Lexical Analysis, Tokens, Patterns, Lexemes, Example pattern, Stages of a Lexical Analyzer, Regular expressions to the lexical analysis, Implementation of Lexical Analyzer, Lexical analyzer: use as generator.
Lexical Analysis, Tokens, Patterns, Lexemes, Example pattern, Stages of a Lexical Analyzer, Regular expressions to the lexical analysis, Implementation of Lexical Analyzer, Lexical analyzer: use as generator.
A Parser is an integral part when building a Domain Specific Language or file format parser, such as our example usage case: the Ical format. This session will cover the general concept about tokenizing and parsing into a datastructure, as well as going into depth about how to keep the memory footprint and runtime low with the help of a stream-tokenizer.
It is on simple topic of compiler but first and foremost important topic of compiler. For Lexical Analyzing we coded in C language. So it is easy to understand .
Lexical analyzer, tokenizer, scanner, or lexer is a function that is invoked by the syntax analyzer. This function returns the nxt lexicon or word in the source file.
A Parser is an integral part when building a Domain Specific Language or file format parser, such as our example usage case: the Ical format. This session will cover the general concept about tokenizing and parsing into a datastructure, as well as going into depth about how to keep the memory footprint and runtime low with the help of a stream-tokenizer.
It is on simple topic of compiler but first and foremost important topic of compiler. For Lexical Analyzing we coded in C language. So it is easy to understand .
Lexical analyzer, tokenizer, scanner, or lexer is a function that is invoked by the syntax analyzer. This function returns the nxt lexicon or word in the source file.
Whats your Needs ? What need to learn about Compiler Design?
---------------- Reference :Compilers Principles,Techniques and Tools -By Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman ---------
match the following attributes to the parts of a compilerstrips ou.pdfarpitaeron555
match the following attributes to the parts of a compiler
strips out the comments and whitespace
converts text into lexemes
generates an Abstrat Symbol Tree
recursive descent or table driven
uses BNF or EBNF definitions
a. lexer
b. parser
Solution
The Program and Portfolio Management Maturity Model is an effective tool for organizations to
decide quickly what PPM improvements they should make to enhance their organization\'s
ability to optimize investments, execute big changes and deliver value.
Overview
Key Findings
Real project, program and portfolio management, when operating at the level of well-integrated
practices, is the key enabler that allows organizations to identify and execute strategic change.
Any meaningful undertakings to enhance or evolve the program and portfolio management
(PPM) function must pay more than lip service to organizational structure, business model and
culture to have any chance of success.
Competitive pressures and changing market conditions are forcing organizations toward Level 3,
and most organizations still aren\'t ready to make the leap.
Recommendations
At any level of PPM maturity, focus first on helping the organization make well-informed
investment choices. This will improve the odds of project success more than any other factor.
For organizations that require enterprisewide change and capabilities, it is worth the effort to
pursue Level 4, where enterprise PPM practices are built.
Identify objectives for your enterprise, and use them to identify the most salient improvement
opportunities for your enterprise.
Meticulously manage the change involved in maturing/improving your PPM capabilities.
Analysis
Project/program/portfolio management office (PMO) leaders, program managers and portfolio
managers are frequently challenged by ineffective processes, lack of stakeholder engagement and
difficult-to-quantify value. 1 Part of the problem is failure to match their processes, people and
technology approaches to the maturity level of their organizations. 2
The Gartner Program and Portfolio Management (PPM) Maturity Model assessment is designed
to help PPM leaders understand best practices around large project management, as well as PPM
to handle delivery of strategic value. This model assumes that organizations progress through a
maturity curve and that each level of organizational maturity directly affects the level of
investment and types of PPM approaches organizations choose to adopt.
arsing
A parser is an algorithm that determines whether a given input string is in a language and, as a
side-effect, usually produces a parse tree for the input. There is a procedure for generating a
parser from a given context-free grammar.
Recursive-Descent Parsing
Recursive-descent parsing is one of the simplest parsing techniques that is used in practice.
