The document provides information on programmatically obtaining backtraces in C using functions from the execinfo.h header file. It describes the backtrace(), backtrace_symbols(), and backtrace_symbols_fd() functions for getting and translating a backtrace. It also gives examples of using these functions to print a backtrace after a crash.
Memory management is one of the most fundamental and important aspect for any computer programming language. In the dynamic memory allocation, the memory is allocated to a variable or program at the run time.
Pointers are among C’s most powerful, yet most difficult concepts to master. Some tasks like dynamic memory allocation done only by using pointers. So it is essential to learn pointers.
Pointers are a type of variable, just like int, double, etc., except instead of storing a value, they store a memory address of another variable.
Memory management is one of the most fundamental and important aspect for any computer programming language. In the dynamic memory allocation, the memory is allocated to a variable or program at the run time.
Pointers are among C’s most powerful, yet most difficult concepts to master. Some tasks like dynamic memory allocation done only by using pointers. So it is essential to learn pointers.
Pointers are a type of variable, just like int, double, etc., except instead of storing a value, they store a memory address of another variable.
I prepared this slides for the student of FSC BSC BS Computer Science Students. These Slides are very easy to read and understand the pointer logic used in C++ Programming.
All Topic related to pointer is discussed and examples are given
I prepared this slides for the student of FSC BSC BS Computer Science Students. These Slides are very easy to read and understand the pointer logic used in C++ Programming.
All Topic related to pointer is discussed and examples are given
Q1 Consider the below omp_trap1.c implantation, modify the code so t.pdfabdulrahamanbags
Q1 Consider the below omp_trap1.c implantation, modify the code so that: i. The time used by
the parallel block is timed using the OpenMP function omp_get_wtime(). The syntax is double
omp_get_wtime ( void ) It returns the number of seconds that have elapsed since some time in
the past. ii. Now on a system with at least two cores, time the program with a. one thread and a
large value of n, and b. two threads and the same value of n. Explain what happens? Then Do the
same measurements for the omp_trap2.c code.
1. How does its performance compare with the performance of the omp_trap1.c ?
2. Explain your answers.
3. provide with your answers the code and detailed screenshots showing how did you compile
and run the code and times for each run:
/* File: omp_trap1.c * Purpose: Estimate definite integral (or area under curve) using trapezoidal
rule. * Input: a, b, n * Output: estimate of integral from a to b of f(x) * using n trapezoids. * *
Compile: gcc -g -Wall -fopenmp -o omp_trap1 omp_trap1.c * Usage: ./omp_trap1 * * Notes: *
1. The function f(x) is hardwired. * 2. In this version, each thread explicitly computes the
integral over its assigned subinterval, a critical directive is used for the global sum. * 3. This
version assumes that n is evenly divisible by the number of threads #include #include #include
#include void Usage(char* prog_name); double f(double x); /* Function we're integrating */
double Local_trap ( double a , double b , i n t n ) ; int main(int argc, char* argv[]) { double
global_result = 0.0; /* Store result in global_result */ double a, b; /* Left and right endpoints */
int n; /* Total number of trapezoids */ int thread_count; if (argc != 2) Usage(argv[0]);
thread_count = strtol(argv[1], NULL, 10); printf("Enter a, b, and n\n"); scanf("%lf %lf %d", &a,
&b, &n); if (n % thread_count != 0) Usage(argv[0]); double global_result = 0.0; # pragma omp p
a r a l l e l num_threads ( t h r e a d _ c o u n t ) { # pragma omp c r i t i c a l global_result +=
Local_trap ( double a , double b , i n t n ) ; } printf("With n = %d trapezoids, our estimate\n", n);
printf("of the integral from %f to %f = %.14e\n", a, b, global_result); return 0; } /* main */ /*----
---------------------------------------------------------------- * Function: Usage * Purpose: Print
command line for function and terminate * In arg: prog_name */ void Usage(char* prog_name) {
fprintf(stderr, "usage: %s \n", prog_name); fprintf(stderr, " number of trapezoids must be evenly
divisible by\n"); fprintf(stderr, " number of threads\n"); exit(0); } /* Usage */ /*---------------------
--------------------------------------------- * Function: f * Purpose: Compute value of function to be
integrated * Input arg: x * Return val: f(x) */ double f(double x) { double return_val; return_val
= x*x; return return_val; } /* f */ /*------------------------------------------------------------------ *
Function: Trap * Purpose: Use trapezoidal rule to estimate definite integral * Input args.
