Search

We give a domain-theoretic semantics to a statistical programming language, using the plain old category of dcpos, in contrast to some more sophisticated recent proposals. Remarkably, our monad of minimal valuations is commutative, which allows for program transformations that permute the order of independent random draws, as one would expect. A similar property is not known for Jones and Plotkin's monad of continuous valuations. Instead of working with true real numbers, we work with exact real arithmetic, providing a bridge towards possible implementations (implementations by themselves are not addressed here). Rather remarkably, we show that restricting ourselves to minimal valuations does not restrict us much: All measures on the real line can be modeled by minimal valuations on the domain IR⊥ of exact real arithmetic. We give three operational semantics for our language, and we show that they are all adequate with respect to the denotational semantics. We also explore quite a few examples to demonstrate that our semantics computes exactly as one would expect and to debunk the myth that a semantics based on continuous maps would not be expressive enough to encode measures with non-compact support using only measures with compact support, or to encode measures via non-continuous density functions, for instance. Our examples also include some useful, non-trivial cases of distributions on higher-order objects. [ABSTRACT FROM AUTHOR]

Model transformation, which is a program targeting at transforming an input model to an output model, has been a critical basis for Model-Driven Engineering (MDE). The quality of model transformation programs directly affects the quality of software products built with MDE activities. Therefore, debugging model transformation programs has been crucial from the quality assurance point of view. One of the key impediments to the model transformation debugging is the high complexity and scale of the input models. In order to ameliorate the burden on model transformation debugging, this study proposes an effective approach to systematically reduce input models of model transformation programs. By combining the advantages of input simplification approaches for traditional programs and also the characteristics of model transformation, our approach leverages and adapts the delta debugging technique to model simplification. We conduct experiments to evaluate the proposed approach from two aspects: its effectiveness in model simplification, and its effects on model transformation debugging. Our experimental results confirm the positive contributions of the approach in both aspects. It delivers promising reduction effectiveness, and it can also well support the fault localization in model transformations. [ABSTRACT FROM AUTHOR]

There are a number of structurally different fullerene cages with the same number of carbon atoms. For example, 1812 fullerene isomers C60 are possible. To date, many methods for changing the structure of fullerenes (i.e., transformations) have been developed. In this paper, one formal possible transformation is considered. It consists in sequential changes of local sections of the fullerene surface by moving an octagonal defect. A program to demonstrate the transformation of fullerene-like surfaces is described. [ABSTRACT FROM AUTHOR]

Public-private partnership (PPP) policies have been on the Turkish Government's healthcare agenda for a long time. Türkiye has implemented a series of policies with various elements of neoliberal reforms over the last 20 years and the Turkish Government initiated the PPP policy in 2013 as the final step of the Health Transformation Program. This article reviews the policy process that led to extensive collaboration with the private sector in public health and also examines the effect of the policy on the principles of public service. Türkiye's policy experience has elements that reinforce the principles of continuity, variability, and equality in many ways. However, this policy was found to have weakened the long-term financial viability of healthcare and led to its fragmentation and the government eventually abandoned this policy in the construction of new hospitals. Türkiye's experience demonstrates that governments seeking to establish sustainable PPP policies for healthcare must consider the unique dynamics inherent to public service. [ABSTRACT FROM AUTHOR]

Algorithmic paradigms such as divide-and-conquer (D&C) are proposed to guide developers in designing efficient algorithms, but it can still be difficult to apply algorithmic paradigms to practical tasks. To ease the usage of paradigms, many research efforts have been devoted to the automatic application of algorithmic paradigms. However, most existing approaches to this problem rely on syntax-based program transformations and thus put significant restrictions on the original program. In this article, we study the automatic application of D&C and several similar paradigms, denoted as D&C-like algorithmic paradigms, and aim to remove the restrictions from syntax-based transformations. To achieve this goal, we propose an efficient synthesizer, named AutoLifter, which does not depend on syntax-based transformations. Specifically, the main challenge of applying algorithmic paradigms is from the large scale of the synthesized programs, and AutoLifter addresses this challenge by applying two novel decomposition methods that do not depend on the syntax of the input program, component elimination and variable elimination, to soundly divide the whole problem into simpler subtasks, each synthesizing a sub-program of the final program and being tractable with existing synthesizers. We evaluate AutoLifter on 96 programming tasks related to six different algorithmic paradigms. AutoLifter solves 82/96 tasks with an average time cost of 20.17 s, significantly outperforming existing approaches. [ABSTRACT FROM AUTHOR]

