This document describes a proposed Applicant Qualification Filtering System that uses tests and a weighted-sum calculation method to rank and shortlist job applicants for employers. The system would have applicants complete personality, aptitude, and skills tests. It would calculate scores for each test component, weight them, and total the scores to generate an overall percentage for each applicant. Applicants would be ranked based on their scores, and employers could view a shortlist of the highest scoring candidates to interview. The document outlines the system's introduction, problem statement, objectives, process model, data model, solution complexity involving the weighted-sum method, proof of concept, and references.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Validation and Verification of SYSML Activity Diagrams Using HOARE Logic ijseajournal
SysML diagrams are significant medium using for supporting software lifecycle management. The existing TBFV method is designed for error detection with full automation efficiency, only for code. For verifying the correctness of SysML diagram, we applying TBFV method into SysML diagram. In this paper, we
propose a novel technique that makes use of Hoare Logic and testing to verify whether the SysML diagrams meet the requirement, called TBFV-M. This research can improve the correctness of SysML diagram, which is likely to significantly affect the reliability of the implementation. A case study is conducted to show its feasibility and used to illustrate how the proposed method is applied; and discussion on potential
challenges to TBFV-M is also presented.
Software Testing Outline Performances and Measurementsijtsrd
The procedure of carrying out a program or else scheme by means of the target of ruling bugs called “Software s w Testing”. It is whichever action intended by estimating a characteristic or else ability of a program system plus shaping that it congregates its requisite consequences. Testing is an essential piece in s w growth. It is generally arranged in each stage in the s w progress sequence. Classically, in excess of fifty two perecent of the progress period is used up in testing. Metrics are attainmenting significance plus receiving in commercial segments as associations raise, grown up and endeavour to get better venture values. This study talks about s w testing methods as well as measurements. Indu Maurya "Software Testing Outline: Performances and Measurements" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38550.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38550/software-testing-outline-performances-and-measurements/indu-maurya
Test Case Optimization and Redundancy Reduction Using GA and Neural Networks IJECEIAES
More than 50% of software development effort is spent in testing phase in a typical software development project. Test case design as well as execution consume a lot of time. Hence, automated generation of test cases is highly required. Here a novel testing methodology is being presented to test objectoriented software based on UML state chart diagrams. In this approach, function minimization technique is being applied and generate test cases automatically from UML state chart diagrams. Software testing forms an integral part of the software development life cycle. Since the objective of testing is to ensure the conformity of an application to its specification, a test “oracle” is needed to determine whether a given test case exposes a fault or not. An automated oracle to support the activities of human testers can reduce the actual cost of the testing process and the related maintenance costs. In this paper, a new concept is being presented using an UML state chart diagram and tables for the test case generation, artificial neural network as an optimization tool for reducing the redundancy in the test case generated using the genetic algorithm. A neural network is trained by the backpropagation algorithm on a set of test cases applied to the original version of the system.
This is the chapter 3 of ISTQB Advance Test Automation Engineer certification. This presentation helps aspirants understand and prepare content of certification.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Validation and Verification of SYSML Activity Diagrams Using HOARE Logic ijseajournal
SysML diagrams are significant medium using for supporting software lifecycle management. The existing TBFV method is designed for error detection with full automation efficiency, only for code. For verifying the correctness of SysML diagram, we applying TBFV method into SysML diagram. In this paper, we
propose a novel technique that makes use of Hoare Logic and testing to verify whether the SysML diagrams meet the requirement, called TBFV-M. This research can improve the correctness of SysML diagram, which is likely to significantly affect the reliability of the implementation. A case study is conducted to show its feasibility and used to illustrate how the proposed method is applied; and discussion on potential
challenges to TBFV-M is also presented.
Software Testing Outline Performances and Measurementsijtsrd
The procedure of carrying out a program or else scheme by means of the target of ruling bugs called “Software s w Testing”. It is whichever action intended by estimating a characteristic or else ability of a program system plus shaping that it congregates its requisite consequences. Testing is an essential piece in s w growth. It is generally arranged in each stage in the s w progress sequence. Classically, in excess of fifty two perecent of the progress period is used up in testing. Metrics are attainmenting significance plus receiving in commercial segments as associations raise, grown up and endeavour to get better venture values. This study talks about s w testing methods as well as measurements. Indu Maurya "Software Testing Outline: Performances and Measurements" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38550.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38550/software-testing-outline-performances-and-measurements/indu-maurya
Test Case Optimization and Redundancy Reduction Using GA and Neural Networks IJECEIAES
More than 50% of software development effort is spent in testing phase in a typical software development project. Test case design as well as execution consume a lot of time. Hence, automated generation of test cases is highly required. Here a novel testing methodology is being presented to test objectoriented software based on UML state chart diagrams. In this approach, function minimization technique is being applied and generate test cases automatically from UML state chart diagrams. Software testing forms an integral part of the software development life cycle. Since the objective of testing is to ensure the conformity of an application to its specification, a test “oracle” is needed to determine whether a given test case exposes a fault or not. An automated oracle to support the activities of human testers can reduce the actual cost of the testing process and the related maintenance costs. In this paper, a new concept is being presented using an UML state chart diagram and tables for the test case generation, artificial neural network as an optimization tool for reducing the redundancy in the test case generated using the genetic algorithm. A neural network is trained by the backpropagation algorithm on a set of test cases applied to the original version of the system.
