Affiliated Participation in Open Source Communities

Background: The adoption of Free/Libre and Open Source Software (FOSS) by institutions is significantly increasing, and so is the affiliated participation (the participation of industry engineers in open source communities as part of their jobs). Aims: This study is an investigation into affiliated participation in FOSS communities. So far, little is known about the affiliated participation and the forces that influence it, even though the FOSS innovation model is increasingly becoming a serious contender for the private investment model in many sectors. Method: We present a qualitative inquiry into affiliated participation in the Robot Operating System (ROS) and Linux Kernel communities, using twenty-one in-depth interviews and participatory observation data from twenty-nine community events. Results: Our results show that affiliated participation in these communities is constrained by several barriers: objections of senior management, protection of the company's image, protection of intellectual property, undefined processes and policies, the high cost of participation, and unfamiliarity with the FOSS system. Conclusions: These barriers should be addressed in any organization considering using FOSS as a significant acquisition, distribution, and development strategy

Going Beyond Obscurity: Organizational Approaches to Data Anonymization

Anonymization is viewed as a solution to over-exposure of personal information in a data-driven society. Yet how organizations apply anonymization techniques to data for regulatory, ethical or commercial reasons remains underexplored. We investigate how such measures are applied in organizations, asking whether anonymization practices are used, what approaches are considered practical and adequate, and how decisions are made to protect the privacy of data subjects while preserving analytical value. Our findings demonstrate that anonymization is applied to data far less pervasively than expected. Organizations that do employ anonymization often view their practices as sensitive and resort to anonymity by obscurity alongside technical means. Rather than being a purely technical question of applying the right algorithms, anonymization in practice is a complex socio-technical process that relies on multi-stakeholder collaborations. Organizational decision-making about appropriate approaches and the management of responsibility can result in workarounds necessary to negotiate the technical complexi

Finding suitable variability abstractions for lifted analysis

Many software systems are today variational: they are built as program families or Software Product Lines. They can produce a potentially huge number of related programs, known as products or variants, by selecting suitable configuration options (features) at compile time. Many such program families are safety critical, yet the appropriate tools only rarely are able to analyze them effeciently. Researchers have addressed this problem by designing specialized variability-aware static (dataflow) analyses, which allow analyzing all variants of the family, simultaneously, in a single run without generating any of the variants explicitly. They are also known as lifted or family-based analyses. They take as input the common code base, which encodes all variants of a program family, and produce precise analysis results corresponding to all variants. These analyses scale much better than “brute force” approach, where all individual variants are analyzed in isolation, one-by-one, using off-the-shelf single-program analyzers. Nevertheless, the computational cost of lifted analyses still greatly depends on the number of features and variants (which is often huge). For families with a large number of features and variants, the lifted analyses may be too costly or even infeasible. In order to speed up lifted analyses and make them computationally cheaper, variability abstractions which simplify variability away from program families and lifted analyses have been introduced. However, the space of possible variability abstractions is still intractably large to search naively, with most abstractions being either too imprecise or too costly.We introduce here a method to efficiently find suitable variability abstractions from a large space of possible abstractions for a lifted static analysis. The main idea is to use a pre-analysis to estimate the impact of variability-specific parts of the program family on the analysis’s precision. The pre-analysis is fully variability-aware while it aggressively abstracts the other semantics aspects. Then we use the pre-analysis results to find out when and where the subsequent abstract lifted analysis should turn off or on its variability-awareness. The abstraction constructed in this way is effective in discarding variability-specific program details that are irrelevant for showing the analysis’s ultimate goal. We formalize this approach and we illustrate its effectiveness on several Java case studies. The evaluation shows that our approach which consists of running a pre-analysis followed by a subsequent abstract lifted analysis achieves competitive the precision-speed tradeoff compared to the standard lifted analysis

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Variability Abstractions: Trading Precision for Speed in Family-Based Analyses

