19,375 research outputs found

    Software search is not a science, even among scientists: A survey of how scientists and engineers find software

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    Improved software discovery is a prerequisite for greater software reuse: after all, if someone cannot find software for a particular task, they cannot reuse it. Understanding people’s approaches and preferences when they look for software could help improve facilities for software discovery. We surveyed people working in several scientific and engineering fields to better understand their approaches and selection criteria. We found that even among highly-trained people, the rudimentary approaches of relying on general Web searches, the opinions of colleagues, and the literature were still the most commonly used. However, those who were involved in software development differed from nondevelopers in their use of social help sites, software project repositories, software catalogs, and organization-specific mailing lists or forums. For example, software developers in our sample were more likely to search in community sites such as Stack Overflow even when seeking ready-to-run software rather than source code, and likewise, asking colleagues was significantly more important when looking for ready-to-run software. Our survey also provides insight into the criteria that matter most to people when they are searching for ready-to-run software. Finally, our survey also identifies some factors that can prevent people from finding software

    The importance of socio-technical resources for software ecosystems management

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    AbstractSoftware Ecosystem (SECO) is often understood as a set of actors interacting among themselves and manipulating artifacts with the support of a common technology platform. Usually, SECO approaches can be designed as an environment whose component repository is gathering stakeholders as well as software products and components. By manipulating software artifacts, a technical network emerges from interactions made over the component repository in order to reuse artifacts, improving code quality, downloading, selling, buying etc. Although technical repositories are essential to store SECO’s artifacts, the interaction among actors in an emerging social network is a key factor to strengthen the SECO’s through increasing actor’s participation, e.g., developing new software, reporting bugs, and communicating with suppliers. In the SECO context, both the internal and external actors keep the platform’s components updated and documented, and even support requirements and suggestions for new releases and bug fixes. However, those repositories often lack resources to support actors’ relationships and consequently to improve the reuse processes by stimulating actors’ interactions, information exchange and better understanding on how artifacts are manipulated by actors. In this paper, we focused on investigating SECO as component repositories that include socio-technical resources. As such, we present a survey that allowed us to identify the relevance of each resource for a SECO based on component repositories, initially focused on the Brazilian scenario. This paper also describes the analysis of the data collected in that survey. Information of other SECO elements extracted from the data is also presented, e.g., the participants’ profile and how they behave within a SECO. As an evolution of our research, a study for evaluating the availability and the use of such resources on top of two platforms was also conducted with experts in collaborative development in order to analyze the usage of the most relevant resources in real SECO’s platforms. We concluded that socio-technical resources have aided collaboration in software development for SECO, coordination of teams based on more knowledge of actor’s tasks and interactions, and monitoring of quality of SECOs’ platforms through the orchestration of the contributions developed by external actors

    Towards improving web service repositories through semantic web techniques

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    The success of the Web services technology has brought topicsas software reuse and discovery once again on the agenda of software engineers. While there are several efforts towards automating Web service discovery and composition, many developers still search for services via online Web service repositories and then combine them manually. However, from our analysis of these repositories, it yields that, unlike traditional software libraries, they rely on little metadata to support service discovery. We believe that the major cause is the difficulty of automatically deriving metadata that would describe rapidly changing Web service collections. In this paper, we discuss the major shortcomings of state of the art Web service repositories and, as a solution, we report on ongoing work and ideas on how to use techniques developed in the context of the Semantic Web (ontology learning, mapping, metadata based presentation) to improve the current situation

    Characterizing the Landscape of Musical Data on the Web: State of the Art and Challenges

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    Musical data can be analysed, combined, transformed and exploited for diverse purposes. However, despite the proliferation of digital libraries and repositories for music, infrastructures and tools, such uses of musical data remain scarce. As an initial step to help fill this gap, we present a survey of the landscape of musical data on the Web, available as a Linked Open Dataset: the musoW dataset of catalogued musical resources. We present the dataset and the methodology and criteria for its creation and assessment. We map the identified dimensions and parameters to existing Linked Data vocabularies, present insights gained from SPARQL queries, and identify significant relations between resource features. We present a thematic analysis of the original research questions associated with surveyed resources and identify the extent to which the collected resources are Linked Data-ready

    Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

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    A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval
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