Expressive Languages Research Articles

On the Expressive Power of Languages for Static Variability

Variability permeates software development to satisfy ever-changing requirements and mass-customization needs. A prime example is the Linux kernel, which employs the C preprocessor to specify a set of related but distinct kernel variants. To study, analyze, and verify variational software, several formal languages have been proposed. For example, the choice calculus has been successfully applied for type checking and symbolic execution of configurable software, while other formalisms have been used for variational model checking, change impact analysis, among other use cases. Yet, these languages have not been formally compared, hence, little is known about their relationships. Crucially, it is unclear to what extent one language subsumes another, how research results from one language can be applied to other languages, and which language is suitable for which purpose or domain. In this paper, we propose a formal framework to compare the expressive power of languages for static (i.e., compile-time) variability. By establishing a common semantic domain to capture a widely used intuition of explicit variability, we can formulate the basic, yet to date neglected, properties of soundness, completeness, and expressiveness for variability languages. We then prove the (un)soundness and (in)completeness of a range of existing languages, and relate their ability to express the same variational systems. We implement our framework as an extensible open source Agda library in which proofs act as correct compilers between languages or differencing algorithms. We find different levels of expressiveness as well as complete and incomplete languages w.r.t. our unified semantic domain, with the choice calculus being among the most expressive languages.

Modular Synthesis of Efficient Quantum Uncomputation

A key challenge of quantum programming is uncomputation: the reversible deallocation of qubits. And while there has been much recent progress on automating uncomputation, state-of-the-art methods are insufficient for handling today’s expressive quantum programming languages. A core reason is that they operate on primitive quantum circuits, while quantum programs express computations beyond circuits, for instance, they can capture families of circuits defined recursively in terms of uncomputation and adjoints. In this paper, we introduce the first modular automatic approach to synthesize correct and efficient uncomputation for expressive quantum programs. Our method is based on two core technical contributions: (i) an intermediate representation (IR) that can capture expressive quantum programs and comes with support for uncomputation, and (ii) modular algorithms over that IR for synthesizing uncomputation and adjoints. We have built a complete end-to-end implementation of our method, including an implementation of the IR and the synthesis algorithms, as well as a translation from an expressive fragment of the Silq programming language to our IR and circuit generation from the IR. Our experimental evaluation demonstrates that we can handle programs beyond the capabilities of existing uncomputation approaches, while being competitive on the benchmarks they can handle. More broadly, we show that it is possible to benefit from the greater expressivity and safety offered by high-level quantum languages without sacrificing efficiency.

On the expressiveness and efficiency of guarded lists in Bach

Concurrency theory has received considerable attention, but mostly in the scope of synchronous process algebras such as CCS, CSP, and ACP. As another way of handling concurrency, data-based coordination languages aim to provide a clear separation between interaction and computation by synchronizing processes asynchronously by means of information being available or not on a shared space. Although these languages enjoy interesting properties, verifying program correctness remains challenging. In particular, model checking logic formulae is known to raise performance issues due to the state space explosion problem. In this paper, we propose a guarded list construct as a solution to address this problem. Beyond increasing performance, it also enriches the expressiveness of data-based coordination languages and allows for program transformations that further increase the speed of computations.

Expressiveness of Pastoral Language in the Use of Idioms in the Press

Expressiveness of Pastoral Language in the Use of Idioms in the Press

AMD: Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion

Generating realistic human motion sequences from text descriptions is a challenging task that requires capturing the rich expressiveness of both natural language and human motion. Recent advances in diffusion models have enabled significant progress in human motion synthesis. However, existing methods struggle to handle text inputs that describe complex or long motions. In this paper, we propose the Adaptable Motion Diffusion (AMD) model, which leverages a Large Language Model (LLM) to parse the input text into a sequence of concise and interpretable anatomical scripts that correspond to the target motion. This process exploits the LLM’s ability to provide anatomical guidance for complex motion synthesis. We then devise a two-branch fusion scheme that balances the influence of the input text and the anatomical scripts on the inverse diffusion process, which adaptively ensures the semantic fidelity and diversity of the synthesized motion. Our method can effectively handle texts with complex or long motion descriptions, where existing methods often fail. Experiments on datasets with relatively more complex motions, such as CLCD1 and CLCD2, demonstrate that our AMD significantly outperforms existing state-of-the-art models.