Mainstream compilers perform a multitude of analyses and optimizations on the given input program. Each analysis (such as points-to analysis) may generate a program-abstraction (such as points-to graph). Each optimization is typically composed of multiple alternating phases of inspection of such program-abstractions and transformations of the program. Upon transformation of a program, the program-abstractions generated by various analyses may become inconsistent with the modified program. Consequently, the correctness of the downstream inspection (and consequent transformation) phases cannot be ensured until the relevant program-abstractions are stabilized; that is, the program-abstractions are either invalidated or made consistent with the modified program. In general, the existing compiler frameworks do not perform automated stabilization of the program-abstractions and instead leave it to the compiler pass writers to deal with the complex task of identifying the relevant program-abstractions to be stabilized, the points where the stabilization is to be performed, and the exact procedure of stabilization. In this article, we address these challenges by providing the design and implementation of a novel compiler-design framework called Homeostasis. Homeostasis automatically captures all the program changes performed by each transformation phase, and later, triggers the required stabilization using the captured information, if needed. We also provide a formal description of Homeostasis and a correctness proof thereof. To assess the feasibility of using Homeostasis in compilers of parallel programs, we have implemented our proposed idea in IMOP, a compiler framework for OpenMP C programs. Furthermore, to illustrate the benefits of using Homeostasis, we have implemented a set of standard data-flow passes, and a set of involved optimizations that are used to remove redundant barriers in OpenMP C programs. Implementations of none of these optimizations in IMOP required any additional lines of code for stabilization of the program-abstractions. We present an evaluation in the context of these optimizations and analyses, which demonstrates that Homeostasis is efficient and easy to use. [ABSTRACT FROM AUTHOR]

We propose Abstract Execution, a static verification framework based on symbolic execution and dynamic frames for proving properties of schematic programs. Since a schematic program may potentially represent infinitely many concrete programs, Abstract Execution can analyze infinitely many programs at once. Trading off expressiveness and automation, the framework allows proving many interesting (universal, behavioral) properties fully automatically. Its main application are correctness proofs of program transformations represented as pairs of schematic programs. We implemented Abstract Execution in a deductive verification framework and designed a graphical workbench supporting the modeling process. Abstract Execution has been applied to correct code refactoring, analysis of the cost impact of transformation rules, and parallelization of sequential code. Using our framework, we found and reported several bugs in the refactoring engines of the Java IDEs IntelliJ IDEA and Eclipse, which were acknowledged and fixed. [ABSTRACT FROM AUTHOR]

This system-level ethnographic study of a strength-based approach to transforming a national invention education program makes visible how program leadership drew on research and their own expertise to shift who and how they served. With data analysis grounded in program reports, documentation, and internal and published research, the program's developmental trajectory is (re)constructed and (re)presented with contextual details provided by program leadership to bring forward how facets of a strength-based approach informed the overtime transformation. Working in conjunction with program leadership to identify common design elements across new program offerings, this study presents this program's principles for designing for instruction and considerations for curricular integration of invention education into K-14 educational institutions. Furthermore, how these principles align with a strength-based approach are discussed. [ABSTRACT FROM AUTHOR]

Application Programming Interface (API) migration is a common task for adapting software across different programming languages and platforms, where manually constructing the mapping relations between APIs is indeed time-consuming and error-prone. To facilitate this process, many automated API mapping approaches have been proposed. However, existing approaches were mainly designed and evaluated for mapping APIs of statically-typed languages, while their performance on dynamically-typed languages remains unexplored. In this article, we conduct the first extensive study to explore existing API mapping approaches' performance for mapping APIs in dynamically-typed languages, for which we have manually constructed a high-quality dataset. According to the empirical results, we have summarized several insights. In particular, the source code implementations of APIs can significantly improve the effectiveness of API mapping. However, due to the confidentiality policy, they may not be available in practice. To overcome this, we propose a novel API mapping approach, named Matl, which leverages the transfer learning technique to learn the semantic embeddings of source code implementations from large-scale open-source repositories and then transfers the learned model to facilitate the mapping of APIs. In this way, Matl can produce more accurate API embedding of its functionality for more effective mapping without knowing the source code of the APIs. To evaluate the performance of Matl, we have conducted an extensive study by comparing Matl with state-of-the-art approaches. The results demonstrate that Matl is indeed effective as it improves the state-of-the-art approach by at least 18.36% for mapping APIs of dynamically-typed language and by 30.77% for mapping APIs of the statically-typed language. [ABSTRACT FROM AUTHOR]