This is the chapter 3 of ISTQB Advance Test Automation Engineer certification. This presentation helps aspirants understand and prepare content of certification.
Tool Support for Testing as Chapter 6 of ISTQB Foundation 2018. Topics covered are Tool Benefits, Test Tool Classification, Benefits of Test Automation, Risk of Test Automation, Selecting a tool for Organization, Pilot Project, Success factor for using a tool
Real time implementation of the software system requires being more versatile. In the maintenance phase, the modified system under regression testing must assure that the existing system remains defect free. Test case prioritization technique of regression testing includes code as well as model based methods of prioritizing the test cases. System model based test case prioritization can detect the severe faults early as compare to the code based test case prioritization. Model based prioritization techniques based on requirements in a cost effective manner has not been taken for study so far. Model based testing used to test the functionality of the software system based on requirement. An effective model based approach is defined for prioritizing test cases and to generate the effective test sequence. The test cases are rescheduled based on requirement analysis and user view analysis. With the use of weighted approach the overall cost is estimated to test the functionality of the model elements. Here, the genetic approach has been applied to generate efficient test path. The regression cost in terms of effort has been reduced under model based prioritization approach.
Projek Sarjana Muda (PSM) / Final Year Project (FYP)
Tajuk : REQUIREMENT TRACEABILITY OF ECAMPUS SYSTEM OF INTEGRATED UNIVERSITY MANAGEMENT SYSTEM FORUNIVERSITI ISLAM MALAYSIA
EXTRACTING THE MINIMIZED TEST SUITE FOR REVISED SIMULINK/STATEFLOW MODELijaia
Test case generation techniques are successfully employed to generate test cases from a formal model. A problem is that as the model evolves, test suites tend to grow in size, making it too costly to execute entire test suites. This paper aims to propose a practical approach to reduce the size of test suites for modified Simulink/Stateflow (SL/SF) model, which is popularly used for modeling software behavior in many industries like automobile manufacturers. The model for describing a system is frequently modified until it is fixed. The proposed technique is capable of extracting the minimized sized test suite in terms of test coverage, by taking into account both the modified and the affected portion of revised SL/SF model. Two real models for the ECUs deployed in a commercial car are used for an empirical study.
Configuration Navigation Analysis Model for Regression Test Case Prioritizationijsrd.com
Regression testing has been receiving increasing attention nowadays. Numerous regression testing strategies have been proposed. Most of them take into account various metrics like cost as well as the ability to find faults quickly thereby saving overall testing time. In this paper, a new model called the Configuration Navigation Analysis Model is proposed which tries to consider all stakeholders and various testing aspects while prioritizing regression test cases.
EXPERIMENTAL EVALUATION AND RESULT DISCUSSION OF METAMORPHIC TESTING AUTOMATI...IAEME Publication
Metamorphic Testing is an attribute relations based testing, used to mitigate the test oracle problem in testing complex non-testable programs. MTAF stands for Metamorphic Testing Automation Framework, introduced to eliminate the human intervention in creating test cases, mapping the relations, executing the statements and identifying the errors from input programs. MTAF is especially designed to address the test oracle problem of two most popular non-testable program domains are Multi Precision Arithmetic (MPA) and Graph Theory (GT) applications. In this paper, the researcher explains the results of conducted experiments and identified bug information with MTAF. Several Multi Precision Arithmetic and Graph Theory related hidden bugs are discussed in this paper to show the performance of MTAF.