On the Expressivity of Recurrent Neural Cascades

Recurrent Neural Cascades (RNCs) are the recurrent neural networks with no cyclic dependencies among recurrent neurons. This class of recurrent networks has received a lot of attention in practice. Besides training methods for a fixed architecture such as backpropagation, the cascade architecture naturally allows for constructive learning methods, where recurrent nodes are added incrementally one at a time, often yielding smaller networks. Furthermore, acyclicity amounts to a structural prior that even for the same number of neurons yields a more favourable sample complexity compared to a fully-connected architecture. A central question is whether the advantages of the cascade architecture come at the cost of a reduced expressivity. We provide new insights into this question. We show that the regular languages captured by RNCs with sign and tanh activation with positive recurrent weights are the star-free regular languages. In order to establish our results we developed a novel framework where capabilities of RNCs are assessed by analysing which semigroups and groups a single neuron is able to implement. A notable implication of our framework is that RNCs can achieve the expressivity of all regular languages by introducing neurons that can implement groups.

Livestreaming commerce service quality measurement and its effect on swift guanxi, trust, and repurchase intention

Livestreaming commerce is an important emerging technology that has not been systematically investigated in service marketing research. This study aims to develop livestreaming commerce service quality (LSCSQ) measures and explores the impact of LSCSQ on repurchase intention from swift guanxi and trust perspectives. Four phases are conducted to measure and validate LSCSQ, including item generation, item purification, scale validation, and nomological validity testing. Three rounds of online survey by distributing questionnaires on the Wenjuanxing platform were conducted to collect data. Customers with livestreaming commerce service experience were selected and invited randomly to finish questionnaire. The valid samples in the first, second, and third rounds were 376, 264, and 308 respectively. SPSS 25.0 and SmartPLS 3.0 were employed to analyse data in this study. The results show that cues multiplicity, scene visibility, personalisation, informational fit-to-task, efficiency, empathy, real-time interactivity, language expressiveness, and edutainment are the measurements of LSCSQ. Moreover, LSCSQ positively influence repurchase intention by building swift guanxi and improving trust. This study contributes to the service quality and livestreaming commerce literature and provides theoretical tools for livestreaming retailers to improve their service quality by adopting better targeted strategy.

Sound Runtime Assertion Checking for Memory Properties via Program Transformation

Runtime Assertion Checking (RAC) for expressive specification languages is a non-trivial verification task that becomes even more complex for memory-related properties of imperative languages with dynamic memory allocation. It is important to ensure the soundness of RAC verdicts, in particular when RAC reports the absence of failures for execution traces. This article presents a formalization of a program transformation technique for RAC of memory properties for a representative language with pointers and memory operations, including dynamic allocation and deallocation. The generated program instrumentation relies on an axiomatized observation memory model, which is essential to record and monitor memory-related properties. We prove the soundness of RAC verdicts with regard to the semantics of this language.

Call combination in African forest elephants Loxodonta cyclotis.

Syntax, the combination of meaning-devoid phonemes into meaningful words, which in turn are combined in structurally and semantically complex sentences, is fundamental to the unlimited expressiveness of human languages. Studying the functions of call combinations in non-human species provides insights into the evolution of such syntactic capabilities. Here, we investigated the combination of high amplitude broadband calls with low frequency rumble vocalizations in a highly social species, the African forest elephant Loxodonta cyclotis. Rumbles play an integral role in coordinating social interactions by transmitting socially relevant information, including individual identity. By contrast, broadband calls, such as roars, are thought to function as signals of distress and urgency as they are typically produced in situations of high emotional intensity. Functional changes associated with the combination of these calls remain little understood. We found that call combinations were produced by all age-sex classes but were most prevalent in immature individuals. We found that rumbles used singularly occurred in all five investigated social contexts, whereas single broadband calls were restricted to two resource-related contexts. Call combinations also occurred in all five contexts, suggesting an increase in the functional use of broadband calls when combined with rumbles, analogous to the generativity brought about through syntax in human speech. Moreover, combining calls appeared to lead to functional shifts towards high-stake contexts. Call combinations were more likely in competition contexts compared to single rumbles, and more likely in separation contexts compared to single broadband calls. We suggest that call combination in forest elephants may aide to reduce message ambiguity in high-stake situation by simultaneously communicating distress and individual identity, which may be critical to secure access to resources, reduce the risk of injury and to reunite with or recruit the support of the family group.

