Computer Science as Immaterial Formal Logic

Bringsjord, Selmer

doi:10.1007/s13347-019-00366-7

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…Philosophically, computer science is a science with issues that arise based on reflecting on the discipline and its scientific practice [208]. In the computational artifacts of the philosophy of computer science [209], computer science is a science that involves logic to realize the systematics of ordinance and mathematics for modeling as the basis for developing the theory [210]. Although philosophy did not underlie the emergence of computer science [122], this requires a collaborative transformation between philosophy and computer science that presents an interaction between teaching and teaching [211].…”

Section: B Discussion: Accumulation and Spread -The Growth Overviewmentioning

confidence: 99%

Computer Science

Nasution¹,

Hidayat²,

Syah³

2022

International Journal on Advanced Science, Engineering and Information Technology

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Possible for science itself, conceptually, to have and will understand differently, let alone science also seen as technology, such as computer science. After all, science and technology are viewpoints diverse by either individual, community, or social. Generally, it depends on socioeconomic capabilities. So it is with computer science has become a phenomenon and fashionable, where based on the stream of documents, various issues arise in either its theory or implementation, adapting different communities, or designing curriculum holds in the education system. Generally, there are gaps between rich and poor, masculine and feminine, and basic sciences, engineering, and social sciences in accessing and using computer science. In particular, there have been various developments in hardware, software, and brain-ware from computer science in the application. There are recurring problems shortly, in the same or different places, both in developed and technologically lagging countries. Although computer science is still new, it has provided various innovations through research, which is proven by many documents. Therefore, following the growth of computer science -documents in the reputable indexed database, Scopus -there are clues for showing the trends. That is, dividing documents into three-time sessions: sloping, increasing and decreasing. That is by using a growth graphic. Then equip it with some parameters: topics and the weights from hit counts of databases. It gives the meaning as an interpretation to support the reviews. Therefore, this paper will provide a commentary related to that growth. It is for showing that despite the spread of studies, at the last time-session, the issues were always present simultaneously at the same time in accumulation. That is for describing a study title of computer science about what the world already has, going, and will understand about computer science. It is a view regarding its philosophy, basic science, applications, and technology as concepts and solutions that make computer science the primary foundation for skills and professions in the 21 st century through the education system. Therefore, other scientific fields such as informatics, computer engineering, information science, information technology, and data science, which are at the crossroads of computer science, are also scientific fields that raise different issues.

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Section: B Discussion: Accumulation and Spread -The Growth Overviewmentioning

confidence: 99%

Computer Science

Nasution¹,

Hidayat²,

Syah³

2022

International Journal on Advanced Science, Engineering and Information Technology

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“…Our inference rules for N D are summarized in Figure 1 1 . This formalization is modeled after Bringsjord [3] and fully captures the notion of discharging of assumptions. It is also particularly well suited to hypergraphical representation, which will be discussed in §2.2.…”

Section: Natural Deductionmentioning

confidence: 99%

Parallel Verification of Natural Deduction Proof Graphs

Oswald,

Rozek

2023

Electron. Proc. Theor. Comput. Sci.

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Graph-based interactive theorem provers offer a visual representation of proofs, explicitly representing the dependencies and inferences between each of the proof steps in a graph or hypergraph format. The number and complexity of these dependency links can determine how long it takes to verify the validity of the entire proof. Towards this end, we present a set of parallel algorithms for the formal verification of graph-based natural deduction (N D ) style proofs. We introduce a definition of layering that captures dependencies between the proof steps (nodes). Nodes in each layer can then be verified in parallel as long as prior layers have been verified. To evaluate the performance of our algorithms on proof graphs, we propose a framework for finding the performance bounds and patterns using directed acyclic network topologies (DANTs). This framework allows us to create concrete instances of DANTs for empirical evaluation of our algorithms. With this, we compare our set of parallel algorithms against a serial implementation with two experiments: one scaling the problem size and the other scaling the number of threads. Our findings show that parallelization results in improved verification performance for certain DANT instances. We also show that our algorithms scale for certain DANT instances with respect to the number of threads.

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Computational Artifacts: the Things of Computer Science

Turner

2019

Philos. Technol.

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Computer Science as Immaterial Formal Logic

Cited by 6 publications

References 12 publications

Computer Science

Computer Science

Parallel Verification of Natural Deduction Proof Graphs

Computational Artifacts: the Things of Computer Science

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