Heilige, Heiliges und Heiligkeit in spätantiken Religionskulturen

Was das Heilige ist und wie man darüber sprechen kann, ist eine offene Frage in der religionswissenschaftlichen und theologischen Forschung. Jenseits der klassischen Entwürfe von Durkheim, Otto oder Eliade kann Heiliges heute nur in multiperspektivischer Betrachtung angemessen untersucht werden. Die Beiträge zu diesem Band analysieren Diskurse über Heiliges in spätantiken Religionskulturen: griechisch-römische Religion, Judentum und Christentum. Terminologien, Handlungen und Reflexionen in Bezug auf Heiliges werden in ihrem jeweiligen religiösen Bezugssystem thematisiert, aber darüber hinaus auch miteinander ins Gespräch gebracht. Hierfür dienen Kategorien wie Zeit, Ort, Individuum und Gruppe der Zuordnung der Befunde. Besonderes Augenmerk liegt zudem auf quellensprachlichen und forschungsinternen Begrifflichkeiten von Heiligem sowie auf der geschichtlichen Dynamik von Heiligkeitsvorstellungen. Dieses interdisziplinäre Vorgehen macht Diskontinuitäten und Kontinuitäten des Diskurses über „das Heilige“ in der Vielfalt seiner Erscheinungsformen präziser als bisher identifizierbar.

Predicting dependencies using domain-based coupling

Software dependencies play a vital role in programme comprehension, change impact analysis and other software maintenance activities. Traditionally, these activities are supported by source code analysis; however, the source code is sometimes inaccessible or difficult to analyse, as in hybrid systems composed of source code in multiple languages using various paradigms (e.g. object-oriented programming and relational databases). Moreover, not all stakeholders have adequate knowledge to perform such analyses. For example, non-technical domain experts and consultants raise most maintenance requests; however, they cannot predict the cost and impact of the requested changes without the support of the developers. We propose a novel approach to predicting software dependencies by exploiting the coupling present in domain-level information. Our approach is independent of the software implementation; hence, it can be used to approximate architectural dependencies without access to the source code or the database. As such, it can be applied to hybrid systems with heterogeneous source code or legacy systems with missing source code. In addition, this approach is based solely on information visible and understandable to domain users; therefore, it can be efficiently used by domain experts without the support of software developers. We evaluate our approach with a case study on a large-scale enterprise system, in which we demonstrate how up to 65 of the source code dependencies and 77% of the database dependencies are predicted solely based on domain information.

How Do Software Architects Specify and Validate Quality Requirements?

Software architecture is the result of a design effort aimed at ensuring a certain set of quality attributes. As we show, quality requirements are commonly specified in practice but are rarely validated using automated techniques. In this paper we analyze and classify commonly specified quality requirements after interviewing professionals and running a survey. We report on tools used to validate those requirements and comment on the obstacles encountered by practitioners when performing such activity (e.g., insufficient tool-support; poor understanding of users needs). Finally we discuss opportunities for increasing the adoption of automated tools based on the information we collected during our study (e.g., using a business-readable notation for expressing quality requirements; increasing awareness by monitoring non-functional aspects of a system).

Dicto: A Unified DSL for Testing Architectural Rules

Software architecture consists of a set of design choices that can be partially expressed in form of rules that the implementation must conform to. Architectural rules are intended to ensure properties that fulfill fundamental non-functional requirements. Verifying architectural rules is often a non- trivial activity: available tools are often not very usable and support only a narrow subset of the rules that are commonly specified by practitioners. In this paper we present a new highly-readable declarative language for specifying architectural rules. With our approach, users can specify a wide variety of rules using a single uniform notation. Rules can get tested by third-party tools by conforming to pre-defined specification templates. Practitioners can take advantage of the capabilities of a growing number of testing tools without dealing with them directly.

Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

Dicto: Keeping Software Architecture Under Control

Dicto is a declarative language for specifying architectural rules using a single uniform notation. Once defined, rules can automatically be validated using adapted off-the-shelf tools.

A Quantitative Analysis of Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of information needs of software developers who work in projects that are part of larger ecosystems. This work is based on a quantitative survey of 75 professional software developers. We corroborate the results identified in the sur- vey with needs and motivations proposed in a previous sur- vey and discover that tool support for developers working in an ecosystem context is even more meager than we thought: mailing lists and internet search are the most popular tools developers use to satisfy their ecosystem-related information needs.

Top-Down Parsing with Parsing Contexts

The domain of context-free languages has been extensively explored and there exist numerous techniques for parsing (all or a subset of) context-free languages. Unfortunately, some programming languages are not context-free. Using standard context-free parsing techniques to parse a context-sensitive programming language poses a considerable challenge. Im- plementors of programming language parsers have adopted various techniques, such as hand-written parsers, special lex- ers, or post-processing of an ambiguous parser output to deal with that challenge. In this paper we suggest a simple extension of a top-down parser with contextual information. Contrary to the tradi- tional approach that uses only the input stream as an input to a parsing function, we use a parsing context that provides ac- cess to a stream and possibly to other context-sensitive infor- mation. At a same time we keep the context-free formalism so a grammar definition stays simple without mind-blowing context-sensitive rules. We show that our approach can be used for various purposes such as indent-sensitive parsing, a high-precision island parsing or XML (with arbitrary el- ement names) parsing. We demonstrate our solution with PetitParser, a parsing-expression grammar based, top-down, parser combinator framework written in Smalltalk.

