GitHub, the largest code hosting site (with 25 million public active repositories and contributions from 6 million active users), provides an unprecedented opportunity to observe the collaboration patterns of software developers. Understanding the patterns behind the social coding phenomena is an active research area where the insights gained can guide the design of better collaboration tools, and can also help to identify and select developer talent. In this paper, we present a large-scale analysis of the co-commit patterns in GitHub. We analyze 10 million commits made by 200 thousand developers to 16 thousand repositories, using 17 of the most popular programming languages over a period of 3 years. Although a large volume of data is included in our study, we pay close attention to the participation criteria for repositories and developers. We select repositories by reputation (based on star ranking), and we introduce the notion of active developer in GitHub (observing that a limited subset of developers is responsible for the vast majority of the commits). Using co-authorship networks, we analyze the co-commit patterns of the active developer network for each programming language. We observe that the active developer networks are less connected and more centralized than the general GitHub developer networks, and that the patterns vary significantly among languages. We compare our results to other collaborative environments (Wikipedia and scientific research networks), and we also describe the evolution of the co-commit patterns over time.

We introduce Extended Property Paths (EPPs), a significant enhancement of SPARQL property paths. EPPs allow to capture in a succinct way a larger class of navigational queries than property paths. We present the syntax and formal semantics of EPPs and introduce two different evaluation strategies. The first is based on an algorithm implemented in a custom query processor. The second strategy leverages a translation algorithm of EPPs into SPARQL queries that can be executed on existing SPARQL processors. We compare the two evaluation strategies on real data to highlight their pros and cons.

We demonstrate S+EPPs, a system that provides fast construction of bisimulation summaries using graph analytics platforms, and then enhances existing SPARQL engines to support summary-based exploration and navigational query optimization. The construction component adds a novel optimization to a parallel bisimulation algorithm implemented on a multi-core graph processing framework. We show that for several large, disk resident, real world graphs, full summary construction can be completed in roughly the same time as the data load. The query translation component supports Extended Property Paths (EPPs), an enhancement of SPARQL 1.1 property paths that can express a significantly larger class of navigational queries. EPPs are implemented via rewritings into a widely used SPARQL subset. The optimization component can (transparently to users) translate EPPs defined on instance graphs into EPPs that take advantage of bisimulation summaries. S+EPPs combines the query and optimization translations to enable summary-based optimization of graph traversal queries on top of off-the-shelf SPARQL processors. The demonstration showcases the construction of bisimulation summaries of graphs (ranging from millions to billions of edges), together with the exploration benefits and the navigational query speedups obtained by leveraging summaries stored alongside the original datasets.

We describe a framework designed to facilitate privacy auditing while accommodating a variety of privacy scenarios and policies that involve multiple participants. Our proposal is based on two ontologies, L2TAP and SCIP, designed for deployment in a Linked Data environment. L2TAP provides provenance

We introduce divergent designs as a novel tuning paradigm for database systems that employ replication. A divergent design installs a different physical configuration (e.g., indexes and materialized views) with each database replica, specializing replicas for different subsets of the workload. At runtime, queries are routed to the subset of the replicas configured to yield the most efficient execution plans. When compared to uniformly designed replicas, divergent replicas can potentially execute their subset of the queries significantly faster, and their physical configurations could be initialized and maintained(updated) in less time. However, the specialization of divergent replicas limits the ability to load-balance the workload at runtime.

As Web applications mature and evolve, the nature of the semistructured data that drives these applications also changes. An important trend is the need for increased flexibility in the structure of Web documents. Hence, applications cannot rely solely on schemas to provide the complex knowledge needed to visualize, use, query and manage documents. Even when XML Web documents are valid with regard to a schema, the actual structure of such documents may exhibit significant variations across collections for several reasons: the schema may be very lax (e.g., RSS feeds), the schema may be large and different subsets of it may be used in different documents (e.g., industry standards like UBL), or open content models may allow arbitrary schemas to be mixed (e.g., RSS extensions like those used for podcasting). For these reasons, many applications that incorporate XPath queries to process a large Web document collection require an understanding of the actual structure present in the collection, and not just the schema. To support modern Web applications, we introduce DescribeX, a powerful framework that is capable of describing complex XML summaries of Web collections. DescribeX supports the construction of heterogenous summaries that can be declaratively defined and refined by means of axis path regular expression (AxPREs). AxPREs provide the flexibility necessary for declaratively defining complex mappings between instance nodes (in the documents) and summary nodes. These mappings are capable of expressing order and cardinality, among other properties, which can significantly help in the understanding of the structure of large collections of XML documents and enhance the performance of Web applications over these collections. DescribeX captures most summary proposals in the literature by providing (for the first time) a common declarative definition for them. Experimental results demonstrate the scalability of DescribeX summary operations (summary creation, as well as refinement and stabilization, two key enablers for tailoring summaries) on multi-gigabyte Web collections.