Java bytecode is a quite high-level language and, as such, it is fairly easy to analyze and decompile with malicious intents, e.g., to tamper with code and skip license checks. Code obfuscation was a first attempt to mitigate malicious reverse-engineering based on static analysis. However, obfuscated code can still be dynamically analyzed with standard debuggers to perform step-wise execution and to inspect (or change) memory content at important execution points, e.g., to alter the verdict of license validity checks. Although some approaches have been proposed to mitigate debugger-based attacks, they are only applicable to binary compiled code and none address the challenge of protecting Java bytecode. In this article, we propose a novel approach to protect Java bytecode from malicious debugging. Our approach is based on automated program transformation to manipulate Java bytecode and split it into two binary processes that debug each other (i.e., a self-debugging solution). In fact, when the debugging interface is already engaged, an additional malicious debugger cannot attach. To be resilient against typical attacks, our approach adopts a series of technical solutions, e.g., an encoded channel is shared by the two processes to avoid leaking information, an authentication protocol is established to avoid Man-in-the-middle attacks, and the computation is spread between the two processes to prevent the attacker to replace or terminate either of them. We test our solution on 18 real-world Java applications, showing that our approach can effectively block the most common debugging tasks (either with the Java debugger or the GNU debugger) while preserving the functional correctness of the protected programs. While the final decision on when to activate this protection is still up to the developers, the observed performance overhead was acceptable for common desktop application domains. [ABSTRACT FROM AUTHOR]

Organizations struggle to generate more value through embracing digital transformation but are often confronted with lack of skills in this growing area. For instance, managing (digital) transformation projects requires appropriate skills to holistically plan and implement transformations. This paper outlines a set of skills that can be acquired through training programs of digital transformation projects managers. These skills are built by a working group in academia based on defined persona and then evaluated by practitioners through interviews. The outcome of the interviews indicates a general acceptance of these skills and uncovered some improvement avenues. The results of this work are expected to pave the ground for structuring training programs and building teaching content meeting actual learners and business needs. [ABSTRACT FROM AUTHOR]

Nontermination is an unwanted program property for some software systems, and a safety property for other systems. In either case, automated discovery of preconditions for nontermination is of interest. We introduce NtHorn, a fast lightweight nontermination analyser, which is able to deduce non-trivial sufficient conditions for nontermination. Using Constrained Horn Clauses (CHCs) as a vehicle, we show how established techniques for CHC program transformation and abstract interpretation can be exploited for the purpose of nontermination analysis. NtHorn is comparable in effectiveness to the state-of-the-art nontermination analysis tools, as measured on standard competition benchmark suites (consisting of integer manipulating programs), while typically solving problems faster by one order of magnitude. [ABSTRACT FROM AUTHOR]

Established companies intending to leverage digital technologies are required to innovate their 'legacy' business models through organizational transformations. Existing modeling support often leaves a 'white space' between informal canvas-style models used in the early phases and (semi-)formal aspect models used in the later phases of transformation endeavors. Adopting a Design Science Research approach, this paper presents a semi-formal model that is intended to fill this gap, i. e., to provide easy-to-use support for the heterogeneous stakeholders that participate in early phases of digital transformation endeavors. Being based on the traditional Business Engineering set of models and methods, this comprehensive and collaborative approach was validated together with the digital transformation program manager of a large, international corporation. For supporting analysis, reflection and design tasks that involve a broad range from canvas-style models to enterprise architecture models, four requirements were identified to be central: (remote) collaboration support, a holistic and integrative perspective, an enterprise-level view, and a focus on change. The actual model is comprised of over 20 partial models including popular canvases depicting the transformation program's content on the strategy-to-IT layers, the enterprise and local level, and in the as-is and to-be state. Demonstration and evaluation were done with practitioners and students of an Executive Master program focusing on digital transformation. Both confirmed the utility of the underlying method and recognized its distinctive features, while capability and IT landscape models were found especially relevant. The method is expected to be applicable for digital transformations beyond the case and also to be projectable to smaller-scaled digital business innovations. [ABSTRACT FROM AUTHOR]

Automated software transformations and the process of automated program repair and improvement are an important aspect of modern software engineering practices. In this paper, we describe a system which uses a graph-based deep learning model that can be trained to automatically transform and improve computer programs. By operating on language-agnostic, universal graph-like structures easily extractable from source code files (abstract syntax trees), the deep learning agent learns which transformations should be effectively applied to various structures recognized in the source code in order to improve it. By defining a metric which we want to improve and introducing an optimization task—a reinforcement learning setting, an agent learns to automatically apply a chain of transformations to the program, drastically improving it. While similar program improvement processes exist, they exclusively use exhaustive search algorithms to try all the possible code transformations which is a long process susceptible to local optimum issues. Our solution aims to model and embed structural knowledge about the programs being transformed which greatly helps the agent to choose best possible code transformations to apply. Elements of the approach we present in this paper are further applicable not just to automatic software improvement tasks, but also to other code-related tasks. [ABSTRACT FROM AUTHOR]