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Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
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.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
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.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
2. GOAL The main goal of this document is to provide some information about the signal handling used for dumping the bacltrace due after a crash.
3. A backtrace is a list of the function calls that are currently active in a thread. The usual way to inspect a backtrace of a program is to use an external debugger such as gdb. H owever, sometimes it is useful to obtain a backtrace programmatically from within a program, e.g., for the purposes of logging or diagnostics. The header file `execinfo.h' declares three functions that obtain and manipulate backtraces of the current thread. Function: int backtrace(void **buffer, int size) The backtrace function obtains a backtrace for the current thread, as a list of pointers, and places the information into buffer. The argument size should be the number of void * elements that will fit into buffer. The return value is the actual number of entries of buffer that are obtained, and is at most size. The pointers placed in buffer are actually return addresses obtained by inspecting the stack, one return address per stack frame. Note that certain compiler optimizations may interfere with obtaining a valid backtrace. Function inlining causes the inlined function to not have a stack frame; tail call optimization replaces one stack frame with another; frame pointer elimination will stop backtrace from interpreting the stack contents correctly. Usage
4. Function: char ** backtrace_symbols (void *const *buffer, int size) The backtrace_symbols function translates the information obtained from the backtrace function into an array of strings. The argument buffer should be a pointer to an array of addresses obtained via the backtrace function, and size is the number of entries in that array (the return value of backtrace). The return value is a pointer to an array of strings, which has size entries just like the array buffer. Each string contains a printable representation of the corresponding element of buffer. It includes the function name (if this can be determined), an offset into the function, and the actual return address (in hexadecimal). Currently, the function name and offset only be obtained on systems that use the ELF binary format for programs and libraries. On other systems, only the hexadecimal return address will be present. Also, you may need to pass additional flags to the linker to make the function names available to the program. (For example, on systems using GNU ld, you must pass (-rdynamic.) The return value of backtrace_symbols is a pointer obtained via the malloc function, and it is the responsibility of the caller to free that pointer. Note that only the return value need be freed, not the individual strings. The return value is NULL if sufficient memory for the strings cannot be obtained. Usage
5. Function: void backtrace_symbols_fd (void *const *buffer, int size, int fd) The backtrace_symbols_fd function performs the same translation as the function backtrace_symbols function. Instead of returning the strings to the caller, it writes the strings to the file descriptor fd, one per line. It does not use the malloc function, and can therefore be used in situations where that function might fail. The following program illustrates the use of these functions. Note that the array to contain the return addresses returned by backtrace is allocated on the stack. Therefore code like this can be used in situations where the memory handling via malloc does not work anymore (in which case the backtrace_symbols has to be replaced by a backtrace_symbols_fd call as well). The number of return addresses is normally not very large. Even complicated programs rather seldom have a nesting level of more than, say, 50 and with 200 possible entries probably all programs should be covered. Usage
6. #include <execinfo.h> #include <stdio.h> #include <stdlib.h> /* Obtain a backtrace and print it to stdout. */ void print_trace(void) { void* array[10]; size_t size; char** strings; size_t i; size = backtrace(array, 10); strings = backtrace_symbols(array, size); printf ("Obtained %zd stack frames.", size); for (i = 0; i < size; i++) { printf ("%s", strings[i]); } /* FOR */ free (strings); } /* print_trace */ /* A dummy function to make the backtrace more interesting. */ void dummy_function(void) { print_trace(); } /* dummy_function */ Int main(void) { dummy_function (); return 0; } First example
7. #include <stdio.h> #include <stdlib.h> #include <signal.h> #include <unistd.h> #include <sys/times.h> #include <sys/ucontext.h> #include <asm/unistd.h> #include <execinfo.h> struct dict_entry { int num; const char *s; }; #define DICT_ENTRY_END { -1, NULL } #define PRINTF(fmt...) fprintf(stderr,fmt); static int mainpid=0; /* * Simple dictionary * Search an array terminated by an entry with s field set to NULL * If number not found, return "(unknown)" string */ static const char * search_dict(const struct dict_entry *dict, int num) { const struct dict_entry *p = dict; while (p->s) { if (num == p->num) return p->s; p++; } return "(unknown)"; } Second example 1/6