Recursive-descent parsers are also called top-down parsers, since they construct the parse tree
top down (rather than bottom up).
The basic idea of recursive-descent par.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Leading Change strategies and insights for effective change management pdf 1.pdf
4 lexical and syntax analysis
1. ICS 313 - Fundamentals of Programming Languages 1
4. Lexical and Syntax Analysis
4.1 Introduction
Language implementation systems must analyze source code,
regardless of the specific implementation approach
Nearly all syntax analysis is based on a formal description of the
syntax of the source language (BNF)
The syntax analysis portion of a language processor nearly always
consists of two parts:
A low-level part called a lexical analyzer (mathematically, a finite
automaton based on a regular grammar)
A high-level part called a syntax analyzer, or parser (mathematically, a
push-down automaton based on a context-free grammar, or BNF)
Reasons to use BNF to describe syntax:
Provides a clear and concise syntax description
The parser can be based directly on the BNF
Parsers based on BNF are easy to maintain
2. ICS 313 - Fundamentals of Programming Languages 2
4.1 Introduction (continued)
Reasons to separate lexical and syntax analysis:
Simplicity - less complex approaches can be used for
lexical analysis; separating them simplifies the parser
Efficiency - separation allows optimization of the lexical
analyzer
Portability - parts of the lexical analyzer may not be
portable, but the parser always is portable
4.2 Lexical Analysis
A lexical analyzer is a pattern matcher for character
strings
A lexical analyzer is a “front-end” for the parser
Identifies substrings of the source program that
belong together - lexemes
Lexemes match a character pattern, which is
associated with a lexical category called a token
sum is a lexeme; its token may be IDENT
3. ICS 313 - Fundamentals of Programming Languages 3
4.2 Lexical Analysis (continued)
The lexical analyzer is usually a function that is called by the
parser when it needs the next token
Three approaches to building a lexical analyzer:
1. Write a formal description of the tokens and use a software tool
that constructs table-driven lexical analyzers given such a
description
2. Design a state diagram that describes the tokens and write a
program that implements the state diagram
3. Design a state diagram that describes the tokens and hand-
construct a table-driven implementation of the state diagram
We only discuss approach 2
4.2 Lexical Analysis (continued)
State diagram design:
A naive state diagram would have a transition from every state
on every character in the source language - such a diagram
would be very large!
In many cases, transitions can be combined to simplify the
state diagram
When recognizing an identifier, all uppercase and lowercase
letters are equivalent - Use a character class that includes all
letters
When recognizing an integer literal, all digits are equivalent -
use a digit class
Reserved words and identifiers can be recognized together
(rather than having a part of the diagram for each reserved
word)
Use a table lookup to determine whether a possible identifier is in fact a reserved
word
4. ICS 313 - Fundamentals of Programming Languages 4
4.2 Lexical Analysis (continued)
Convenient utility subprograms:
getChar - gets the next character of input, puts it in
nextChar, determines its class and puts the class in
charClass
addChar - puts the character from nextChar into the place
the lexeme is being accumulated, lexeme
lookup - determines whether the string in lexeme is a
reserved word (returns a code)
4.2 Lexical Analysis (continued)
Implementation (assume initialization):
int lex() {
switch (charClass) {
case LETTER:
addChar();
getChar();
while (charClass == LETTER ||
charClass == DIGIT) {
addChar();
getChar();
}
return lookup(lexeme);
break;
case DIGIT:
addChar();
getChar();
while (charClass == DIGIT) {
addChar();
getChar();
}
return INT_LIT;
break;
} /* End of switch */
} /* End of function lex */