Tuning tensor program generation involves navigating a vast search space to find optimal program transformations and measurements for a program on the target hardware. The complexity of this process is further amplified by the exponential combinations of transformations, especially in heterogeneous environments. This research addresses these challenges by introducing a novel approach that learns the joint neural network and hardware features space, facilitating knowledge transfer to new, unseen target hardware. A comprehensive analysis is conducted on the existing state-of-the-art dataset, TenSet, including a thorough examination of test split strategies and the proposal of methodologies for dataset pruning. Leveraging an attention-inspired technique, we tailor the tuning of tensor programs to embed both neural network and hardware-specific features. Notably, our approach substantially reduces the dataset size by up to 53% compared to the baseline without compromising Pairwise Comparison Accuracy (PCA). Furthermore, our proposed methodology demonstrates competitive or improved mean inference times with only 25–40% of the baseline tuning time across various networks and target hardware. The attention-based tuner can effectively utilize schedules learned from previous hardware program measurements to optimize tensor program tuning on previously unseen hardware, achieving a top-5 accuracy exceeding 90%. This research introduces a significant advancement in autotuning tensor program generation, addressing the complexities associated with heterogeneous environments and showcasing promising results regarding efficiency and accuracy. [ABSTRACT FROM AUTHOR]

Transforming developmental education to promote and enhance student success is an ongoing process. This paper discusses how the Cross Curricular Career Community (C4) was developed and how frequent faculty discussion guides program evolution. Through the lens of business management theory, program changes grounded in personal and professional accountability have led to positive impacts on interactions among faculty, students, and the program in support of student agency, responsibility, and perseverance. [ABSTRACT FROM AUTHOR]

Program reduction is a highly practical, widely demanded technique to help debug language tools, such as compilers, interpreters and debuggers. Given a program P that exhibits a property ψ, conceptually, program reduction iteratively applies various program transformations to generate a vast number of variants from P by deleting certain tokens and returns the minimal variant preserving ψ as the result. A program reduction process inevitably generates duplicate variants, and the number of them can be significant. Our study reveals that on average 61.8% and 24.3% of the generated variants in two representative program reducers HDD and Perses, respectively, are duplicates. Checking them against ψ is thus redundant and unnecessary, which wastes time and computation resources. Although it seems that simply caching the generated variants can avoid redundant property tests, such a trivial method is impractical in the real world due to the significant memory footprint. Therefore, a memory-efficient caching scheme for program reduction is in great demand. This study is the first effort to conduct a systematic, extensive analysis of memory-efficient caching schemes for program reduction. We first propose to use two well-known compression methods, ZIP and SHA , to compress the generated variants before they are stored in the cache. Furthermore, our keen understanding on the program reduction process motivates us to propose a novel, domain-specific, both memory and computation-efficient caching scheme, Refreshable Compact Caching (RCC). Our key insight is two-fold: ① by leveraging the correlation between variants and the original program P, we losslessly encode each variant into an equivalent, compact, canonical representation; ② periodically, stale cache entries, which will never be accessed, are timely removed to minimize the memory footprint over time. Our extensive evaluation on 31 real-world C compiler bugs demonstrates that caching schemes help avoid issuing redundant queries by 61.8% and 24.3% in HDD and Perses, respectively; correspondingly, the runtime performance is notably boosted by 22.8% and 18.2%. With regard to the memory efficiency, all three methods use less memory than the state-of-the-art string-based scheme STR. Specifically, ZIP and SHA cut down the memory footprint by more than 80% and 90% in both Perses and HDD compared to STR ; moreover, the highly-scalable, domain-specific RCC dominates peer schemes, and outperforms the SHA by 96.4% and 91.74% in HDD and Perses, respectively. [ABSTRACT FROM AUTHOR]

The features of solving logistical problems using modern computer modeling tools are considered. The use of specialized software allows you to obtain the results of optimization or risk assessment in logistics management in the shortest possible time. The paper analyzes various application software packages designed for this purpose. The problems of developing logistics models are considered, a methodology for solving logistics problems in the Stamm 4.3 system based on an object-oriented approach, UML modeling and tabular simulation is presented. [ABSTRACT FROM AUTHOR]