On The Reasonable Effectiveness of Relational Diagrams: Explaining Relational Query Patterns and the Pattern Expressiveness of Relational Languages

Comparing relational languages by their logical expressiveness is well understood. Less well understood is how to compare relational languages by their ability to represent relational query patterns. Indeed, what are query patterns other than "a certain way of writing a query"? And how can query patterns be defined across procedural and declarative languages, irrespective of their syntax? To the best of our knowledge, we provide the first semantic definition of relational query patterns by using a variant of structure-preserving mappings between the relational tables of queries. This formalism allows us to analyze the relative pattern expressiveness of relational language fragments and create a hierarchy of languages with equal logical expressiveness yet different pattern expressiveness. Notably, for the non-disjunctive language fragment, we show that relational calculus can express a larger class of patterns than the basic operators of relational algebra. Our language-independent definition of query patterns opens novel paths for assisting database users. For example, these patterns could be leveraged to create visual query representations that faithfully represent query patterns, speed up interpretation, and provide visual feedback during query editing. As a concrete example, we propose Relational Diagrams, a complete and sound diagrammatic representation of safe relational calculus that is provably (i) unambiguous, (ii) relationally complete, and (iii) able to represent all query patterns for unions of non-disjunctive queries. Among all diagrammatic representations for relational queries that we are aware of, ours is the only one with these three properties. Furthermore, our anonymously preregistered user study shows that Relational Diagrams allow users to recognize patterns meaningfully faster and more accurately than SQL.

ФРАЗЕОЛОГИЧЕСКИЕ ЕДИНИЦЫ ТАДЖИКСКОГО ЯЗЫКА, СВЯЗАННЫЕ С ОБОЗНАЧЕНИЕМ ТРУДА И ТРУДОВОЙ ДЕЯТЕЛЬНОСТИ

This article discusses the role of phraseology in the Tajik language as an important element of language culture. Phraseological expressions reflect the history, culture, and way of life of language speakers, enriching the lexicon and giving the language depth and expressiveness. The use of idiomatic expressions contributes to the development of the aesthetic aspect of the language.

Композити як засіб створення експресивності та їх функціювання в англійськомовних текстах

The article is devoted to the consideration and analysis of lexical expressiveness and composites as a means of its actualization. A distinction is made between different approaches to understanding the category of expressiveness, including stylistic, pragmatic, functional, and semantic ones. Among the main types of lexical expressiveness in the English language, inherent and adherent expressiveness were distinguished. Attention is paid to the correlation of neutral and expressively marked vocabulary in the modern English language. The vocabulary selected in the study includes lexical units of different parts of speech (nouns, adjectives, adverbs, verbs), since the phenomenon of expressiveness is not determined by belonging to a certain part of speech, and almost every unit can acquire an expressive tone. It was determined that the formation of language units with inherent explicit expressiveness is facilitated by composition. Special attention is paid to the model of composition of neutral nouns that is the most productive among expressive composites. The peculiarity of this model realises when compound the bases of words, not their neutral meanings, but their secondary ones, which have historically developed from the main meanings through metaphorization, metonymization, and partial de-semantization, are often realized. That is why compound nouns are characterized by their high stylization, their emotional and expressive character is emphasized. Adherent expressiveness of words is formed on the basis of metaphorization. Expressiveness can vary depending on the area of knowledge and communication situation, as well as depending on the type of text. Adherent expressiveness is predominant in modern English. It is confirmed that the adherent and inherent expressiveness of journalistic and fiction works are clearly expressed with the help of expressively marked lexical units.

Ontology-Based AI Design Patterns and Constraints in Cancer Registry Data Validation.

Data validation in cancer registration is a critical operation but is resource-intensive and has traditionally depended on proprietary software. Ontology-based AI is a novel approach utilising machine reasoning based on axioms formally described in description logic. This is a different approach from deep learning AI techniques but not exclusive of them. The advantage of the ontology approach lies in its ability to address a number of challenges concurrently. The disadvantages relate to computational costs, which increase with language expressivity and the size of data sets, and class containment restrictions imposed by description logics. Both these aspects would benefit from the availability of design patterns, which is the motivation behind this study. We modelled the European cancer registry data validation rules in description logic using a number of design patterns and showed the viability of the approach. Reasoning speeds are a limiting factor for large cancer registry data sets comprising many hundreds of thousands of records, but these can be offset to a certain extent by developing the ontology in a modular way. Data validation is also a highly parallelisable process. Important potential future work in this domain would be to identify and optimise reusable design patterns, paying particular attention to avoiding any unintended reasoning efficiency hotspots.

