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Accounting for data encapsulation in the measurement of object-oriented class cohesion

JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS 2015年第5期27卷 373-400页

作者： Al Dallal, Jehad Kuwait Univ Dept Informat Sci Safat 13060 Kuwait

Intuitively, in a certain class, a pair of methods that share an attribute of an object type is potentially more cohesive than those that share an attribute of a primitive type because the attribute of a reference type could implicitly refer to multiple data. Existing class cohesion measures ignore the implicit access to or sharing of attributes due to the encapsulation feature. As a result, the obtained cohesion values can be inaccurate and could lead to incorrect quality indications. This paper aims at demonstrating how to account for data encapsulation (DE) in cohesion measurement and reports empirical studies that investigate the impact of considering DE in cohesion measurement on cohesion values and the abilities of cohesion measures to predict class fault proneness. To differentiate between attributes and parameters of different types, we propose a weight assignment algorithm. The weight that is assigned to an attribute or a parameter of a type depends on the number of encapsulated attributes of the type. Seven cohesion measures are extended to consider the assigned weights in cohesion measurement. The results of the empirical study show that the cohesion values and the corresponding fault-proneness prediction results can significantly change when accounting for DE in cohesion measurement. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： data encapsulation object-oriented design class quality class cohesion cohesion measure fault prediction

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An approach to data encapsulation in the teaching of computing

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Education and Computing 1985年第1期1卷 45-49页

作者： Thomas, P.G. Computing Discipline Faculty of Mathematics The Open University Milton Keynes United Kingdom

data encapsulation, also known as data hiding, has been recognised as an important concept in the construction of maintainable programs [5]. It is a concept that should form part of a modern programming course. Such a course ought to provide practical experience of encapsulating data. Unfortunately, many programming languages used in the teaching of programming do not support this facility. This paper argues the case for teaching about data encapsulation early in a student's career and illustrates how the technique can usefully be employed in a first course on programming. The paper shows the approach taken in OUSBASIC - a programming language designed for teaching computing. © 1985 Elsevier Science Publishers B.V. (North-Holland).

关键词： data encapsulation data hiding Educational software Modularity OUSBASIC Package programming languages

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Flow Cytometry Sorting for Random Access in DNA data Storage: encapsulation for Enhanced Stability and Sequence Integrity of DNA

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ANALYTICAL CHEMISTRY 2024年第40期96卷 16099-16108页

作者： Zhong, Wukun Geng, Chunyang Fu, Zhangcheng Mao, Cuiping Zheng, Yanlin Wang, Saijie Liu, Kai Yang, Yang Lu, Chunhua Jiang, Xingyu Fuzhou Univ Coll Chem MOE Key Lab Analyt Sci Food Safety & Biol Fuzhou 350108 Peoples R China Southern Univ Sci & Technol Dept Biomed Engn Shenzhen Key Lab Smart Healthcare Engn Guangdong Prov Key Lab Adv Biomat Shenzhen 518055 Guangdong Peoples R China Tsinghua Univ Engn Res Ctr Adv Rare Earth Mat Dept Chem Minist Educ Beijing 100084 Peoples R China Shanghai Jiao Tong Univ Renji Hosp Inst Mol Med Sch Med Shanghai 200127 Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Nucle Acid Chem & Nanomed State Key Lab Oncogenes & Related Genes Renji HospSch Med Shanghai 200127 Peoples R China

As digital data undergo explosive growth, deoxyribonucleic acid (DNA) has emerged as a promising storage medium due to its high density, longevity, and ease of replication, offering vast potential in data storage solutions. This study focuses on the protection and retrieval of data during the DNA storage process, developing a technique that employs flow cytometry sorting (FCS) to segregate multicolored fluorescent DNA microparticles encoded with data and facilitating efficient random access. Moreover, the encapsulated fluorescent DNA microparticles, formed through layer-by-layer self-assembly, preserve structural and sequence integrity even under harsh conditions while also supporting a high-density DNA payload. Experimental results have shown that the encoded data can still be successfully recovered from encapsulated DNA microparticles following de-encapsulation. We also successfully demonstrated the automated encapsulation process of fluorescent DNA microparticles using a microfluidic chip. This research provides an innovative approach to the long-term stability and random readability of DNA data storage.

关键词： data encapsulation

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Determination of level of steadiness against data encapsulation steganographic methods attacks

Determination of level of steadiness against data encapsulat...

