Visualization of Practices and Metrics (Workpackage 1.2)

Measuring applications is a challenge and one of the goal of the Squale project is to propose a sound quality model. Now presenting the results of such analysis is also a challenge since it is complex to output and present to the user for the following rea- sons: first a lot of data should be presented and at different audience. Second displaying information is one aspect another one is navigating the information. Finally it is im- portant not to overwhelm the users with too much visualizations. This workpackage presents a state of the art in terms of software visualization approaches that are specif- ically designed to display metrics. In addition it sets up the context for the application of such visualization to practices

Visualizing Objects and Memory Usage

International audienceMost of the current garbage collector implementations work by reachability. This means they only take care of the objects that nobody else points to. As a consequence, there are objects which are not really used but are not garbage collected because they are still referenced. Such unused but reachable objects create memory leaks. This is a problem because applications use much more memory than what is actually needed. In addition, they may get slower and crash. It is important to understand which parts of the system are instantiated but also which are used or unused. There is a plethora of work on runtime information or class instantiation visualizations but none of them show whether instances are actually used. Such information is important to identify memory leaks. In this paper, we present some visualizations that show used/unused objects in object-oriented applications. For this, we use Distribution Map which is a visualization showing spread and focus of properties across systems. We extend Distribution Maps to represent the way classes are used or not, since we distinguish between a class that just has instances from one that has used instances. To identify unused objects, we modified the Pharo Virtual Machine

Augmenting IDEs with Runtime Information for Software Maintenance

Object-oriented language features such as inheritance, abstract types, late-binding, or polymorphism lead to distributed and scattered code, rendering a software system hard to understand and maintain. The integrated development environment (IDE), the primary tool used by developers to maintain software systems, usually purely operates on static source code and does not reveal dynamic relationships between distributed source artifacts, which makes it difficult for developers to understand and navigate software systems. Another shortcoming of today's IDEs is the large amount of information with which they typically overwhelm developers. Large software systems encompass several thousand source artifacts such as classes and methods. These static artifacts are presented by IDEs in views such as trees or source editors. To gain an understanding of a system, developers have to open many such views, which leads to a workspace cluttered with different windows or tabs. Navigating through the code or maintaining a working context is thus difficult for developers working on large software systems. In this dissertation we address the question how to augment IDEs with dynamic information to better navigate scattered code while at the same time not overwhelming developers with even more information in the IDE views. We claim that by first reducing the amount of information developers have to deal with, we are subsequently able to embed dynamic information in the familiar source perspectives of IDEs to better comprehend and navigate large software spaces. We propose means to reduce or mitigate the information by highlighting relevant source elements, by explicitly representing working context, and by automatically housekeeping the workspace in the IDE. We then improve navigation of scattered code by explicitly representing dynamic collaboration and software features in the static source perspectives of IDEs. We validate our claim by conducting empirical experiments with developers and by analyzing recorded development sessions

Visualizing Objects and Memory Usage

International audienceMost of the current garbage collector implementations work by reachability. This means they only take care of the objects that nobody else points to. As a consequence, there are objects which are not really used but are not garbage collected because they are still referenced. Such unused but reachable objects create memory leaks. This is a problem because applications use much more memory than what is actually needed. In addition, they may get slower and crash. It is important to understand which parts of the system are instantiated but also which are used or unused. There is a plethora of work on runtime information or class instantiation visualizations but none of them show whether instances are actually used. Such information is important to identify memory leaks. In this paper, we present some visualizations that show used/unused objects in object-oriented applications. For this, we use Distribution Map which is a visualization showing spread and focus of properties across systems. We extend Distribution Maps to represent the way classes are used or not, since we distinguish between a class that just has instances from one that has used instances. To identify unused objects, we modified the Pharo Virtual Machine

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Visually Characterizing Source Code Changes

International audienceRevision Control Systems (e.g., SVN, Git, Mercurial) include automatic and advanced merging algorithms that help developers to merge their modifications with development repositories. While these systems can help to textually detect conflicts, they do not help to identify the semantic consequences of a change. Unfortunately, there is little support to help release masters (integrators) to take decisions about the integration of changes into the system release. Most of the time, the release master needs to read all the modified code, check the diffs to build an idea of a change, and dig for details from related unchanged code to understand the context and potential impact of some changes. As a result, such a task can be overwhelming. In this article we present a visualization tool to support integrators of object-oriented programs in comprehending changes. Our approach named Torch characterizes changes based on structural informa- tion, authors and symbolic information. It mixes text-based diff information with visual representation and metrics characterizing the changes. The current implementation of our approach analyses Smalltalk programs, and thus we de- scribe our experiments applying it to Pharo, a large open-source system. We also report on the evaluations of our approach by release masters and developers of several open-source projects

Package Fingerprint: a visual summary of package interfaces and relationships

International audienceContext: Object-oriented languages such as Java, Smalltalk, and C++ structure their programs using packages. Maintainers of large systems need to understand how packages relate to each other, but this task is complex because packages often have multiple clients and play different roles (class container, code ownership. . . ). Several approaches have been proposed, among which the use of cohesion and coupling metrics. Such metrics help identify candidate packages for restructuring; however, they do not help maintainers actually understand the structure and interrelation- ships between packages. Objectives: In this paper, we use pre-attentive processing as the basis for package visualization and see to what extent it could be used in package understanding. Method: We present the package fingerprint, a 2D visualization of the references made to and from a package. The proposed visualization offers a semantically rich, but compact and zoomable views centered on packages. We focus on two views (incoming and outgoing references) that help users understand how the package under analysis is used by the system and how it uses the system. Results: We applied these views on four large systems: Squeak, JBoss, Azureus, and ArgoUML. We obtained several interesting results, among which, the identification of a set of recurring visual patterns that help maintainers: (a) more easily identify the role of and the way a package is used within the system (e.g., the package under analysis provides a set of layered services), and, (b) detect either problematic situations (e.g., a single package that groups together a large number of basic services) or opportunities for better package restructuring (e.g., removing cyclic dependencies among packages). The visualization generally scaled well and the detection of different patterns was always possible. Conclusion: The proposed visualizations and patterns proved to be useful in understanding and maintaining the different systems we addressed. To generalize to other contexts and systems, a real user study is required