notation for programs is developed. Because of the recursive nature of programming languages, the properties of programs are most compactly represented using grammars and formal lan- guages. Also the tools that were used for metrics calculation are described.Siirretty Doriast

Model Transformation Languages with Modular Information Hiding

Model transformations, together with models, form the principal artifacts in model-driven software development. Industrial practitioners report that transformations on larger models quickly get sufficiently large and complex themselves. To alleviate entailed maintenance efforts, this thesis presents a modularity concept with explicit interfaces, complemented by software visualization and clustering techniques. All three approaches are tailored to the specific needs of the transformation domain