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International Crimean Conference on Microwave & Telecommunication Technology

作者： O.O. Vovk A.A. Astrakhantsev Kharkiv National University of Radioelecteonics 14 Lenin Ave. 61171 Ukraine

The influence of different types of attacks against the images embedded with DW (digital watermark) was considered. The comparative analysis of stability to distortion of the most popular methods of embedding DW in sp... 详细信息

关键词： Wavelet transforms Watermarking data encapsulation Educational institutions Abstracts Stability analysis

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Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes 10th

Personality Profiling for Literary Character Dialogue Agent...

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10th International Conference on Machine Learning, Optimization, and data Science, LOD 2024

作者： Rusnachenko, Nicolay Liang, Huizhi School of Computing Newcastle University Newcastle upon Tyne Newcastle United Kingdom

ISBN: (纸本)9783031824838

Equipping personalities to dialogue agents can help to better engage end-users. However, how to profile personality remains an open research question due to the difficulties of obtaining real human data. As classic literary characters often encapsulate typical human personality traits, literature books has been used as a high quality data source to construct personality profiles for dialogue agents. Existing work mainly focuses on using external reviews and human experts’ annotations to profile character personalities. The in-text comments about the personality of characters in a literature book itself have been ignored. In this paper, we propose a new NLP task called character comments annotation to annotate the in-text comments about the personality of characters including dialogue utterances and surrounding text, paragraphs mentioning a character. We constructed new personality annotated dialogue datasets based on Gutenberg literature book project. We propose a workflow to automatically profile literary characters from literature novel books. Two personality profiling models have been proposed, including (i) psychological personality traits vocabulary-based spectrum (spectrums) approach and (ii) a tf-idf based words selection as a baseline approach. We applied the proposed personality models in dialogue response prediction tasks with ranking-based and generative dialogue agents. The results show that the fine-tuned dialogue agents with spectrums profiles surpass those trained without them by 2.5% (Hits 1@20) for ranking-based, and by 8% (Rouge-1) for generative agents. The implementation of the workflow with study-related resources is publicly available: https://***/nicolay-r/book-persona-retriever © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data encapsulation

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Initial Observations from Field Testing of a Digital Participatory Tool to Improve Water Security in Rural India 24

Initial Observations from Field Testing of a Digital Partici...

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2024 International Conference on Information and Communication Technologies and Development, ICTD 2024

作者： Mehta, Shivani A Dutt, Aila Tannirkulam, Ajay Singh, Akshay Pratap Verma, Aman Singha, Anamitra Sreenidhi, Ananda Nandi, Ananjan Ankit Kumar, Ankit Dabli, Atharv Athira, P. Ramachandran, Balakumaran Bansal, Chahat Sheth, Chintan Sanjaybhai Dsouza, Craig Kumar, Deepak Sharma, Dharmisha Harshita Singh, Jaskaran Dadheech, Kapil Agrahari, Ksheetiz Krishna, Om Prasad, Pooja Radhakrishnan, Priyadarshini Sardana, Ramita Bhabak, Rittwick Bodavula, Ruptirumal Sai Vishnubhatla, Saketh Haldar, Samitha Agrawal, Sanjali Maurya, Shiv Prakash Kumari, Shruti Siddharth, S. Kumari, Sukriti Vishnu, S. Seth, Aaditeshwar School of Information Technology Indian Institute of Technology Delhi Delhi New Delhi India Gram Vaani Delhi New Delhi India Magasool Tamil Nadu Chennai India Department of Computer Science and Engineering Indian Institute of Technology Delhi Delhi New Delhi India Civil Engineering Indian Institute of Technology Palakkad Kerala Palakkad India Well Labs Karnataka Bengaluru India School of Public Policy Indian Institute of Technology Delhi Delhi New Delhi India Indian Institute of Technology Delhi Delhi New Delhi India

ISBN: (纸本)9798400710414

With almost half the Indian population facing water stress [42], likely to be aggravated with climate change [76, 122], an intersecting crises of environment, livelihood, and social justice can worsen the vulnerability of rural communities that are directly dependent upon water resources for their livelihood and sustenance. To address this challenge of rural water security especially for marginalized communities, MGNREGA is a public works and employment generation scheme in India that contributes towards the construction of water related assets such as farm ponds, checkdams, and trenches and bunds, to improve irrigation and climate resilience of rural communities. MGNREGA is a demand-driven scheme that solicits demands for water related assets through the local governance structure in India of village-level community meetings called Gram Sabhas. In many areas, Civil Society Organizations (CSOs) and community based institutions also play a significant role by coordinating participatory processes to build the capacity of rural community members to participate in local governance and demand such assets under MGNREGA. However, through multiple field visits, we observed a need to strengthen local processes with appropriate data and tools to support context-sensitive and evidence-based bottom-up planning. In this study, we adopt an approach of building a digital participatory tool, built on a technology stack that encapsulates different geospatial datasets, to answer key research questions of whether such technology artefacts can improve the participation of rural communities in water security planning and management, through, (1) community empowerment by building a data-driven understanding of water security, (2) ecological sustainability of water resources through scientific planning of assets, and (3) equity led participatory processes to improve fairness in the distribution of assets. We discuss here the design of the tool, Commons Connect, underlying datasets on whic

