Andrea Capiluppi

Characteristics of open source projects

Most empirical studies about Open Source (OS) projects or products are vertical and usually deal with the flagship, successful projects. There is a substantial lack of horizontal studies to shed light on the whole population of projects, including failures. This paper presents a horizontal study aimed at characterizing OS projects. We analyze a sample of around 400 projects from a popular OS project repository. Each project is characterized by a number of attributes. We analyze these attributes statically and over time. The main results show that few projects are capable of attracting a meaningful community of developers. The majority of projects is made by few (in many cases one) person with a very slow pace of evolution.

From the Cathedral to the Bazaar: An Empirical Study of the Lifecycle of Volunteer Community Projects

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.

Agent-based Simulation of Open Source Evolution

We present an agent-based simulation model developed to study how size, complexity and effort relate to each other in the development of open source software (OSS). In the model, many developer agents generate, extend, and re-factor code modules independently and in parallel. This accords with empirical observations of OSS development. To our knowledge, this is the first model of OSS evolution that includes the complexity of software modules as a limiting factor in productivity, the fitness of the software to its requirements, and the motivation of developers. Validation of the model was done by comparing the simulated results against four measures of software evolution (system size, proportion of highly complex modules, level of complexity control work, and distribution of changes) for four large OSS systems. The simulated results resembled the observed data, except for system size: three of the OSS systems showed alternating patterns of super-linear and sub-linear growth, while the simulations produced only super-linear growth. However, the fidelity of the model for the other measures suggests that developer motivation and the limiting effect of complexity on productivity have a significant effect on the development of OSS systems and should be considered in any model of OSS development.

Empirical Studies of Open Source Evolution

This chapter surveys a sample of empirical studies of Open Source Software (OSS) evolution. According to these, the classical findings in proprietary software evolution, such as Lehman’s laws of software evolution, might need to be revised, at least in part, to account for the OSS observations. The book chapter summarises what appears to be the empirical status of each of Lehman’s laws with respect to OSS and highlights the threats to validity that frequently emerge in this type of research.

Structural evolution of an open source system: a case study

Software evolution empirical studies are made possible only when data is available and easily collectable. Open source software provides a good opportunity for observing software products in various phases of their evolution, growth and maturity. One of the aspects that have not been analyzed yet through empirical studies is the relation that exists between code components growth and the evolving code structure. In this paper, we look at the growth of code elements by measuring the total number of files per release and also by visualizing the folder structure as a tree. Both, the number of files and the shape of the folder tree structure offer proxies to study the evolving complexity of the system. In this study, a number of hypotheses about the evolutionary patterns in the size of files and folders, in the folder tree structure, reflecting common assumptions on software engineering and open source are tested against empirical data reflecting the evolution of the ARLA system. We also relate some of the observed patterns to the arrival rate of new developers. Results show that the number of code components (files and folders) over releases can be interpreted as a linear trend with a superimposed ripple. We also describe the more apparent characteristics of the evolution of the folder tree structure. Furthermore, we observe that the average size of files and folders tends to stabilize over releases. The cumulative number of people who have been involved as developers of the system follows a trend which resembles that of the size in files over releases, suggesting that the latter could provide a good indicator for rate of work and productivity. There was no apparent relation between the arrival rate of developers and the changes observed in the code structure.

An Empirical Study of the Evolution of an Agile-Developed Software System

We have analyzed evolution patterns over two and a half years for a system developed using extreme programming. We find that the system shows a smooth pattern of growth overall, that (McCabe) code complexity is low, and that the relative amount of complexity control work (e.g. refactoring) is higher than in other systems we have studied. To interpret these results, we have drawn on qualitative data including the results of an observational study, records of progress and productivity, and comments on our findings from team members.

Adapting the "staged model for software evolution" to free/libre/open source software

Research into traditional software evolution has been tackled from two broad perspectives: that focused on the how, which looks at the processes, methods and techniques to implement and evolve software; and that focused on the what/why perspective, aiming at achieving an understanding of the drivers and general characteristics of the software evolution phenomenon. The two perspectives are related in various ways: the study of the what/why is for instance essential to achieve an appropriate management of software engineering activities, and to guide innovation in processes, methods and tools, that is, the how. The output of the what/why studies is exemplified by empirical hypotheses, such as the staged model of software evolution. This paper focuses on the commonalities and differences between the evolution and patterns in the lifecycles of traditional commercial systems and free/libre/open source software (FLOSS) systems. The existing staged model for software evolution is therefore revised for its applicability on FLOSS systems.

A study of open source software evolution data using qualitative simulation

Simulation modelling of growth trends and other empirical data from software systems can reveal the main drivers of software evolution and help improve understanding and management of the software evolution phenomenon. This article reports on the application of qualitative abstraction techniques to data from 25 open source software (OSS) systems. After justifying the use of qualitative simulation techniques for the software process domain, the article presents an analysis of the support from OSS-derived data to previously developed qualitative simulation models, which were inspired by observations from the domain of proprietary systems. The analysis involved comparison of model output and qualitatively abstracted growth trends. The analysis also involved the comparison of the transitions in trends of functional size and complexity to those predicted by the models in a sub-set of 21 systems for which complexity data was available. The results indicate that models are able to replicate some of the features in the data. This, in turn, suggests that the study of the relationship between size and complexity and its interaction via feedback loops has a role in explaining the long-term evolutionary behaviour of OSS systems. This is not surprising since it is well known that the evolution of all type of real-world software systems, proprietary and OSS, is driven by feedback from their stakeholders

Studying the evolution of open source systems at different levels of granularity: two case studies

This work presents a study of several evolutionary attributes of two open source software systems: the distributed file system Arla and the stable branch of the Web browser Mozilla. The attributes (size, activity rate and complexity) are visualized over releases using measures at various levels of granularity: folders, files and procedures. A number of hypotheses about the evolutionary behaviour of the systems are considered and, in general, supported by the data from the 2 systems.

Estimating development effort in Free/Open source software projects by mining software repositories: a case study of OpenStack

Because of the distributed and collaborative nature of free / open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially ---but not only--- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.