Structured documents (predominantly encoded in XML) utilize markup dialects for several purposes, such as conveying logical structure, or providing rendering instructions. XML structure can also help users to navigate within documents to satisfy their information needs. However, including the user's structural preferences in the ranking of retrieved elements remains a key challenge in XML retrieval. In this paper, we propose an approach for including structural preferences in the ranking of XML elements by improving the structural relevance (SR) of results. SR is an evaluation measure which relies on graphical navigation models to capture the structural preferences of users. We propose several algorithms to post-process search engine output to improve the SR of the output. Experimental results (using data, assessments, and search engines from INEX 2007 and 2008) demonstrate the effect of different combinations of post-processing algorithms and navigation models on the effectiveness of systems.

This paper presents a unified framework for the evaluation of a range of structured document retrieval (SDR) approaches and tasks. The framework is based on a model of tree retrieval, evaluated using a novel extension of the Structural elevance (SR) measure. The measure replaces the assumption of independence in traditional information retrieval (IR) with a notion of redundancy that takes into account the user navigation inside documents while seeking relevant information. Unlike existing metrics for SDR, our proposed framework does not require the computation of an ideal ranking which has, thus far, prevented the practical application of such measures. Instead, SR builds on a Markovian model of user navigation that can be estimated through the use of structural summaries. The results of this paper (supported by experimental validation using INEX data) show that SR defined over a tree retrieval model can provide a common basis for the evaluation of SDR approaches across various structured search tasks.

DescribeX is a visual, interactive tool for exploring the underlying structure of an XML collection. DescribeX implements a framework for creating XML summaries described using axis path regular expressions (abbreviated AxPRE). AxPRE's capture all the bisimilarity-based proposals in the summary literature and they can be used to define new and more expressive summaries. This demonstration shows how DescribeX helps to analyze diverse XML collections in one particular scenario: the analysis of protein-protein interaction XML data from multiple providers that conform to the PSI-MI schema.

This paper introduces AxPRE summaries, a formalism that allows exploring the (semi-)structure of large XML collections. AxPRE summaries are implemented in a tool, DescribeX, that supports visualizing XML collections via summaries that can be interactively refined using a powerful and descriptive axis path regular expression language. Experimental results on gigabyte collections have shown that this flexibility does not come at the expense of efficiency.

The popularity of XML has motivated the development of novel XML processing tools many of which embed the XPath language for XML querying, transformation, constraint specification, etc. XPath developers (as well as less technical users) have access to commercial tools to help them use the language effectively. Example tools include debuggers that return the result of XPath subexpressions visualized in the context of the input XML document. This paper introduces XPlainer, a language that provides explanations of why XPath expressions return a specific answer. An explanation returns precisely the nodes in the input XML document that contribute to the answer. We provide a complete formalization for explanation queries based on the semantics of XPath. This enables the use of XPath engines for the evaluation of explanation queries. We describe a tool that uses XPlainer queries to provide visual explanations. The XPlainer-Eclipse tool is built on an extensible development environment that includes editors for visualizing both XML documents and XPath expressions as trees together with the explanation of the answers.

No abstract available.

XML is an important practical paradigm in information technology and has a broad range of applications. How to access and retrieve the XML data is crucial to these applications. There are two standard ways for accessing and manipulating XML data, the Simple API for XML (SAX) and the Document Object Model (DOM). However, when an application needs to traverse through XML data, it is not easy to retrieve the required data with these two standard ways. XML data is impossible to be retrieved back and forth by SAX, and the graph-oriented DOM notation is not easy to work with. With such limitation, the W3C supervises the development of three important languages: XPath [3], XQuery and XSLT for exploring and querying XML. Among these three languages, XPath is the key and cornerstone language for the other two. XPath defines expressions for traversing an XML document and specifies the set of nodes (XPath 1.0) or the sequence of nodes (XPath 2.0) in the XML document.