5. ICS 313 - Fundamentals of Programming Languages 5
4.3 The Parsing Problem
Goals of the parser, given an input program:
Find all syntax errors; For each, produce an appropriate diagnostic
message, and recover quickly
Produce the parse tree, or at least a trace of the parse tree, for the
program
Two categories of parsers
Top down - produce the parse tree, beginning at the root
Order is that of a leftmost derivation
Bottom up - produce the parse tree, beginning at the leaves
Order is the that of the reverse of a rightmost derivation
Parsers look only one token ahead in the input
Top-down Parsers
Given a sentential form, xAα , the parser must choose the correct A-rule to
get the next sentential form in the leftmost derivation, using only the first
token produced by A
The most common top-down parsing algorithms:
Recursive descent - a coded implementation
LL parsers - table driven implementation
4.3 The Parsing Problem (continued)
Bottom-up parsers
Given a right sentential form, α, what substring of α is the right-
hand side of the rule in the grammar that must be reduced to
produce the previous sentential form in the right derivation
The most common bottom-up parsing algorithms are in the LR
family (LALR, SLR, canonical LR)
The Complexity of Parsing
Parsers that works for any unambiguous grammar are complex
and inefficient (O(n3), where n is the length of the input)
Compilers use parsers that only work for a subset of all
unambiguous grammars, but do it in linear time (O(n), where n
is the length of the input)
6. ICS 313 - Fundamentals of Programming Languages 6
4.4 Recursive-Descent Parsing
Recursive Descent Process
There is a subprogram for each nonterminal in the grammar, which can
parse sentences that can be generated by that nonterminal
EBNF is ideally suited for being the basis for a recursive-descent
parser, because EBNF minimizes the number of nonterminals
A grammar for simple expressions:
<expr> → <term> {(+ | -) <term>}
<term> → <factor> {(* | /) <factor>}
<factor> → id | ( <expr> )
Assume we have a lexical analyzer named lex, which puts the next
token code in nextToken
The coding process when there is only one RHS:
For each terminal symbol in the RHS, compare it with the next input token;
if they match, continue, else there is an error
For each nonterminal symbol in the RHS, call its associated parsing
subprogram
4.4 Recursive-Descent Parsing (continued)
/* Function expr
Parses strings in the language generated by the rule:
<expr> → <term> {(+ | -) <term>} */
void expr() {
/* Parse the first term */
term();
/* As long as the next token is + or -, call
lex to get the next token, and parse the next term */
while (nextToken == PLUS_CODE ||
nextToken == MINUS_CODE){
lex();
term();
}
}
This particular routine does not detect errors
Convention: Every parsing routine leaves the next token in nextToken
7. ICS 313 - Fundamentals of Programming Languages 7
4.4 Recursive-Descent Parsing (continued)
A nonterminal that has more than one RHS requires
an initial process to determine which RHS it is to
parse
The correct RHS is chosen on the basis of the next token
of input (the lookahead)
The next token is compared with the first token that can
be generated by each RHS until a match is found
If no match is found, it is a syntax error
4.4 Recursive-Descent Parsing (continued)
/* Function factor
Parses strings in the language generated by
the rule: <factor> -> id | (<expr>) */
void factor() {
/* Determine which RHS */
if (nextToke == ID_CODE)
/* For the RHS id, just call lex */
lex();
/* If the RHS is (<expr>) – call lex to pass
over the left parenthesis, call expr, and
check for the right parenthesis */
else if (nextToken == LEFT_PAREN_CODE) {
lex();
expr();
if (nextToken == RIGHT_PAREN_CODE)
lex();
else
error();
} /* End of else if (nextToken == ... */
else error(); /* Neither RHS matches */
}
8. ICS 313 - Fundamentals of Programming Languages 8
4.4 Recursive-Descent Parsing (continued)
The LL Grammar Class
The Left Recursion Problem
If a grammar has left recursion, either direct or indirect, it cannot be the