FIGURATIVE LANGUAGE: A KEY TO UNDERSTANDING IN TAYLOR SWIFT'S "ENCHANTED" LYRICS.

One of the best literary forms is a song. Another crucial fact to be aware of is that a song is a small piece of rhyming music that contains the songwriter's fantasies, ideas, illusions, and messages for the listener. Figurative language is used in song lyrics to help the reader understand the messages being conveyed. Additionally, the purpose of the current study is to identify the figurative language used in Taylor Swift's song "Enchanted" lyrics. The authors employed a descriptive qualitative study approach that included metaphors (379%) and other literary devices such as alliteration ( 21,6%), hyperbole (16,2%), personification (13,5% ), simile (5,4%) and irony (5,4%). The use of figurative language as a non-literal or idiomatic form of expression could increase learners' vocabulary and improve their language's expressiveness and proximity to their feelings.

Teaching the Russian literary language to foreign master and postgraduate students within the special course “Modern Russian literature”: key problems and prospects

The article puts insight into current issues of teaching the Russian literary language to foreign under-graduates and postgraduates, specializing in “Linguistics and Intercultural Communication”, in the course of studying “Modern Russian Literature”. We use a broad historical and cultural context to substantiate the fundamental role of Russian literature in the formation of world culture and the global literary canon, and highlight the great influence that such Russian classical writers as Pushkin, Dostoevsky, Tolstoy, Turgenev and Chekhov had on the development of foreign literature in the East and West. We observe and trace continuity in classical and modern literary eras and the best long-lasting spiritual, moral and linguistic traditions of the Russian people. We assume that the key problems the teacher should focus on are: Russian literature as a significant phenomenon of world culture, the development of classical traditions in the history of Russian literature at present, the dialogue among cultures and the translation of modern writers’ works into foreign languages, historical and philosophical problems in literature, and historical heritage of the Russian language. The article comprehensively studies the Russian language value dimensions and linguistic axiological directions. The data show the presence, stability and preservation of the fundamental values (life, love, truth, good, beauty, hope, grace, honour, etc.) in the Russian literary language. These values form the spiritual conceptual sphere in Russian culture and constitute its main moral foundations. Serious attention is paid to the aesthetics of the language. We show the aesthetic potential, artistic expressiveness and stylistic richness of the modern Russian literary language, based on the works of E. Vodolazkin, L. Ulitskaya, M. Shishkin, M. Kucherskaya, M. Stepnova, D. Rubina and others. We focus on the problem of preserving the Russian literary language and the high status of Russian in general, revealing complex realities of modern multinational and multicultural world. We recommend such modern masterpieces as “Laurel” by E. Vodolazkin, “The God of Rain” by M. Kucherskaya, “The Garden” by M. Stepnova, “The Writer” by M. Shishkin, “Yakov’s Staircase” by L. Ulitskaya as sources to improve literacy and general cultural competence of foreign students.

Mapping natural language procedures descriptions to linear temporal logic templates: an application in the surgical robotic domain

Natural language annotations and manuals can provide useful procedural information and relations for the highly specialized scenario of autonomous robotic task planning. In this paper, we propose and publicly release AUTOMATE, a pipeline for automatic task knowledge extraction from expert-written domain texts. AUTOMATE integrates semantic sentence classification, semantic role labeling, and identification of procedural connectors, in order to extract templates of Linear Temporal Logic (LTL) relations that can be directly implemented in any sufficiently expressive logic programming formalism for autonomous reasoning, assuming some low-level commonsense and domain-independent knowledge is available. This is the first work that bridges natural language descriptions of complex LTL relations and the automation of full robotic tasks. Unlike most recent similar works that assume strict language constraints in substantially simplified domains, we test our pipeline on texts that reflect the expressiveness of natural language used in available textbooks and manuals. In fact, we test AUTOMATE in the surgical robotic scenario, defining realistic language constraints based on a publicly available dataset. In the context of two benchmark training tasks with texts constrained as above, we show that automatically extracted LTL templates, after translation to a suitable logic programming paradigm, achieve comparable planning success in reduced time, with respect to logic programs written by expert programmers.

