The term Open Source is widely applied to describe some software development methodologies. This paper does not provide a judgment on the open source approach, but exposes the fact that simply stating that a project is open source does not provide a precise description of the approach used to support the project. By taking a multidisciplinary point of view, we propose a collection of characteristics that are common, as well as some that vary among open source projects. The set of open source characteristics we found can be used as a tick-list both for analysing and for setting up open source projects. Our tick-list also provides a starting point for understanding the many meanings of the term open source.

An Open Source Software (OSS) project is unlikely to be successful unless there is an accompanied community that provides the platform for developers and users to collaborate. Members of such communities are volunteers whose motivation to participate and contribute is of essential importance to the success of OSS projects. In this paper, we aim to create an understanding of what motivates people to participate in OSS communities. We theorize that learning is one of the motivational forces. Our theory is grounded in the learning theory of Legitimate Peripheral Participation, and is supported by analyzing the social structure of OSS communities and the co-evolution between OSS systems and communities. We also discuss practical implications of our theory for creating and maintaining sustainable OSS communitie as well as for software engineering research and education..

Open-Source Software (OSS) development is regarded as a successful model of encouraging "natural product evolution". To understand how this "natural product evolution" happens, we have conducted a case study of four typical OSS projects. Unlike most previous studies on software evolution that focus on the evolution of the system per se, our study takes a broader perspective: It examines not only the evolution of OSS systems, but also the evolution of the associated OSS communities, as well as the relationship between the two types of evolution.

As systems evolve and their structure decays, maintainers need accurate and automatic identification of the design problems. Current approaches for automatic detection of design problems are not accurate enough because they analyze only a single version of a system and consequently they miss essential information as design problems appear and evolve over time. Our approach is to use the historical information of the suspected flawed structure to increase the accuracy of the automatic problem detection. Our means is to define measurements which summarize how persistent the problem was and how much maintenance effort was spent on the suspected structure. We apply our approach on a large scale case study and show how it improves the accuracy of the detection of God Classes and Data Classes, and additionally how it adds valuable semantical information about the evolution of flawed design structures.

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Browsing- and querying-oriented schemes have long served as the principal techniques for software developers to locate software components from a component repository for reuse. Unfortunately, the problem remains that software developers simply will not actively search for components when they are unaware that they need components or that relevant components even exist. Thus, to assist software developers in making full use of large component repositories, information access need to be complemented by information delivery. Effective delivery of components calls for the personalization of the components to the task being performed and the knowledge of the user performing it. We have designed, implemented, and evaluated the CodeBroker system to support personalized component delivery to increase the usefulness of a Java software reuse environment.

The goal of this research is to study the role and effects of the use of animated information visualization in early stages of exploratory data analysis tasks. Despite the existence of a large body of research on information visualization, there has been little known regarding how and when one should use and how to interact with animated visualization to help exploring data. By animated visualization, we mean a type of information visualization technique that produces autonomous motions of representations. This research has explored the issue from two aspects: what cognitive effects animated information visualization has, and what interactions people would have with animated visualization when exploring data. We have conducted two user studies to investigate each aspect, and identified research challenges for designing an interactive animated information visualization environment that supports early stages of exploratory data analysis. These findings help us further study how to extend the notions developed in the spatial visualization to the temporal visualization; for instance, what Focus+Context means when applied to the time dimension in animated visualization. 1.

Abstract. Some free software and open source projects have been extremely successful in the past. The success of a project is often related to the number of developers it can attract: a larger community of developers (the `bazaar') identifies and corrects more software defects and adds more features via a peer-review process. In this paper two free software projects (Wine and Arla) are empirically explored in order to characterize their software lifecycle, development processes and communities. Both the projects show a phase where the number of active developers and the actual work performed on the system is constant, or does not grow: we argued that this phase corresponds to the one termed 'cathedral ' in the literature. One of the two projects (Wine) shows also a second phase: a sudden growing amount of developers corresponds to a similar growing output produced: we termed this as the `bazaar ' phase, and we also argued that this phase was not achieved for the other system. A further analysis revealed that the transition between `cathedral' and `bazaar ' was a phase by itself in Wine, achieved by creating a growing amount of new modules, which attracted new developers. 1Introduction Prominent free software (or open source software, OSS) projects such as Linux [32], Apache [27] and FreeBSD [18] have been extremely successful. Anecdotal evidence has been used in the past to characterize successful OSS projects: users/developers acting as "more eyeballs " in the correction of bugs, developers implementing new features independently, skillful project managers dealing with a mostly flat organization, and the resulting coordination costs [28]. Previous studies have provided empirical evidence on the process of successful OSS projects: the definition of various types of developers has been discussed for the Mozilla and the Apache projects, justifying different levels of effort [27], and claiming that the first type (core developers) contribute to the success of a system.

CODECITY is a language-independent interactive 3D visualization tool for the analysis of large software systems. Using a city metaphor, it depicts classes as buildings and packages as districts of a “software city”. By offering consistent locality and solid orientation points we keep the viewer oriented during the exploration of a city. We applied our tool on several large-scale industrial systems.

The term “open source ” is widely applied to describe some software development methodologies. This paper does not provide a judgment on the open source approach, but exposes the fact that simply stating that a project is open source does not provide a precise description of the approach used to support the project. By taking a multidisciplinary point of view, we propose a collection of characteristics that are common, as well as some that vary among open source projects. The set of open source characteristics we found can be used as a tick-list both for analysing and for setting up open source projects. Our tick-list also provides a starting point for understanding the many meanings of the term open source. 1