The paper analyzes the possibilities of transforming C programming language constructs into objects of EO programming language. The key challenge of the method is the transpilation from a system programming language into a language of a higher level of abstraction, which does not allow direct manipulations with computer memory. Almost all application and domain-oriented programming languages disable such direct access to memory. Operations that need to be supported in this case include the use of dereferenced pointers, the imposition of data of different types in the same memory area, and different interpretation of the same data which is located in the same memory address space. A decision was made to create additional EO-objects that directly simulate the interaction with computer memory as in C language. These objects encapsulate unreliable data operations which use pointers. An abstract memory object was proposed for simulating the capabilities of C language to provide interaction with computer memory. The memory object is essentially an array of bytes. It is possible to write into memory and read from memory at a given index. The number of bytes read or written depends on which object is being used. The transformation of various C language constructs into EO code is considered at the level of the compilation unit. To study the variants and analyze the results a transpiler was developed that provides necessary transformations. It is implemented on the basis of Clang, which forms an abstract syntax tree. This tree is processed using LibTooling and LibASTMatchers libraries. As a result of compiling a C program, code in EO language is generated. The considered approach turns out to be appropriate for solving different problems. One of such problems is static code analysis. Such solutions make it possible to isolate low-level code fragments into separate program objects, focusing on their study and possible transformations into more reliable code. [ABSTRACT FROM AUTHOR]

Traditional hardware verification methods synthesize RTL designs into gate-level netlists and use SAT solvers for verification, without effectively leveraging their word-level structure, resulting in the inability to verify some properties. In recent years, software analysis and verification techniques and SMT solving technology have made significant progress. To migrate the latest software analysis and verification techniques to hardware verification, a Verilog code verification method based on C program analysis and verification technology is proposed. First, a Verilog-to-C translation system based on integrated semantics is designed, and then typical techniques and tools in the current software analysis and verification field are used to analyze and verify the converted C program, in order to determine whether the original Verilog code satisfies the property assertion. Experimental results demonstrate the feasibility and effectiveness of migrating C program analysis and verification techniques to Verilog code verification. [ABSTRACT FROM AUTHOR]

Saudi Arabia is taking significant steps to improve urban lifestyles by implementing the Quality-of-Life Program, which focuses on increasing public participation in physical activities. Studies have shown a link between physical inactivity and poor health. A large percentage of the adult population does not meet the World Health Organization's physical activity recommendations due to many reasons, including the lack of active design strategies in the built environment. This research aims to measure the extent to which active design strategies are applied in university buildings at King Abdulaziz University in Saudi Arabia and suggest recommendations for university educational buildings in KSA. A comparative analysis of systems for evaluating the application of active design strategies was conducted, and The Movement Checklist in WELL Building Standard was used as a tool to evaluate educational buildings. Additionally, a questionnaire and interviews were used to identify the awareness of the study sample of the importance of physical activity and to discover appropriate active design strategies for them. The findings of this research will help to inform the development of active design strategies that can be applied to university educational buildings in KSA and will contribute to achieving the objectives of the National Transformation Program's Quality-of-Life Program. [ABSTRACT FROM AUTHOR]

A thorough examination of the lived experiences of Brigada Eskwela Coordinators in the post-pandemic era was necessitated by the significant challenges and transformations experienced by the program. In this qualitative phenomenological study, the CIPP Process Evaluation framework is employed to examine the essence of Brigada Eskwela Program coordinators' roles, responsibilities, and challenges within the changing landscape. This study employs a phenomenological research design to uncover the universal essence of Brigada Eskwela Coordinators' experiences. The study examines three pivotal stages of the journey of six Outstanding Brigada Eskwela Coordinators through in-depth, face-to-face interviews: (1) Genesis of Execution, which emphasizes preparations and planning; (2) Implementation Midway, which emphasizes program activities; and (3) Monitoring and Feedbacking, which documents and reports progress. This study utilizes Stufflebeam's CIPP Model of Evaluation for Process Evaluation, emphasizing the activities performed, strategies utilized for preparation, and results of the program. As a result of the profound dedication, bayanihan spirit, and volunteerism exhibited by diverse stakeholders, the school is regarded as a place of unity by diverse stakeholders as reflected in their narratives. Brigada Eskwela Coordinators have embraced their traditional roles beyond the classroom to extend their reach to the home and wider community through this study. Their experiences underscore the crucial importance of partnerships, community outreach, and holistic engagement in the aftermath of the pandemic, creating a new narrative for the Brigada Eskwela Program. [ABSTRACT FROM AUTHOR]

Static analysis is popular for detecting SQL injection vulnerabilities. However, due to the lack of accurate modeling of object-oriented database extensions, current methods fail to accurately detect SQL injection vulnerabilities in applications that use object-oriented database extensions. We propose a program transformation-based SQL injection vulnerability detection method to address this issue. This method consists of two stages: program transformation and vulnerability detection. In the first stage, object-oriented database extensions are automatically transformed into semantically equivalent procedural database extensions through the identification of key statements, call relation verification, and program transformation. In the second stage, application programs are automatically scanned using a combination of control flow graph construction and taint analysis techniques to detect SQL injection vulnerabilities. Based on the proposed method, we have implemented the OODBE-SCAN prototype system and performed experimental analysis on eight modern PHP applications. We compare OODBE-SCAN with two related static analysis tools, RIPS and Seay. The results show that OODBE-SCAN can detect more real-world vulnerabilities and has higher accuracy than existing methods. [ABSTRACT FROM AUTHOR]

