Bottom-up parsing builds parse trees starting from the leaves (terminals) and working towards the root (start symbol). It can handle a more general class of grammars than top-down parsing. Shift-reduce parsing splits the input string into two parts separated by a special character, with terminals on the right. It uses two actions: shift moves a terminal from right to left, and reduce applies a production to remove symbols from the left. Conflicts can occur when it is possible to shift or reduce, or to reduce in different ways. Handles mark points where reduction also allows deriving the start symbol.
This slide is prepared By these following Students of Dept. of CSE JnU, Dhaka. Thanks To: Nusrat Jahan, Arifatun Nesa, Fatema Akter, Maleka Khatun, Tamanna Tabassum.
Syntax Analysis: Introduction, Context-Free Grammars, Writing a Grammar, Top-Down Parsing, Bottom-Up Parsing, Introduction to LR Parsing: Simple LR, More Powerful LR Parsers, Using Ambiguous Grammars, Parser Generators.
Points covered in this PPT: Syntax Analysis - CFG, top-down and bottom-up parsers, RDP, Predictive parser, SLR,LR(1), LALR parsers, using ambiguous grammar, Error detection and recovery, automatic construction of parsers using YACC,
Introduction to Semantic analysis-Need of semantic analysis, type checking and type conversion.
This slide is prepared By these following Students of Dept. of CSE JnU, Dhaka. Thanks To: Nusrat Jahan, Arifatun Nesa, Fatema Akter, Maleka Khatun, Tamanna Tabassum.
Syntax Analysis: Introduction, Context-Free Grammars, Writing a Grammar, Top-Down Parsing, Bottom-Up Parsing, Introduction to LR Parsing: Simple LR, More Powerful LR Parsers, Using Ambiguous Grammars, Parser Generators.
Points covered in this PPT: Syntax Analysis - CFG, top-down and bottom-up parsers, RDP, Predictive parser, SLR,LR(1), LALR parsers, using ambiguous grammar, Error detection and recovery, automatic construction of parsers using YACC,
Introduction to Semantic analysis-Need of semantic analysis, type checking and type conversion.
This is the presentation on Syntactic Analysis in NLP.It includes topics like Introduction to parsing, Basic parsing strategies, Top-down parsing, Bottom-up
parsing, Dynamic programming – CYK parser, Issues in basic parsing methods, Earley algorithm, Parsing
using Probabilistic Context Free Grammars.
Information representation, Floating point representation (IEEE 754), computer arithmetic and their implementation; Fixed-point Arithmetic: Addition, Subtraction, Multiplication and Division, Memory Technology, static and dynamic memory, Random Access and Serial Access Memories, Cache memory and Memory Hierarchy, Address Mapping, Cache updation schemes, Virtual memory and memory management unit.
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Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
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Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
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Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
2. Bottom-Up Parsing
• Given a grammar G, a parse tree for a given string is constructed by
starting at the leaves (terminals of the string) and working to the root
(the start symbol S).
• They are able to accept a more general class of grammars compared to
top-down predictive parsers.
• It builds on the concepts developed in top-down parsing.
• Preferred method for most of the parser generators including bison
• They don’t need left-factored grammars
– So, its valid to use the following grammar
E T + E | T
T int * T | int | (E)
3. • A parse for a string generates a sequence of derivations of the
form:
S δ0 δ1 δ2 … … δn-1 sentence
• Bottom-up parsing reduces a string to the start symbol by
inverting productions
Bottom-Up Parsing
• Let A b be a production and δi-1 and δi be two consecutive
derivations with sentential forms: αAβ and αbβ
– δi-1 is derived from δi by match the RHS b in δi, and then replacing b with
its corresponding LHS, A. This is called a reduction
• The parse tree is the result of the tokens and the reductions.
4. • Consider the parse for the input string: int * int + int
E T + E | T
T int * T | int | (E)
• When we reduce, we only have
terminals to the right.
Sentential Form Productions
int * int + int
int * T + int T int
T + int T int * T
T + T T int
Bottom-Up Parsing
terminals to the right.
– In the reduction: αAβ αbβ
– If b to A is a step of a bottom-up
parsing (i.e. A b is a reduction)
– Then β is a string of terminals
• In other words, a bottom-up parser traces a rightmost derivation
in reverse
T + E E T
E E T+E
5. Shift-Reduce Parsing
• Idea: Split string being parsed into two parts:
– Two parts are separated by a special character ‘|’
– Left part is a string of terminals and non terminals
– Right part is a string of terminals
• Still to be examined
• Bottom up parsing has two actions• Bottom up parsing has two actions
– Shift: Move terminal symbol from right string to left string
• ABC | xyz ABCx | yz
– Reduce: Apply an inverse production at the right end of the
left string
– If A xy is a production, then
• Cbxy | ijk CbA | ijk
6. Sentential Form Productions
|int * int + int Shift
int | * int + int Shift
int * | int + int Shift
int * int | + int Reduce T int
int * T | + int Reduce T int * T
Shift-Reduce Example
int * T | + int Reduce T int * T
T | + int Shift
T + | int Shift
T + int | Reduce T int
T + T | Reduce E T
T + E | Reduce E T+E
E | Accept
7. To Shift or Reduce
• Symbols on the left of “|” are kept on a stack
– Top of the stack is at “|”
– Shift pushes a terminal on the stack
– Reduce pops symbols (RHS of production) and pushes a
non terminal (LHS of production) onto the stack
• The most important issues are:
– When to shift and when to reduce!
– Which production to use for reduction?
– Sometimes parser can reduce but it should not!
– X Є can always be reduced!
– Sometimes parser can reduce in different ways!
8. • In a given state, more than one action (shift or
reduce) may lead to a valid parse
– If it is legal to shift or reduce:
• Shift-reduce conflict
– If it is legal to reduce by two different productions:
To Shift or Reduce ? - Conflicts
– If it is legal to reduce by two different productions:
• Reduce-reduce conflict
• Reduce action should be taken only if the result
can be reduced to the start symbol
9. Shift-Reduce Parsing - Handles
• A substring that matches the right-side of a production
that occurs as one step in the rightmost derivation. This
substring is called a handle.
• Because d is a right-sentential form, the substring to the
right of a handle contains only terminal symbols.
Therefore, the parser doesn’t need to scan past theTherefore, the parser doesn’t need to scan past the
handle.
• If a grammar is unambiguous, then every right
sentential form has a unique handle
• If we can find those handles, we can build a derivation
10. Recognizing Handles
• Given the grammar: E T + E | T
T int * T | int | (E)
• Consider step : int | * int + int
• We could reduce by T int giving T | * int + int
– But this is incorrect because:
• No way to reduce to the start symbol E
• So, a handle is a reduction that also allows further
reductions back to the start symbol
• In shift-reduce parsing, handles appear only at the top
of the stack, never inside
11. • Handles always appear only at stack top:
– Immediately after reducing a handle
– Right-most non-terminal on top of the stack
– Next handle must be to right of right-most non-
terminal, because this is a right-most derivation
– Sequence of shift moves reaches next handle
Recognizing Handles
– Sequence of shift moves reaches next handle
• It is not obvious how to detect handles
• At each step the parser sees only the stack, not the
entire input; start with that . . .
• α is a viable prefix if there is a β such that α|β is a
state of a shift-reduce parser
12. Viable Prefixes
• A viable prefix does not extend past the right end
of the handle
• It’s a viable prefix because it is a prefix of the
handle
• As long as a parser has viable prefixes on the
stack no parsing error has been detectedstack no parsing error has been detected
• For any grammar, the set of viable prefixes is a
regular language
• So, we can generate an automata to recognize
viable prefixes!