Family-based (lifted) data-flow analysis for Software Product Lines (SPLs) is capable of analyzing all valid products (variants) without generating any of them explicitly. It takes as input only the common code base, which encodes all variants of a SPL, and produces analysis results corresponding to all variants. However, the computational cost of the lifted analysis still depends inherently on the number of variants (which is exponential in the number of features, in the worst case). For a large number of features, the lifted analysis may be too costly or even infeasible. In this paper, we introduce variability abstractions defined as Galois connections and use abstract interpretation as a formal method for the calculational-based derivation of approximate (abstracted) lifted analyses of SPL programs, which are sound by construction. Moreover, given an abstraction we define a syntactic transformation that translates any SPL program into an abstracted version of it, such that the analysis of the abstracted SPL coincides with the corresponding abstracted analysis of the original SPL. We implement the transformation in a tool, that works on Object-Oriented Java program families, and evaluate the practicality of this approach on three Java SPL benchmarks

Why Does Code Review Work for Open Source Software Communities?

Open source software communities have demonstrated that they can produce high quality results. The overall success of peer code review, commonly used in open source projects, has likely contributed strongly to this success. Code review is an emotionally loaded practice, with public exposure of reputation and ample opportunities for conflict. We set off to ask why code review works for open source communities, despite this inherent challenge. We interviewed 21 open source contributors from four communities and participated in meetings of ROS community devoted to implementation of the code review process.It appears that the hacker ethic is a key reason behind the success of code review in FOSS communities. It is built around the ethic of passion and the ethic of caring. Furthermore, we observed that tasks of code review are performed with strong intrinsic motivation, supported by many non-material extrinsic motivation mechanisms, such as desire to learn, to grow reputation, or to improve one’s positioning on the job market.In the paper, we describe the study design, analyze the collected data and formulate 20 proposals for how what we know about hacker ethics and human and social aspects of code review, could be exploited to improve the effectiveness of the practice in software projects

Identifying Redundancies in Fork-based Development

Fork-based development is popular and easy to use, but makes it difficult to maintain an overview of the whole community when the number of forks increases. This may lead to redundant development where multiple developers are solving the same problem in parallel without being aware of each other. Redundant development wastes effort for both maintainers and developers. In this paper, we designed an approach to identify redundant code changes in forks as early as possible by extracting clues indicating similarities between code changes, and building a machine learning model to predict redundancies. We evaluated the effectiveness from both the maintainer's and the developer's perspectives. The result shows that we achieve 57-83% precision for detecting duplicate code changes from maintainer's perspective, and we could save developers' effort of 1.9-3.0 commits on average. Also, we show that our approach significantly outperforms existing state-of-art

Flavonoids as GABAA receptor ligands: the whole story?

Benzodiazepines are the most widely prescribed class of psychoactive drugs in current therapeutic use, despite the important unwanted side effects that they produce, such as sedation, myorelaxation, ataxia, amnesia, and ethanol and barbiturate potentiation and tolerance. They exert their therapeutic effects via binding to the benzodiazepine binding site of gamma-aminobutyric acid (GABA) type A receptors, and allosterically modulating the chloride flux through the ion channel complex. First isolated from plants used as tranquilizers in folkloric medicine, some natural flavonoids have been shown to possess selective affinity for the benzodiazepine binding site with a broad spectrum of central nervous system effects. Since the initial search for alternative benzodiazepine ligands amongst the flavonoids, a list of successful synthetic derivatives has been generated with enhanced activities. This review provides an update on research developments that have established the activity of natural and synthetic flavonoids on GABA type A receptors. Flavonoids are prominent drugs in the treatment of mental disorders, and can also be used as tools to study modulatory sites at GABA type A receptors and to develop GABA type A selective agents further.Fil: Wasowski, Cristina Lucia N.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Físico-Química Biológicas "Prof. Alejandro C. Paladini". Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Físico-Química Biológicas; ArgentinaFil: Marder, Nora Mariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Físico-Química Biológicas "Prof. Alejandro C. Paladini". Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Físico-Química Biológicas; Argentin