Background: Community-based organizations (CBOs) are key players in health and social care integration initiatives, yet little is known about CBO perspectives and experiences in these pilot programs. Understanding CBO perspectives is vital to identifying best practices for successful medical and social care integration. Methods: From February 2021 to March 2021, we conducted surveys with 12 CBOs that participated in the North Carolina COVID-19 Social Support Program, a pre-pilot for North Carolina's Medicaid Sect. 1115 demonstration waiver program that addresses social drivers of health. Results: CBO participants preferred communication strategies that involved direct communication and felt clear communication was vital to the program's success. Participants expressed varied experiences regarding their ability to handle a changing volume of referrals. Participants identified their organizations' strengths as: strong organizational operations, past experiences with and understanding of the community, and coordination across organizations. Participants identified challenges as: difficulty communicating with clients, coping with capacity demands for scaling services, and lack of clear processes from external organizations. Almost all CBO participants expressed enthusiasm for participating in similar social care transformation programs in the future. Conclusions: CBO participants in our study had broadly positive experiences in the pilot program and almost all would participate in a similar program in the future. Participants provided perspectives that can inform health and social care integration initiatives, including strengths and challenges in such programs. To build and sustain health and social care integration programs, it is important to: (1) support CBOs through regular, direct communication that builds trust and power-sharing between CBO and health care entities; (2) leverage CBO community expertise; and (3) pursue an individualized assessment of CBO capacity and identify CBO capacity-building strategies that ensure program success and sustainability. [ABSTRACT FROM AUTHOR]

A new automata-based programming language built by extending the Event-B specification language is proposed. When developing models in Event-B, it becomes possible to use automata-based methods in addition to the popular refinement method. The automata-based software engineering based on Event-B is demonstrated by the example of traffic control on a bridge from the Event-B system manual. A simpler solution with verification in the Rodin tool is proposed. The effectiveness of Event-B verification methods is confirmed by finding three nontrivial bugs in our solution. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has accelerated the need for successful digital transformation in master's programs, particularly in the realm of e-learning. This article explores the importance of a needscentered approach in navigating this transformational journey amidst the challenges posed by the pandemic. By understanding and addressing the evolving needs of students in a remote learning environment, educational institutions can effectively leverage digital technologies to deliver highquality education. The article presents a comprehensive framework for digital transformation, emphasizing the evaluation of student needs and objectives as the starting point. Strategic planning, resource allocation, and timeline development are crucial for the seamless integration of digital tools into the curriculum, taking into account the unique challenges imposed by the pandemic. Faculty and staff training and development play a pivotal role in equipping educators with the skills necessary to facilitate effective online instruction. The adoption of suitable technologies and platforms is explored within the context of e-learning, considering factors such as scalability, security, and user experience. The needs-centered approach highlights the importance of personalized learning experiences to cater to individual student requirements, ensuring engagement and achievement in the virtual classroom. Continuous monitoring, evaluation, and improvement are paramount during the digital transformation process, particularly in the context of the pandemic. Gathering feedback from students and educators allows institutions to adapt and refine their digital initiatives to optimize learning outcomes. Effective change management strategies, including clear communication, robust support systems, and stakeholder engagement, help navigate the challenges presented by the sudden shift to remote learning. In conclusion, a needs-centered approach is crucial for successful digital transformation in master's programs, especially in the face of the covid-19 pandemic. By prioritizing student needs, aligning strategies with remote learning requirements, and leveraging digital tools effectively, educational institutions can ensure the continuity and quality of education. This article provides insights and guidance for institutions seeking to navigate the digital transformation journey in the context of Covid-19, empowering them to deliver exceptional e-learning experiences and prepare students for the future of education. [ABSTRACT FROM AUTHOR]

