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We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance.
In this talk, I would like to share my experiences gained from participating in four CSP solver competitions and the second ASP solver competition. In particular, I’ll talk about how various programming techniques can make huge differences in solving some of the benchmark problems used in the competitions. These techniques include global constraints, table constraints, and problem-specific propagators and labeling strategies for selecting variables and values. I’ll present these techniques with experimental results from B-Prolog and other CLP(FD) systems.
The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Component based software development (CBSD) and aspectoriented software development (AOSD) are two complementary approaches. However, existing proposals for integrating aspects into component models are direct transposition of object-oriented AOSD techniques to components. In this article, we propose a new approach based on views. Our proposal introduces crosscutting components quite naturally and can be integrated into different component models.
Despite the phenomenal growth of Big Data Analytics in the last few years, little research is done to explicate the relationship between Big Data Analytics Capability (BDAC) and indirect strategic value derived from such digital capabilities. We attempt to address this gap by proposing a conceptual model of the BDAC - Innovation relationship using dynamic capability theory. The work expands on BDAC business value research and extends the nominal research done on BDAC – innovation. We focus on BDAC's relationship with different innovation objects, namely product, business process, and business model innovation, impacting all value chain activities. The insights gained will stimulate academic and practitioner interest in explicating strategic value generated from BDAC and serve as a framework for future research on the subject
Different properties of programs, implemented in Constraint Handling Rules (CHR), have already been investigated. Proving these properties in CHR is fairly simpler than proving them in any type of imperative programming language, which triggered the proposal of a methodology to map imperative programs into equivalent CHR. The equivalence of both programs implies that if a property is satisfied for one, then it is satisfied for the other. The mapping methodology could be put to other beneficial uses. One such use is the automatic generation of global constraints, at an attempt to demonstrate the benefits of having a rule-based implementation for constraint solvers.
Because software development is increasingly expensive and timeconsuming, software reuse gains importance. Aspect-oriented software development modularizes crosscutting concerns which enables their systematic reuse. Literature provides a number of AOP patterns and best practices for developing reusable aspects based on compelling examples for concerns like tracing, transactions and persistence. However, such best practices are lacking for systematically reusing invasive aspects. In this paper, we present the ‘callback mismatch problem’. This problem arises in the context of abstraction mismatch, in which the aspect is required to issue a callback to the base application. As a consequence, the composition of invasive aspects is cumbersome to implement, difficult to maintain and impossible to reuse. We motivate this problem in a real-world example, show that it persists in the current state-of-the-art, and outline the need for advanced aspectual composition mechanisms to deal with this.
The devil in disguise
(2021)
Envy constitutes a serious issue on Social Networking Sites (SNSs), as this painful emotion can severely diminish individuals' well-being. With prior research mainly focusing on the affective consequences of envy in the SNS context, its behavioral consequences remain puzzling. While negative interactions among SNS users are an alarming issue, it remains unclear to which extent the harmful emotion of malicious envy contributes to these toxic dynamics. This study constitutes a first step in understanding malicious envy’s causal impact on negative interactions within the SNS sphere. Within an online experiment, we experimentally induce malicious envy and measure its immediate impact on users’ negative behavior towards other users. Our findings show that malicious envy seems to be an essential factor fueling negativity among SNS users and further illustrate that this effect is especially pronounced when users are provided an objective factor to mask their envy and justify their norm-violating negative behavior.
The interest in extensions of the logic programming paradigm beyond the class of normal logic programs is motivated by the need of an adequate representation and processing of knowledge. One of the most difficult problems in this area is to find an adequate declarative semantics for logic programs. In the present paper a general preference criterion is proposed that selects the ‘intended’ partial models of generalized logic programs which is a conservative extension of the stationary semantics for normal logic programs of [Prz91]. The presented preference criterion defines a partial model of a generalized logic program as intended if it is generated by a stationary chain. It turns out that the stationary generated models coincide with the stationary models on the class of normal logic programs. The general wellfounded semantics of such a program is defined as the set-theoretical intersection of its stationary generated models. For normal logic programs the general wellfounded semantics equals the wellfounded semantics.
Deductive databases need general formulas in rule bodies, not only conjuctions of literals. This is well known since the work of Lloyd and Topor about extended logic programming. Of course, formulas must be restricted in such a way that they can be effectively evaluated in finite time, and produce only a finite number of new tuples (in each iteration of the TP-operator: the fixpoint can still be infinite). It is also necessary to respect binding restrictions of built-in predicates: many of these predicates can be executed only when certain arguments are ground. Whereas for standard logic programming rules, questions of safety, allowedness, and range-restriction are relatively easy and well understood, the situation for general formulas is a bit more complicated. We give a syntactic analysis of formulas that guarantees the necessary properties.
Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic “Operating the Cloud”. Our goal is to provide a forum for the exchange of knowledge and experience between industry and academia. Hence, HPI’s Future SOC Lab is the adequate environment to host this event which is also supported by BITKOM.
On the occasion of this workshop we called for submissions of research papers and practitioners’ reports. “Operating the Cloud” aims to be a platform for productive discussions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration.
In this workshop proceedings the results of the second HPI cloud symposium "Operating the Cloud" 2014 are published. We thank the authors for exciting presentations and insights into their current work and research. Moreover, we look forward to more interesting submissions for the upcoming symposium in 2015.
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. The 23rd WLP was held in Potsdam at September 15 – 16, 2009. The topics of the presentations of WLP2009 were grouped into the major areas: Databases, Answer Set Programming, Theory and Practice of Logic Programming as well as Constraints and Constraint Handling Rules.
Aspect-oriented middleware is a promising technology for the realisation of dynamic reconfiguration in heterogeneous distributed systems. However, like other dynamic reconfiguration approaches, AO-middleware-based reconfiguration requires that the consistency of the system is maintained across reconfigurations. AO-middleware-based reconfiguration is an ongoing research topic and several consistency approaches have been proposed. However, most of these approaches tend to be targeted at specific contexts, whereas for distributed systems it is crucial to cover a wide range of operating conditions. In this paper we propose an approach that offers distributed, dynamic reconfiguration in a consistent manner, and features a flexible framework-based consistency management approach to cover a wide range of operating conditions. We evaluate our approach by investigating the configurability and transparency of our approach and also quantify the performance overheads of the associated consistency mechanisms.
Preface
(2010)
Aspect-oriented programming, component models, and design patterns are modern and actively evolving techniques for improving the modularization of complex software. In particular, these techniques hold great promise for the development of "systems infrastructure" software, e.g., application servers, middleware, virtual machines, compilers, operating systems, and other software that provides general services for higher-level applications. The developers of infrastructure software are faced with increasing demands from application programmers needing higher-level support for application development. Meeting these demands requires careful use of software modularization techniques, since infrastructural concerns are notoriously hard to modularize. Aspects, components, and patterns provide very different means to deal with infrastructure software, but despite their differences, they have much in common. For instance, component models try to free the developer from the need to deal directly with services like security or transactions. These are primary examples of crosscutting concerns, and modularizing such concerns are the main target of aspect-oriented languages. Similarly, design patterns like Visitor and Interceptor facilitate the clean modularization of otherwise tangled concerns. Building on the ACP4IS meetings at AOSD 2002-2009, this workshop aims to provide a highly interactive forum for researchers and developers to discuss the application of and relationships between aspects, components, and patterns within modern infrastructure software. The goal is to put aspects, components, and patterns into a common reference frame and to build connections between the software engineering and systems communities.
Preface
(2010)
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. In this decade, previous workshops took place in Dresden (2008), Würzburg (2007), Vienna (2006), Ulm (2005), Potsdam (2004), Dresden (2002), Kiel (2001), and Würzburg (2000). Contributions to workshops deal with all theoretical, experimental, and application aspects of constraint programming (CP) and logic programming (LP), including foundations of constraint/ logic programming. Some of the special topics are constraint solving and optimization, extensions of functional logic programming, deductive databases, data mining, nonmonotonic reasoning, , interaction of CP/LP with other formalisms like agents, XML, JAVA, program analysis, program transformation, program verification, meta programming, parallelism and concurrency, answer set programming, implementation and software techniques (e.g., types, modularity, design patterns), applications (e.g., in production, environment, education, internet), constraint/logic programming for semantic web systems and applications, reasoning on the semantic web, data modelling for the web, semistructured data, and web query languages.
A wide range of additional forward chaining applications could be realized with deductive databases, if their rule formalism, their immediate consequence operator, and their fixpoint iteration process would be more flexible. Deductive databases normally represent knowledge using stratified Datalog programs with default negation. But many practical applications of forward chaining require an extensible set of user–defined built–in predicates. Moreover, they often need function symbols for building complex data structures, and the stratified fixpoint iteration has to be extended by aggregation operations. We present an new language Datalog*, which extends Datalog by stratified meta–predicates (including default negation), function symbols, and user–defined built–in predicates, which are implemented and evaluated top–down in Prolog. All predicates are subject to the same backtracking mechanism. The bottom–up fixpoint iteration can aggregate the derived facts after each iteration based on user–defined Prolog predicates.
