3. Algorithmic thinking

2016 ◽  
pp. 33-61
Author(s):  
Subrata Dasgupta
Keyword(s):  
Computer Science ◽  
Time Complexity ◽  
Procedural Knowledge ◽  
Space Complexity ◽  
Exponential Time ◽  
Computational Problem ◽  
Algorithmic Thinking ◽  
Abstract Artifacts

Algorithms are at the epicentre of computer science—thinking computationally is forming the habit of algorithmic thinking. In order for a procedure to qualify as an algorithm, it must possess the following attributes: finiteness, definiteness, effectiveness, and having one or more inputs and one or more outputs. Algorithms are determinate, abstract artifacts, and procedural knowledge. ‘Algorithmic thinking’ explains the process of designing algorithms, the ‘goodness’ of algorithms as utilitarian artefacts, and why the aesthetics of algorithms matter. The performance of algorithms can be estimated in terms of time (or space) complexity. A computational problem is intractable if all known algorithms to solve the problem are of at least exponential time complexity.

scholarly journals Space Complexity of C Compiler and Lex Tool

2020 ◽  
Vol 8 (6) ◽  
pp. 5141-5144
Keyword(s):  
Computer Science ◽  
Programming Languages ◽  
Time Complexity ◽  
Space Complexity ◽  
The Other ◽  
Machine Language ◽  
Memory Consumption ◽  
C Compiler ◽  
High Level ◽  
Computer Processor

We can never stop stressing on the purpose and the importance of the compiler in the field of computer science. compiler does translates the high level programs like C,C++,java ,python and so on into low level language (machine language ) which in turn computer processor use. Though the job of the compiler is to translate, depending on the properties of the programming languages the time complexity, space complexity and some of the other characteristics varies accordingly. Thus the purpose of the paper is concentrated on comparing such factors significantly the C compiler and the Lex tool. Our study reveals the best memory consumption among c compiler and lex tool.

scholarly journals Efficient Nonrecursive Bit-Parallel Karatsuba Multiplier for a Special Class of Trinomials

VLSI Design ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Yin Li ◽  
Yu Zhang ◽  
Xiaoli Guo
Keyword(s):  
Time Delay ◽  
Special Class ◽  
Time Complexity ◽  
Space Complexity ◽  
Polynomial Basis ◽  
Gate Delay ◽  
Complexity Bound ◽  
Parallel Multiplier ◽  
Highly Efficient ◽  
First Time

Recently, we present a novel Mastrovito form of nonrecursive Karatsuba multiplier for all trinomials. Specifically, we found that related Mastrovito matrix is very simple for equally spaced trinomial (EST) combined with classic Karatsuba algorithm (KA), which leads to a highly efficient Karatsuba multiplier. In this paper, we consider a new special class of irreducible trinomial, namely, xm+xm/3+1. Based on a three-term KA and shifted polynomial basis (SPB), a novel bit-parallel multiplier is derived with better space and time complexity. As a main contribution, the proposed multiplier costs about 2/3 circuit gates of the fastest multipliers, while its time delay matches our former result. To the best of our knowledge, this is the first time that the space complexity bound is reached without increasing the gate delay.

scholarly journals Cryptanalytic Performance Appraisal of Improved CCH2 Proxy Multisignature Scheme

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Raman Kumar ◽  
Nonika Singla
Keyword(s):  
Elliptic Curve ◽  
Performance Appraisal ◽  
Time Complexity ◽  
Space Complexity ◽  
Elliptic Curve Cryptosystem ◽  
Forgery Attack ◽  
Signature Schemes ◽  
Computational Overhead ◽  
Threshold Schemes

Many of the signature schemes are proposed in which thetout ofnthreshold schemes are deployed, but they still lack the property of security. In this paper, we have discussed implementation of improved CCH1 and improved CCH2 proxy multisignature scheme based on elliptic curve cryptosystem. We have represented time complexity, space complexity, and computational overhead of improved CCH1 and CCH2 proxy multisignature schemes. We have presented cryptanalysis of improved CCH2 proxy multisignature scheme and showed that improved CCH2 scheme suffered from various attacks, that is, forgery attack and framing attack.

On Parameterized Exponential Time Complexity

2009 ◽  
pp. 168-177
Author(s):  
Jianer Chen ◽  
Iyad A. Kanj ◽  
Ge Xia
Keyword(s):  
Time Complexity ◽  
Exponential Time

An Efficient Algorithm for Automating Classification of Chemical Reactions into Classes in Ugi’s Reaction Scheme

2013 ◽  
pp. 285-296
Author(s):  
Sanjay Ram ◽  
Somnath Pal
Keyword(s):  
Chemical Reactions ◽  
Efficient Algorithm ◽  
Time Complexity ◽  
Symmetric Matrix ◽  
Reaction Scheme ◽  
Space Complexity ◽  
Average Case ◽  
Model Driven ◽  
Reaction Matrix