We address the problem of compiling defeasible theories to Datalog¬ programs. We prove the correctness of this compilation, for the defeasible logic DL (∂||), but the techniques we use apply to many other defeasible logics. Structural properties of DL (∂||) are identified that support efficient implementation and/or approximation of the conclusions of defeasible theories in the logic, compared with other defeasible logics. We also use previously well-studied structural properties of logic programs to adapt to incomplete Datalog¬ implementations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Turkish Court of Accounts / Sayistay Dergisi is the property of Turkish Court of Accounts and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Reading intervention programs pose intricate challenges for school implementers, particularly the educators leading them. Employing phenomenology as a qualitative research methodology, this study charts a compelling investigative path. It aims to plumb the depths of lived experiences, convictions, and perspectives of educators who occupy pivotal roles in executing the DEAR program. Drawing from a purposively selected group of six participants in the Davao region, Philippines, this research employs semi-structured interviews subjected to meticulous thematic analysis. The study has illuminated themes that intricately capture participants' interactions with the program, vividly portraying educators' roles in program implementation: "Igniting Passion" probes the motivations that propel teachers, "Facing the Storm" delves into the encountered challenges, "Navigating the Tides" spotlights coping strategies, while "Learning and Transformation Through the Program" focuses on insights garnered from participation. The ultimate theme, "Guiding the Path Forward: Strengthening the Program," encapsulates participants' suggestions for enhancing and perpetuating program efficacy. These findings enrich discussions on reading interventions, underscore the indispensable roles of educators in nurturing reading skills, cultivating a love for literature, and nurturing lifelong learners. Implications drawn from these themes underscore the pivotal importance of support, collaboration, unwavering dedication, and proactive adaptations in effectually implementing reading programs. [ABSTRACT FROM AUTHOR]

Bourdieu's field theory has become a key heuristic for studying the impact of the market on American journalism, but this approach has not been employed to analyze the consequences of a technology-driven decline in advertising revenue. To understand this change and update the commercial critique of journalism, I extend the emerging Bourdieusian historical research program to chart transformations in the market's heteronomous effects on journalism. To do so, I highlight how the New York Times was exceptionally positioned to manage heteronomy as it emanated through the technology, political, and financial fields. This analysis throws the crisis of the wider field into relief, a field I characterize as an "inverted pyramid" to reflect how the Times' success deepened hierarchy, while also giving it the freedom to reinvent orthodoxy in a wide space of possibility atop the field. [ABSTRACT FROM AUTHOR]

DT changes the original logic of enterprise management thinking and drives enterprise production management to become more intelligent; enterprise marketing management to be more precise; and enterprise resource management to be more efficient, thus bringing about disruptive innovations in management paradigms and management systems. To carry out, direct, and connect, the DT program managers must assemble a program leadership team devoted to executing the DT strategy. The DT Program Manager Although companies do not necessarily have a unified position for digital program managers, companies have set up positions as senior IT directors, DT directors, DT chiefs, DT managers, and IT program managers to assume the responsibilities. DT introduces digital technology into the existing enterprise management structure to promote a systematic remodeling of information structures, management methods, operating mechanisms, and production processes, all of which objectively require enterprises to break with traditional industrialized management. [Extracted from the article]

Machine knitting is a well-established fabrication technique for complex soft objects, and both companies and researchers have developed tools for generating machine knitting patterns. However, existing representations for machine knitted objects are incomplete (do not cover the complete domain of machine knittable objects) or overly specific (do not account for symmetries and equivalences among knitting instruction sequences). This makes it difficult to define correctness in machine knitting, let alone verify the correctness of a given program or program transformation. The major contribution of this work is a formal semantics for knitout, a low-level Domain Specific Language for knitting machines. We accomplish this by using what we call the fenced tangle, which extends concepts from knot theory to allow for a mathematical definition of knitting program equivalence that matches the intuition behind knit objects. Finally, using this formal representation, we prove the correctness of a sequence of rewrite rules; and demonstrate how these rewrite rules can form the foundation for higher-level tasks such as compiling a program for a specific machine and optimizing for time/reliability, all while provably generating the same knit object under our proposed semantics. By establishing formal definitions of correctness, this work provides a strong foundation for compiling and optimizing knit programs. [ABSTRACT FROM AUTHOR]

Objective: Monitoring and comparing regional service performance is inevitable to use resources effectively and allocate resources without creating interregional inequalities. With the Health Transformation Program, there has been an increase in the amount and quality of the service provided throughout the country. In addition, there has been a decrease in the inequalities between regions due to its implementation. In order to ensure continuity in health service delivery, health service activities in provinces and regions should be followed regularly, and their performance should be evaluated. Methods: The study calculated Data Envelopment Analysis efficiencies and Cross-efficiency for 26 subregions in the NUTS-II classification in Turkey. The number of hospital beds and primary care units were the inputs of the research; the number of primary, secondary and tertiary care visits and the number of inpatients are also the output of the study. Subregions are reordered and grouped according to their cross-efficiency. Decisionmaking units with unusual production structures were investigated by calculating Maverick Index scores. Results: Regarding DEA efficiency, the average efficiency score of the ten subregions classified as efficient is 0.97 (sd. 0.0395). The average crossefficiency score obtained from the benevolent method is 0.89 (sd. 0.058), while the average score achieved through the aggressive method is 0.86 (sd. 0.574). Maverick index scores had a balanced distribution. The average maverick index score for aggressive and benevolent are 0.13 (std. 0.0474), and 0.0871 (std. 0.0420), respectively. Although only the Malatya subregion was classified as efficient in the traditional DEA method, it had low scores in the cross-efficiency evaluation and was classified as a maverick decision unit with an MI score of 0.21. Conclusion: The cross-efficiency method yields more valuable results because it employs more realistic weights for peer evaluation. These outcomes are simpler for decision-makers to comprehend and assess. The regions of Kocaeli, Adana, Aydın, Hatay, Şanlıurfa, and Tekirdağ exhibit notable performance in the cross-efficiency examination, as they have attained the most significant efficiency scores. The regions of Kastamonu, Erzurum, Van, and Ağrı exhibit poor levels of efficiency, thereby requiring the implementation of precautionary measures. [ABSTRACT FROM AUTHOR]