basis for a top-down parser
A grammar can be modified to remove left recursion
The other characteristic of grammars that disallows top-down parsing is
the lack of pairwise disjointness
The inability to determine the correct RHS on the basis of one token of
lookahead
Def: FIRST(α) = {a | α =>* aβ } (If α =>* ε, ε is in FIRST(α))
Pairwise Disjointness Test:
For each nonterminal, A, in the grammar that has more than one RHS, for
each pair of rules, A → αi and A → αj, it must be true that FIRST(αi) ∩
FIRST(αj) = φ
Examples:
A → a | bB | cAb
A → a | aB
4.4 Recursive-Descent Parsing (continued)
Left factoring can resolve the problem
Replace
<variable> → identifier | identifier [<expression>]
with
<variable> → identifier <new>
<new> → ε | [<expression>]
or
<variable> → identifier [[<expression>]]
(the outer brackets are metasymbols of EBNF)
9. ICS 313 - Fundamentals of Programming Languages 9
4.5 Bottom-up Parsing
The parsing problem is finding the correct RHS in a right-
sentential form to reduce to get the previous right-sentential
form in the derivation
Intuition about handles:
Def: β is the handle of the right sentential form
γ = αβw if and only if S =>*rm αAw => αβw
Def: β is a phrase of the right sentential form
γ if and only if S =>* γ = α1Aα2 =>+ α1βα2
Def: β is a simple phrase of the right sentential form γ if and
only if S =>* γ = α1Aα2 => α1βα2
The handle of a right sentential form is its leftmost simple
phrase
Given a parse tree, it is now easy to find the handle
Parsing can be thought of as handle pruning
4.5 Bottom-up Parsing (continued)
Shift-Reduce Algorithms
Reduce is the action of replacing the handle on the top of the
parse stack with its corresponding LHS
Shift is the action of moving the next token to the top of the
parse stack
Advantages of LR parsers:
They will work for nearly all grammars that describe
programming languages
They work on a larger class of grammars than other bottom-up
algorithms, but are as efficient as any other bottom-up parser
They can detect syntax errors as soon as it is possible
The LR class of grammars is a superset of the class parsable
by LL parsers
10. ICS 313 - Fundamentals of Programming Languages 10
4.5 Bottom-up Parsing (continued)
LR parsers must be constructed with a tool
Knuth’s insight: A bottom-up parser could use the
entire history of the parse, up to the current point, to
make parsing decisions
There were only a finite and relatively small number of
different parse situations that could have occurred, so the
history could be stored in a parser state, on the parse
stack
An LR configuration stores the state of an LR parser
(S0X1S1X2S2…XmSm, aiai+1…an$)
4.5 Bottom-up Parsing (continued)
LR parsers are table driven, where the table has two
components, an ACTION table and a GOTO table
The ACTION table specifies the action of the parser,
given the parser state and the next token
Rows are state names; columns are terminals
The GOTO table specifies which state to put on top of the
parse stack after a reduction action is done
Rows are state names; columns are nonterminals
11. ICS 313 - Fundamentals of Programming Languages 11
4.5 Bottom-up Parsing (continued)
Initial configuration: (S0, a1…an$)
Parser actions:
If ACTION[Sm, ai] = Shift S, the next configuration is:
(S0X1S1X2S2…XmSmaiS, ai+1…an$)
If ACTION[Sm, ai] = Reduce A → β and S = GOTO[Sm-r, A],
where r = the length of β, the next configuration is
(S0X1S1X2S2…Xm-rSm-rAS, aiai+1…an$)
If ACTION[Sm, ai] = Accept, the parse is complete and no errors
were found
If ACTION[Sm, ai] = Error, the parser calls an error-handling
routine
A parser table can be generated from a given grammar
with a tool, e.g., yacc
4.5 Bottom-up Parsing (continued)
Reduce 4 (use GOTO[6, T])
…
* id $
…
0E1+6F3
…
Reduce 6 (use GOTO[6, F])* id $0E1+6id5
Shift 5id * id $0E1+6
Shift 6+ id * id $0E1
Reduce 2 (use GOTO[0, E])+ id * id $0T2
Reduce 4 (use GOTO[0, T])+ id * id $0F3
Reduce 6 (use GOTO[0, F])+ id * id $0id5
Shift 5id + id * id $0
ActionInputStack
1. E → E + T
2. E → T
3. T → T * F
4. T → F
5. F → (E)
6. F → id