Search Results - Complexity Measures and Classes—Complexity hierarchies

Some facets of complexity theory and cryptography: A five-lecture tutorial

Authors: Jörg Rothe The Pennsylvania State University CiteSeerX Archives

Contributors: Jörg Rothe The Pennsylvania State University CiteSeerX Archives

Source: http://arxiv.org/pdf/cs/0111056v2.pdf.

Subject Terms: Categories and Subject Descriptors, E.3 [Data Encryption, Public-key Cryptosystems, F.1.3 [Computation by Abstract Devices, Complexity Measures and Classes—Complexity hierarchies, Relations among complexity classes, F.2.2 [Analysis of Algorithms and Problem Complexity, Nonnumerical Algorithms and Problems—Computations on discrete structures General Terms, Theory, Security, Algorithms Additional Key Words and Phrases, complexity theory, public-key cryptography, secret-key agreement, digital signatures, interactive proof systems, zero-knowledge protocols, one-way functions

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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.342.6969; http://arxiv.org/pdf/cs/0111056v2.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.342.6969
http://arxiv.org/pdf/cs/0111056v2.pdf

Cognitive Weighted Inherited Class Complexity Metric

Authors: A. Aloysius K. Maheswaran

Source: Procedia Computer Science. 125:297-304

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://www.sciencedirect.com/science/article/pii/S1877050917328041

Cognitive Weighted Inherited Class Complexity Metric.

Authors: Maheswaran, K. Aloysius, A.

Source: Procedia Computer Science. 2018, Vol. 125, p297-304. 8p.

Subject Terms: Cognitive load, Programming languages, Electronic data processing, Information storage & retrieval systems, Computer software

New Proposed Inheritance Metrics to Measure the Software Complexity

Authors: Rajender S. Chillar Preeti Gulia

Source: International Journal of Computer Applications. 58:1-4

Subject Terms: 9. Industry and infrastructure, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://research.ijcaonline.org/volume58/number21/pxc3883486.pdf
https://www.ijcaonline.org/archives/volume58/number21/9403-3486
https://core.ac.uk/display/22118525
https://ui.adsabs.harvard.edu/abs/2012IJCA...58u...1G/abstract

Optimal bounds for decision problems on the CRCW PRAM

Authors: Paul Beame Johan Hastad The Pennsylvania State University CiteSeerX Archives

Contributors: Paul Beame Johan Hastad The Pennsylvania State University CiteSeerX Archives

Source: http://www.cs.washington.edu/homes/beame/papers/crcwparity.pdf.

Subject Terms: Categories and Subject Descriptors, F. 1.2 [Computation by Abstract Devices, Modes of Computationparallelism, F. 1.3 [Computation by Abstract Devices, Complexity Classes-complexity hierarchies, relations among complexify measures, F.2.3 [Analysis of Algorithms and Problem Complexity, Trudeoffs among complexity classes General Terms, Theory, Verification Additional Key Words and Phrases, Concurrent-write, lower bounds, parallel random-access machines, parity

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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.8602; http://www.cs.washington.edu/homes/beame/papers/crcwparity.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.8602
http://www.cs.washington.edu/homes/beame/papers/crcwparity.pdf

Predicting Software Maintainability Using Object Oriented Dynamic Complexity Measures.

Authors: Gosain, Anjana Sharma, Ganga

Source: Smart Trends in Information Technology & Computer Communications; 2016, p218-230, 13p

New Proposed Inheritance Metrics to Measure the Software Complexity

Authors: Preeti Gulia Rajender S. Chillar The Pennsylvania State University CiteSeerX Archives

Contributors: Preeti Gulia Rajender S. Chillar The Pennsylvania State University CiteSeerX Archives

Source: http://research.ijcaonline.org/volume58/number21/pxc3883486.pdf.

Subject Terms: Complexity, software metrics, inheritance, NOC, DIT, Object

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.252.7841; http://research.ijcaonline.org/volume58/number21/pxc3883486.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.252.7841
http://research.ijcaonline.org/volume58/number21/pxc3883486.pdf

Upward Mobility and Class Inequities among Filipino Migrant Nurses in the Republic of Ireland.

Authors: Trinidad, Arnie Cordero Faas, Daniel

Source: Sociology; Feb2025, Vol. 59 Issue 1, p37-54, 18p

Subject Terms: FILIPINOS, NURSES' attitudes, IMMIGRANTS, CAPITALISM

Geographic Terms: IRELAND, PHILIPPINES

Validation of measurement tools to extract metrics from open source projects.

Authors: Bakar, Normi Sham Awang Abu Boughton, Clive V.