This paper focuses on the practical application of system architecture modeling and reference enabling in systems engineering, introducing the fundamental principles and proof of concept. The fundamental principles are defined by ISO/IEC 81346 standard series, which provides a common language for systems across all engineering disciplines through the Reference Designation System (RDS). RDS is used to create a reference model with unambiguous identifiers representing system breakdowns in different views called aspects, allowing for clear reference designations of system elements and their relationships, complying with the basic rules of ISO 704 – Terminology work. The practical use of this system reference model is demonstrated through a selected use case: the Digital Design, Manufacturing & Services (DDMS) transformation program at AIRBUS S.A.S. (Toulouse, France). This case includes practical experience and a brief introduction to tools that assist with the usage of ontologies and terminology work in daily life. [ABSTRACT FROM AUTHOR]

Copyright of Boğaziçi Journal: Review of Social, Economic & Administrative Studies is the property of Bogazici University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Administration & Economics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The K-variant is a multi-variant architecture to enhance the security of the time-bounded mission and safety-critical systems. Variants in the K-variant architecture are generated by controlled source program transformations. Previous experimental studies showed that the K-variant architecture might improve the security of systems against memory exploitation attacks. In order to estimate the survivability of K-variant systems, simulation techniques are utilized. However, these techniques are slow and may not be practical for the design of K-variant systems. Therefore, fast and highly accurate estimations of the survivability of K-variant systems are necessary for developers. The neural networks may allow quick and accurate estimation of the survivability of K-variant systems. The developed neural network-based tool can make quick and precise estimations of the survivability of K-variant systems under different conditions. In this paper, the accuracy of the neural network-based tool is investigated in an experimental study. The neural network-based tool estimations are compared with a K-variant attack emulator in three programs for up to ten variant systems under four attack types and three attack durations. The experimental study demonstrates that the neural network-based tool makes fast and accurate estimations of the survivability of K-variant systems under all the conditions investigated. [ABSTRACT FROM AUTHOR]

Model transformation is a core mechanism for Model-Driven Engineering (MDE). Writing complex programs such as model transformations (MT) is error-prone, and efficient testing techniques are required for their quality assurance. There are several challenges when it comes to testing MT, including the automatic generation of suitable input test models and the construction of test oracles based on verification properties. Many approaches to generating input models ensure coverage of a certain level of the source meta-model and some input/output model constraints. Furthermore, most transformation testing techniques are tailored to specific implementation languages or quality properties, which makes it difficult to reuse testing techniques for different languages due to their language-specific nature. The diversity of languages and verification properties raises the need for a black-box testing framework of MT that is independent of transformation implementation languages as well as supports systematic verification of the quality properties. In this paper, we clarify the basic elements of such a framework, and how to apply this framework for systematically testing MT. The main tasks of the model transformation testing process, including test design, test execution and evaluation, are defined and realized within this integrated framework. [ABSTRACT FROM AUTHOR]

Public spaces are an essential part of the urban environment as they support a wide variety of public activity. Within the City of Hail, Saudi Arabia, public spaces have undergone a cultural shift, making them more vibrant and highly attractive, serving as much needed breathing spaces for the city and popular gathering places. The culture of Hail and its surrounding region strives to accept change while preserving the customs and traditions of previous generations. The aim of the study is to first examine public spaces through six dimensions to identify and understand the differences in space quality. The presence of these six dimensions is further refined into eighteen. These dimensions and attributes will be used to evaluate the various public spaces within Hail, and the results of this study are intended to inform both citizens and city officials of the quality of public spaces throughout the city. Second, the study intends to correlate quantitative and qualitative data to develop a better understanding of specific space qualities by utilizing fieldwork observations and user perception. The study concludes by identifying several specific challenges concerning the planning and design of public spaces in Hail, as well as several recommendations for increasing the value of Hail's public spaces in accordance with Saudi Arabia's National Transformation Program. [ABSTRACT FROM AUTHOR]