Bounded Seas: Island Parsing Without Shipwrecks

Imprecise manipulation of source code (semi-parsing) is useful for tasks such as robust parsing, error recovery, lexical analysis, and rapid development of parsers for data extraction. An island grammar precisely defines only a subset of a language syntax (islands), while the rest of the syntax (water) is defined imprecisely. Usually, water is defined as the negation of islands. Albeit simple, such a definition of water is naive and impedes composition of islands. When developing an island grammar, sooner or later a programmer has to create water tailored to each individual island. Such an approach is fragile, however, because water can change with any change of a grammar. It is time-consuming, because water is defined manually by a programmer and not automatically. Finally, an island surrounded by water cannot be reused because water has to be defined for every grammar individually. In this paper we propose a new technique of island parsing - bounded seas. Bounded seas are composable, robust, reusable and easy to use because island-specific water is created automatically. We integrated bounded seas into a parser combinator framework as a demonstration of their composability and reusability.

Mining frequent bug-fix code changes

Detecting bugs as early as possible plays an important role in ensuring software quality before shipping. We argue that mining previous bug fixes can produce good knowledge about why bugs happen and how they are fixed. In this paper, we mine the change history of 717 open source projects to extract bug-fix patterns. We also manually inspect many of the bugs we found to get insights into the contexts and reasons behind those bugs. For instance, we found out that missing null checks and missing initializations are very recurrent and we believe that they can be automatically detected and fixed.

Towards Faster Method Search Through Static Ecosystem Analysis

Software developers are often unsure of the exact name of the method they need to use to invoke the desired behavior in a given context. This results in a process of searching for the correct method name in documentation, which can be lengthy and distracting to the developer. We can decrease the method search time by enhancing the documentation of a class with the most frequently used methods. Usage frequency data for methods is gathered by analyzing other projects from the same ecosystem - written in the same language and sharing dependencies. We implemented a proof of concept of the approach for Pharo Smalltalk and Java. In Pharo Smalltalk, methods are commonly searched for using a code browser tool called "Nautilus", and in Java using a web browser displaying HTML based documentation - Javadoc. We developed plugins for both browsers and gathered method usage data from open source projects, in order to increase developer productivity by reducing method search time. A small initial evaluation has been conducted showing promising results in improving developer productivity.

Overthrowing the Tyranny of Alphabetical Ordering in Documentation Systems

Software developers are often unsure of the exact name of the API method they need to use to invoke the desired behavior. Most state-of-the-art documentation browsers present API artefacts in alphabetical order. Albeit easy to implement, alphabetical order does not help much: if the developer knew the name of the required method, he could have just searched for it in the first place. In a context where multiple projects use the same API, and their source code is available, we can improve the API presentation by organizing the elements in the order in which they are more likely to be used by the developer. Usage frequency data for methods is gathered by analyzing other projects from the same ecosystem and this data is used then to improve tools. We present a preliminary study on the potential of this approach to improve the API presentation by reducing the time it takes to find the method that implements a given feature. We also briefly present our experience with two proof-of-concept tools implemented for Smalltalk and Java.

Mining the Ecosystem to Improve Type Inference For Dynamically Typed Languages

Dynamically typed languages lack information about the types of variables in the source code. Developers care about this information as it supports program comprehension. Ba- sic type inference techniques are helpful, but may yield many false positives or negatives. We propose to mine information from the software ecosys- tem on how frequently given types are inferred unambigu- ously to improve the quality of type inference for a single system. This paper presents an approach to augment existing type inference techniques by supplementing the informa- tion available in the source code of a project with data from other projects written in the same language. For all available projects, we track how often messages are sent to instance variables throughout the source code. Predictions for the type of a variable are made based on the messages sent to it. The evaluation of a proof-of-concept prototype shows that this approach works well for types that are sufficiently popular, like those from the standard librarie, and tends to create false positives for unpopular or domain specific types. The false positives are, in most cases, fairly easily identifiable. Also, the evaluation data shows a substantial increase in the number of correctly inferred types when compared to the non-augmented type inference.

IL-9 and its receptor are predominantly involved in the pathogenesis of UC.

OBJECTIVE Several pathogenic roles attributed over the past two decades to either T helper (Th)1 or Th2 cells are increasingly becoming associated with interleukin (IL)-17 and most recently IL-9 signalling. However, the implication of IL-9 in IBD has not been addressed so far. DESIGN We investigated the expression of IL-9 and IL-9R by using peripheral blood, biopsies and surgical samples. We addressed the functional role of IL-9 signalling by analysis of downstream effector proteins. Using Caco-2 cell monolayers we followed the effect of IL-9 on wound healing. RESULTS IL-9 mRNA expression was significantly increased in inflamed samples from patients with UC as compared with controls. CD3(+) T cells were major IL-9-expressing cells and some polymorphonuclear leucocytes (PMN) also expressed IL-9. IL-9 was co-localised with the key Th9 transcription factors interferon regulatory factor 4 and PU.1. Systemically, IL-9 was abundantly produced by activated peripheral blood lymphocytes, whereas its receptor was overexpressed on gut resident and circulating PMN. IL-9 stimulation of the latter induced IL-8 production in a dose-dependent manner and rendered PMN resistant to apoptosis suggesting a functional role for IL-9R signalling in the propagation of gut inflammation. Furthermore, IL-9R was overexpressed on gut epithelial cells and IL-9 induced STAT5 activation in these cells. Moreover, IL-9 inhibited the growth of Caco-2 epithelial cell monolayers in wound healing experiments. CONCLUSIONS Our results provide evidence that IL-9 is predominantly involved in the pathogenesis of UC suggesting that targeting IL-9 might become a therapeutic option for patients with UC.