In the most abstract definition of its operational semantics, the declarative and concurrent programming language CHR is trivially non-terminating for a significant class of programs. Common refinements of this definition, in closing the gap to real-world implementations, compromise on declarativity and/or concurrency. Building on recent work and the notion of persistent constraints, we introduce an operational semantics avoiding trivial non-termination without compromising on its essential features.
A constraint programming system combines two essential components: a constraint solver and a search engine. The constraint solver reasons about satisfiability of conjunctions of constraints, and the search engine controls the search for solutions by iteratively exploring a disjunctive search tree defined by the constraint program. The Monadic Constraint Programming framework gives a monadic definition of constraint programming where the solver is defined as a monad threaded through the monadic search tree. Search and search strategies can then be defined as firstclass objects that can themselves be built or extended by composable search transformers. Search transformers give a powerful and unifying approach to viewing search in constraint programming, and the resulting constraint programming system is first class and extremely flexible.
Openness indicators for the evaluation of digital platforms between the launch and maturity phase
(2024)
In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation.
The metaverse is envisioned as a virtual shared space facilitated by emerging technologies such as virtual reality (VR), augmented reality (AR), the Internet of Things (IoT), 5G, artificial intelligence (AI), big data, spatial computing, and digital twins (Allam et al., 2022; Dwivedi et al., 2022; Ravenscraft, 2022; Wiles, 2022). While still a nascent concept, the metaverse has the potential to “transform the physical world, as well as transport or extend physical activities to a virtual world” (Wiles, 2022). Big data technologies will also be essential in managing the enormous amounts of data created in the metaverse (Sun et al., 2022). Metaverse technologies can offer the public sector a host of benefits, such as simplified information exchange, stronger communication with citizens, better access to public services, or benefiting from a new virtual economy. Implementations are underway in several cities around the world (Geraghty et al., 2022). In this paper, we analyze metaverse opportunities for the public sector and explore their application in the context of Germany’s Federal Employment Agency. Based on an analysis of academic literature and practical examples, we create a capability map for potential metaverse business capabilities for different areas of the public sector (broadly defined). These include education (virtual training and simulation, digital campuses that offer not just online instruction but a holistic university campus experience, etc.), tourism (virtual travel to remote locations and museums, virtual festival participation, etc.), health (employee training – as for emergency situations, virtual simulations for patient treatment – for example, for depression or anxiety, etc.), military (virtual training to experience operational scenarios without being exposed to a real-world threats, practice strategic decision-making, or gain technical knowledge for operating and repairing equipment, etc.), administrative services (document processing, virtual consultations for citizens, etc.), judiciary (AI decision-making aids, virtual proceedings, etc.), public safety (virtual training for procedural issues, special operations, or unusual situations, etc.), emergency management (training for natural disasters, etc.), and city planning (visualization of future development projects and interactive feedback, traffic management, attraction gamification, etc.), among others. We further identify several metaverse application areas for Germany's Federal Employment Agency. These applications can help it realize the goals of the German government for digital transformation that enables faster, more effective, and innovative government services. They include training of employees, training of customers, and career coaching for customers. These applications can be implemented using interactive learning games with AI agents, virtual representations of the organizational spaces, and avatars interacting with each other in these spaces. Metaverse applications will both use big data (to design the virtual environments) and generate big data (from virtual interactions). Issues related to data availability, quality, storage, processing (and related computing power requirements), interoperability, sharing, privacy and security will need to be addressed in these emerging metaverse applications (Sun et al., 2022). Special attention is needed to understand the potential for power inequities (wealth inequity, algorithmic bias, digital exclusion) due to technologies such as VR (Egliston & Carter, 2021), harmful surveillance practices (Bibri & Allam, 2022), and undesirable user behavior or negative psychological impacts (Dwivedi et al., 2022). The results of this exploratory study can inform public sector organizations of emerging metaverse opportunities and enable them to develop plans for action as more of the metaverse technologies become a reality. While the metaverse body of research is still small and research agendas are only now starting to emerge (Dwivedi et al., 2022), this study offers a building block for future development and analysis of metaverse applications.