Source: 2012 IEEE Conference on Open Systems; 1/ 1/2012, p1-6, 6p

On the effectiveness of network metrics on key class prediction: An empirical study.

Authors: Zhou, Shiyuan Wu, Wei Wang, Jiale et al.

Source: PLoS ONE; 10/10/2025, Vol. 20 Issue 10, p1-25, 25p

Subject Terms: COMPUTER software, EMPIRICAL research, MACHINE learning, SOFTWARE measurement

Predictive Benthic Habitat Mapping Reveals Significant Loss of Zostera marina in the Puck Lagoon, Baltic Sea, over Six Decades.

Authors: Janowski, Łukasz Barańska, Anna Załęski, Krzysztof et al.

Source: Remote Sensing; Nov2025, Vol. 17 Issue 22, p3725, 44p

Subject Terms: ZOSTERA marina, ENVIRONMENTAL degradation, SEAGRASS restoration, BENTHIC ecology, SEAWATER, ENVIRONMENTAL mapping, LAGOONS, MACHINE learning

Geographic Terms: BALTIC Sea

A Bedbug Optimization-Based Machine Learning Framework for Software Fault Prediction.

Authors: Arasteh, Bahman Sefati, Seyed Salar Popovici, Eduard-Cristian et al.

Source: Mathematics (2227-7390); Nov2025, Vol. 13 Issue 21, p3531, 26p

Subject Terms: FEATURE selection, COMPUTER software quality control, MACHINE learning, SUPPORT vector machines, NAIVE Bayes classification, ARTIFICIAL neural networks, DECISION trees

ECONOMIC VOTING OR CLASS VOTING? AN ANALYSIS OF THE FACTORS DRIVING INCUMBENT VOTE CHOICE.

Authors: STANCEA, Andreea CIOCÎRLAN, Cecilia COJOCARU, Rebeca et al.

Source: Romanian Sociology / Sociologie Româneascâ; 2024, Vol. 22 Issue 2, p9-28, 20p

Defining model complexity: An ecological perspective.

Authors: Malmborg, Charlotte A. Willson, Alyssa M. Bradley, L. M. et al.

Source: Meteorological Applications; May/Jun2024, Vol. 31 Issue 3, p1-16, 16p

Subject Terms: ECOLOGICAL models, HYPOTHESIS, COMPUTATIONAL complexity, TERMS & phrases

Improvements to a complexity metric: CB measure.

Authors: De Silva, D. I. Kodagoda, N. Kodituwakku, S. R. et al.

Source: 2015 IEEE 10th International Conference on Industrial & Information Systems (ICIIS); 1/1/2015, p401-406, 6p

A Software Code Complexity Framework; Based on an Empirical Analysis of Software Cognitive Complexity Metrics using an Improved Merged Weighted Complexity Measure.

Authors: Joseph, Wafula Mwangi, Waweru Waweru, Stephen N.

Source: International Journal of Advanced Research in Computer Science; May/Jun2013, Vol. 4 Issue 3, p51-62, 12p

Subject Terms: COMPUTER software, COMPUTER software development, COMPUTER software developers, COMPUTER industry, COMPUTER software industry

Geographic Terms: KENYA

The inaccuracy of uniform counting in software metrics: empirical evidence with a weighted remedy.

Authors: Nejad Hajali Irani, Gholamali

Source: Iran Journal of Computer Science; Dec2025, Vol. 8 Issue 4, p2357-2386, 30p

Limitations of an object-oriented metric: Weighted complexity measure.

Authors: De Silva, D. I. Kodagoda, N. Kodituwakku, S. R. et al.

Source: 2015 6th IEEE International Conference on Software Engineering & Service Science (ICSESS); 2015, p698-701, 4p

THE COMPUTATIONAL EFFECT AND HYPERPARAMETERS TUNING OF DEEP CONVOLUTIONAL LAYER DEPTH OF HIGHRANKING TUBERCULOSIS DETECTION MODELS.

Authors: OTOBI, AUGUSTINE O. ESIN, JOSEPH O. ETENG, IDONGESIT E. et al.

Source: Global Journal of Pure & Applied Sciences; 2024, Vol. 30 Issue 4, p577-584, 8p

Subject Terms: ARTIFICIAL neural networks, MACHINE learning, ARTIFICIAL intelligence, CONVOLUTIONAL neural networks, FEATURE extraction, DEEP learning

Identification of Agricultural Areas to Restore Through Nature-Based Solutions (NbS).

Authors: Petti, Beatrice Ottaviano, Marco

Source: Land (2012); Nov2024, Vol. 13 Issue 11, p1954, 21p

Subject Terms: FOREST restoration, ANALYTIC hierarchy process, ECOSYSTEM services, AGRICULTURE, LAND use