We are witnessing an explosive increase in the complexity of the information systems we rely upon, Autonomic systems address this challenge by continuously configuring and tuning themselves. Recently, a number of autonomic features have been incorporated into commercial RDBMS; tools for recommending database configurations (i.e., indexes, materialized views, partitions) for a given workload are prominent examples of this promising trend.In this paper, we introduce a flexible characterization of the performance goals of configuration recommenders and develop an experimental evaluation approach to benchmark the effectiveness of these autonomic tools. We focus on exploratory queries and present extensive experimental results using both real and synthetic data that demonstrate the validity of the approach introduced. Our results identify a specific index configuration based on single-column indexes as a very useful baseline for comparisons in the exploratory setting. Furthermore, the experimental results demonstrate the unfulfilled potential for achieving improvements of several orders of magnitude.

The W3C XQuery language recommendation, based on a hierarchical and ordered document model, supports a wide variety of constructs and use cases. There is a diversity of approaches and strategies for evaluating XQuery expressions, in many cases only dealing with limited subsets of the language. In this paper we describe an implementation approach that handles XQuery with arbitrarily-nested FLWR expressions, element constructors and built-in functions (including structural comparisons). Our proposal maps an XQuery expression to a single equivalent SQL query using a novel dynamic interval encoding of a collection of XML documents as relations, augmented with information tied to the query evaluation environment. The dynamic interval technique enables (suitably enhanced) relational engines to produce predictably good query plans that do not preclude the use of sort-merge join query operators. The benefits are realized despite the challenges presented by intermediate results that create arbitrary documents and the need to preserve document order as prescribed by semantics of XQuery. Finally, our experimental results demonstrate that (native or relational) XML systems can benefit from the above technique to avoid a quadratic scale up penalty that effectively prevents the evaluation of nested FLWR expressions for large documents.

There is a significant amount of interest in combining and extending database and information retrieval tech-

We present a framework which allows the user to access and manipulate data uniformly, regardless of whether it resides in a database or in the file system (or in both). A key issue is the performance of the system. We show that text indexing, combined with newly developed optimization techniques, can be used to provide an efficient high level interface to information stored in files. Furthermore, using these techniques, some queries can be evaluated significantly faster than in standard database implementations. We also study the tradeoff between efficiency and the amount of indexing.

article Free Access Share on Hy+: a Hygraph-based query and visualization system Authors: Mariano Consens Computer Systems Research Institute, University of Toronto, Toronto, Canada M5S 1A1 Computer Systems Research Institute, University of Toronto, Toronto, Canada M5S 1A1View Profile , Alberto Mendelzon Computer Systems Research Institute, University of Toronto, Toronto, Canada M5S 1A1 Computer Systems Research Institute, University of Toronto, Toronto, Canada M5S 1A1View Profile Authors Info & Claims ACM SIGMOD RecordVolume 22Issue 2June 1, 1993 pp 511–516https://doi.org/10.1145/170036.171537Online:01 June 1993Publication History 72citation602DownloadsMetricsTotal Citations72Total Downloads602Last 12 Months14Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Software engineering problems often involve large sets of objects and complex relationships among them.This report proposes that graphical visualization techniques can help engineers understanci and solve a class of these problems.To illustrate this, two problems are analyzed and recast using the graphical language GraphLog.The fwst problem is that of simplifying dependencies among components of a system, which translates into removing cycles from a graph.The second problem is that of designing an efficient code overlay structure, which is facilitat cd in several ways through graphical techniques.

We present a query language called GraphLog, based on a graph representation of both data and queries. Queries are graph patterns. Edges in queries represent edges or paths in the database. Regular expressions are used to qualify these paths. We characterize the expressive power of the language and show that it is equivalent to stratified linear Datalog, first order logic with transitive closure, and non-deterministic logarithmic space (assuming ordering on the domain). The fact that the latter three classes coincide was not previously known. We show how GraphLog can be extended to incorporate aggregates and path summarization, and describe briefly our current prototype implementation.

The video presentation “The G+/GraphLog Visual Query System” gives an overview of the capabilities of the ongoing implementation of the G+ Visual Query System for visualizing both data and queries as graphs. The system provides an environment for expressing queries in GraphLog [Con89, CM89, CM90], as well as for browsing, displaying and editing graphs. The visual query system also supports displaying the answers in several different ways.