关键词： data encapsulation

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Probabilistic datatypes 21st

Probabilistic Datatypes

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21st International Colloquium on Theoretical Aspects of Computing, ICTAC 2024

作者： Chen, Chris McIver, Annabelle Morgan, Carroll School of Computing Macquarie University Sydney Australia University of New South Wales and Trustworthy Systems Sydney Australia

ISBN: (纸本)9783031770180

An encapsulated datatype collects related data together with the operations used to access them. datatype refinement then provides a clear separation between the expectations of programs that call the operations (i.e. from outside the encapsulation) and the implementation of the operations themselves (inside the encapsulation), and it enforces consistency between the two. In this paper we consider encapsulated probabilistic datatypes, i.e. those whose operations can "flip coins";and we find as a result that the interface between calling programs’ expectations and their encapsulated probabilistic implementations must now provide consistency not only for functional properties but also for properties related to information flow. In this paper we use a quantitative information-flow model for programs to give a sound basis for refinement of probabilistic datatypes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data encapsulation

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Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

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JOURNAL OF APPLIED PHYSICS 2025年第3期137卷

作者： Raghavan, Aditya Pratiush, Utkarsh Valleti, Mani Liu, Richard (Yu) Emery, Reece Funakubo, Hiroshi Liu, Yongtao Rack, Philip Kalinin, Sergei Univ Tennessee Dept Mat Sci & Engn Knoxville TN 37909 USA Tokyo Inst Technol Dept Mat Sci & Engn Yokohama 2268502 Japan Oak Ridge Natl Lab Ctr Nanophase Mat Sci Oak Ridge TN 37830 USA Pacific Northwest Natl Lab Phys Sci Div Richland WA 99354 USA

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure-property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://***/licenses/by/4.0/).

关键词： data encapsulation

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Machine learning knowledge-driven Pt-based catalyst design library development for selective oxidation of polyalcohol

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AIChE Journal 2025年第6期71卷

作者： Zhou, Xin Qin, Honghua Zhang, Zhibo Zhu, Mengzhen Yan, Hao Feng, Xiang Wu, Lianying Yang, Chaohe Chen, De College of Chemistry and Chemical Engineering Ocean University of China Qingdao China State Key Laboratory of Heavy Oil Processing China University of Petroleum Qingdao China Department of Chemical Engineering Norwegian University of Science and Technology Trondheim Norway

Laborious first-principles calculations and trial-and-error experimentation often fail to meet the demands of rational and efficient catalyst development. This paper introduces an approach that integrates costly labeled data with process reaction mechanisms for catalyst formulation in the high-value conversion of glycerol. We developed an innovative system framework, POCOM, which simultaneously generates the optimal process superstructure and operating conditions to achieve peak conversion rates and desired product specifications. We synergistically combined reaction mechanisms, machine learning, process optimization, and data generation techniques, encapsulating them into a cutting-edge software system specifically designed for catalyst formulation in glycerol selective oxidation. In this process, we identified a previously unreported Pt-ZnO catalyst formulation. The catalyst, with 1.8 wt% Pt and 0.4 wt% ZnO, demonstrated exceptional performance, achieving a glycerol conversion rate of 88% and a glyceric acid selectivity of 80%. This study offers groundbreaking insights and robust data support for the rational design of glycerol oxidation catalysts. © 2025 American Institute of Chemical Engineers.

关键词： data encapsulation

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data Spatial Programming

arXiv

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arXiv 2025年

作者： Mars, Jason University of Michigan Ann ArborMI United States

We introduce a novel programming model, data Spatial Programming, which extends the semantics of Object-Oriented Programming (OOP) by introducing new class-like constructs called archetypes. These archetypes encapsulate spatial relationships between data entities and execution flow in a structured manner, enabling more expressive and semantically rich computations over interconnected data structures. By formalizing the relationships between data elements in space, our approach allows for more intuitive modeling of complex systems where the topology of connections is essential to the underlying computational model. This paradigm addresses limitations in traditional OOP when representing dynamically evolving networks, agent-based systems, and other spatially-oriented computational problems. © 2025, CC BY-NC-ND.

关键词： data encapsulation

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