There are two approaches for classification of chemical reactions: Model-Driven and Data-Driven. In this paper, the authors develop an efficient algorithm based on a model-driven approach developed by Ugi and co-workers for classification of chemical reactions. The authors’ algorithm takes reaction matrix of a chemical reaction as input and generates its appropriate class as output. Reaction matrices being symmetric, matrix implementation of Ugi’s scheme using upper/lower tri-angular matrix is of O(n2) in terms of space complexity. Time complexity of similar matrix implementation is O(n4), both in worst case as well as in average case. The proposed algorithm uses two fixed size look-up tables in a novel way and requires constant space complexity. Time complexity both in worst and average cases of the algorithm is linear.

scholarly journals On the concept of algorithmic thinking

2018 ◽  
Vol 55 ◽  
pp. 03016 ◽  
Author(s):  
Olga Sadykova ◽  
Alexandr Usolzev
Keyword(s):  
Computer Science ◽  
Distinctive Features ◽  
Algorithmic Thinking

The article deals with the concept of “algorithmic thinking.” Details show the distinctive features of algorithmic thinking and the problems that arise in teaching Computer Science. Such phenomenon is called the “mosaic thinking,” which is also discussed in the paper.

scholarly journals Space and time complexity for infinite time Turing machines

2020 ◽  
Vol 30 (6) ◽  
pp. 1239-1255
Author(s):  
Merlin Carl
Keyword(s):  
Time Complexity ◽  
Space Complexity ◽  
Complexity Classes ◽  
Turing Machines ◽  
Infinite Time ◽  
Space And Time ◽  
Open Questions ◽  
Separation Results ◽  
Ordinal Computability

Abstract We consider notions of space by Winter [21, 22]. We answer several open questions about these notions, among them whether low space complexity implies low time complexity (it does not) and whether one of the equalities P=PSPACE, P$_{+}=$PSPACE$_{+}$ and P$_{++}=$PSPACE$_{++}$ holds for ITTMs (all three are false). We also show various separation results between space complexity classes for ITTMs. This considerably expands our earlier observations on the topic in Section 7.2.2 of Carl (2019, Ordinal Computability: An Introduction to Infinitary Machines), which appear here as Lemma $6$ up to Corollary $9$.

REDUCING SIMPLE GRAMMARS: EXPONENTIAL AGAINST HIGHLY-POLYNOMIAL TIME IN PRACTICE

2007 ◽  
Vol 18 (04) ◽  
pp. 715-725
Author(s):  
CÉDRIC BASTIEN ◽  
JUREK CZYZOWICZ ◽  
WOJCIECH FRACZAK ◽  
WOJCIECH RYTTER
Keyword(s):  
Polynomial Time ◽  
Experimental Analysis ◽  
Time Complexity ◽  
Packet Classification ◽  
State Machines ◽  
Worst Case ◽  
Exponential Time ◽  
Push Down

Simple grammar reduction is an important component in the implementation of Concatenation State Machines (a hardware version of stateless push-down automata designed for wire-speed network packet classification). We present a comparison and experimental analysis of the best-known algorithms for grammar reduction. There are two approaches to this problem: one processing compressed strings without decompression and another one which processes strings explicitly. It turns out that the second approach is more efficient in the considered practical scenario despite having worst-case exponential time complexity (while the first one is polynomial). The study has been conducted in the context of network packet classification, where simple grammars are used for representing the classification policies.

SIMULATIONS BY TIME-BOUNDED COUNTER MACHINES

2011 ◽  
Vol 22 (02) ◽  
pp. 395-409 ◽  
Author(s):  
HOLGER PETERSEN
Keyword(s):  
Lower Bound ◽  
Real Time ◽  
Polynomial Time ◽  
Time Complexity ◽  
Linear Time ◽  
Fixed Number ◽  
Exponential Time ◽  
New Family ◽  
Counter Machines ◽  
Time Bounds

We investigate the efficiency of simulations of storages by several counters. A simulation of a pushdown store is described which is optimal in the sense that reducing the number of counters of a simulator leads to an increase in time complexity. The lower bound also establishes a tight counter hierarchy in exponential time. Then we turn to simulations of a set of counters by a different number of counters. We improve and generalize a known simulation in polynomial time. Greibach has shown that adding s + 1 counters increases the power of machines working in time ns. Using a new family of languages we show here a tight hierarchy result for machines with the same polynomial time-bound. We also prove hierarchies for machines with a fixed number of counters and with growing polynomial time-bounds. For machines with one counter and an additional "store zero" instruction we establish the equivalence of real-time and linear time. If at least two counters are available, the classes of languages accepted in real-time and linear time can be separated.

An Algorithm for Testing Isomorphism of Planer Graph Based on Distant Matrix

2012 ◽  
Vol 487 ◽  
pp. 317-321
Author(s):  
Yan Peng Wu ◽  
Shui Qiang Liu
Keyword(s):  
Graph Theory ◽  
Polynomial Time ◽  
Time Complexity ◽  
Graph Isomorphism ◽  
Distance Matrix ◽  
Space Complexity ◽  
The Subject ◽  
The Many

The testing for graph isomorphism is one of the many problems in the subject of graph theory. This thesis proposes an algorithm for testing isomorphism of planer graph of polynomial time via structuring characteristics of planer graph based on distance matrix. The algorithm, with a time complexity of O (n^4) and a space complexity of O (n^2), has a great application value.

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