Programming microcontrollers through high-level abstractions: The OMicroB project

In this paper, we present an approach for programming microcontrollers that provides more expressivity and safety than the low-level language approach traditionally used to program such devices. To this end, we provide various abstraction layers (abstraction of the microcontroller, of the electronic components of the circuit, and of concurrency) which, while being adapted to the scarce resources of the hardware, offer high-level programming traits for the development of embedded applications. The various presented abstractions make use of an OCaml virtual machine, called OMicroB, which is able to run on devices with limited resources. These take advantage of the expressivity and safety of the OCaml language (parameterized modules, advanced type system). Its extensibility allows to define a synchronous extension to manage concurrency while keeping a good level of efficiency at execution. We illustrate the value of our work on both entertainment applications and embedded software examples.

DoveDB: A Declarative and Low-Latency Video Database

Concerning the usability and efficiency to manage video data generated from large-scale cameras, we demonstrate DoveDB, a declarative and low-latency video database. We devise a more comprehensive video query language called VMQL to improve the expressiveness of previous SQL-like languages, which are augmented with functionalities for model-oriented management and deployment. We also propose a light-weight ingestion scheme to extract tracklets of all the moving objects and build semantic indexes to facilitate efficient query processing. For user interaction, we construct a simulation environment with 120 cameras deployed in a road network and demonstrate three interesting scenarios. Using VMQL, users are allowed to 1) train a visual model using SQL-like statement and deploy it on dozens of target cameras simultaneously for online inference; 2) submit multi-object tracking (MOT) requests on target cameras, store the ingested results and build semantic indexes; and 3) issue an aggregation or top- k query on the ingested cameras and obtain the response within milliseconds. A preliminary video introduction of DoveDB is available at https://www.youtube.com/watch?v=N139dEyvAJk

KG-Roar: Interactive Datalog-Based Reasoning on Virtual Knowledge Graphs

Logic-based Knowledge Graphs (KGs) are gaining momentum in academia and industry thanks to the rise of expressive and efficient languages for Knowledge Representation and Reasoning (KRR). These languages accurately express business rules, through which valuable new knowledge is derived. A versatile and scalable backend reasoner, like Vadalog, a state-of-the-art system for logic-based KGs---based on an extension of Datalog---executes the reasoning. In this demo, we present KG-Roar, a web-based interactive development and navigation environment for logical KGs. The system lets the user augment an input graph database with intensional definitions of new nodes and edges and turn it into a KG, via the metaphor of reasoning widgets---user-defined or off-the-shelf code snippets that capture business definitions in the Vadalog language. Then, the user can seamlessly browse the original and the derived nodes and edges within a "Virtual Knowledge Graph", which is reasoned upon and generated interactively at runtime, thanks to the scalability and responsiveness of Vadalog. KG-Roar is domain-independent but domain aware, as exploration controls are contextually generated based on the intensional definitions. We walk the audience through KG-Roar showcasing the construction of certain business definitions and putting it into action on a real-world financial KG, from our work with the Bank of Italy.

Embodiment of Modern Graphic Images in the Artistic Experiments of Oleg Denysenko (ecoline)

The creative work of the famous Ukrainian artist Oleh Denysenko has been repeatedly recognized abroad and in Ukraine by both representatives of artistic circles and collectors. For the entire period of his artistic practice, no thorough research of his work and experimental searches in graphics has been made, nor has the artist's creative style and graphic language been described. The artist's work was mentioned in some articles, superficially revealed in studies of the creative work of representatives of the Lviv graphic school working in certain graphic techniques and trends. The figure of O. Denysenko has long occupied a significant place among the representatives of Ukrainian printmaking and graphics. This is the case when the artist and his work are more recognized abroad than in Ukraine. Denysenko is a representative of artistic techniques that have existed for more than five centuries, who is not afraid to improve, experiment, and make new searches for graphic embodiment of images and philosophical considerations. The article explores artistic practices and experiments in graphics on the example of the series of graphic works «ecoline». Attention is drawn to the process of searching for new images, methods and visual techniques, as well as to the means of revealing artistic expression. An overview of the stylization, expressiveness of the graphic language and individual manner is given. The possibility of further studying the transformation of graphic images in other techniques and plot compositions is considered. The basis of experimental searches, the emergence of figurative and symbolic interpretations, and the author's innovations are revealed.