Using Data Mining to Identify COSMIC Function Point Measurement Competence IJECEIAES
Cosmic Function Point (CFP) measurement errors leads budget, schedule and quality problems in software projects. Therefore, it’s important to identify and plan requirements engineers’ CFP training need quickly and correctly. The purpose of this paper is to identify software requirements engineers’ COSMIC Function Point measurement competence development need by using machine learning algorithms and requirements artifacts created by engineers. Used artifacts have been provided by a large service and technology company ecosystem in Telco. First, feature set has been extracted from the requirements model at hand. To do the data preparation for educational data mining, requirements and COSMIC Function Point (CFP) audit documents have been converted into CFP data set based on the designed feature set. This data set has been used to train and test the machine learning models by designing two different experiment settings to reach statistically significant results. Ten different machine learning algorithms have been used. Finally, algorithm performances have been compared with a baseline and each other to find the best performing models on this data set. In conclusion, REPTree, OneR, and Support Vector Machines (SVM) with Sequential Minimal Optimization (SMO) algorithms achieved top performance in forecasting requirements engineers’ CFP training need.
Quality aware approach for engineering self-adaptive software systemscsandit
Self-adaptivity allows software systems to autonomously adjust their behavior during run-time to reduce
the cost complexities caused by manual maintenance. In this paper, an approach for building an external
adaptation engine for self-adaptive software systems is proposed. In order to improve the quality of selfadaptive
software systems, this research addresses two challenges in self-adaptive software systems. The
first challenge is managing the complexity of the adaptation space efficiently and the second is handling the
run-time uncertainty that hinders the adaptation process. This research utilizes Case-based Reasoning as
an adaptation engine along with utility functions for realizing the managed system’s requirements and
handling uncertainty.
One of the core quality assurance feature which combines fault prevention and fault detection, is often known as testability approach also. There are many assessment techniques and quantification method evolved for software testability prediction which actually identifies testability weakness or factors to further help reduce test effort. This paper examines all those measurement techniques that are being proposed for software testability assessment at various phases of object oriented software development life cycle. The aim is to find the best metrics suit for software quality improvisation through software testability support. The ultimate objective is to establish the ground work for finding ways reduce the testing effort by improvising software testability and its assessment using well planned guidelines for object-oriented software development with the help of suitable metrics.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Tool Support for Testing as Chapter 6 of ISTQB Foundation 2018. Topics covered are Tool Benefits, Test Tool Classification, Benefits of Test Automation, Risk of Test Automation, Selecting a tool for Organization, Pilot Project, Success factor for using a tool
Real time implementation of the software system requires being more versatile. In the maintenance phase, the modified system under regression testing must assure that the existing system remains defect free. Test case prioritization technique of regression testing includes code as well as model based methods of prioritizing the test cases. System model based test case prioritization can detect the severe faults early as compare to the code based test case prioritization. Model based prioritization techniques based on requirements in a cost effective manner has not been taken for study so far. Model based testing used to test the functionality of the software system based on requirement. An effective model based approach is defined for prioritizing test cases and to generate the effective test sequence. The test cases are rescheduled based on requirement analysis and user view analysis. With the use of weighted approach the overall cost is estimated to test the functionality of the model elements. Here, the genetic approach has been applied to generate efficient test path. The regression cost in terms of effort has been reduced under model based prioritization approach.
Projek Sarjana Muda (PSM) / Final Year Project (FYP)
Tajuk : REQUIREMENT TRACEABILITY OF ECAMPUS SYSTEM OF INTEGRATED UNIVERSITY MANAGEMENT SYSTEM FORUNIVERSITI ISLAM MALAYSIA
EXTRACTING THE MINIMIZED TEST SUITE FOR REVISED SIMULINK/STATEFLOW MODELijaia
Test case generation techniques are successfully employed to generate test cases from a formal model. A problem is that as the model evolves, test suites tend to grow in size, making it too costly to execute entire test suites. This paper aims to propose a practical approach to reduce the size of test suites for modified Simulink/Stateflow (SL/SF) model, which is popularly used for modeling software behavior in many industries like automobile manufacturers. The model for describing a system is frequently modified until it is fixed. The proposed technique is capable of extracting the minimized sized test suite in terms of test coverage, by taking into account both the modified and the affected portion of revised SL/SF model. Two real models for the ECUs deployed in a commercial car are used for an empirical study.
Configuration Navigation Analysis Model for Regression Test Case Prioritizationijsrd.com
Regression testing has been receiving increasing attention nowadays. Numerous regression testing strategies have been proposed. Most of them take into account various metrics like cost as well as the ability to find faults quickly thereby saving overall testing time. In this paper, a new model called the Configuration Navigation Analysis Model is proposed which tries to consider all stakeholders and various testing aspects while prioritizing regression test cases.
EXPERIMENTAL EVALUATION AND RESULT DISCUSSION OF METAMORPHIC TESTING AUTOMATI...IAEME Publication
Metamorphic Testing is an attribute relations based testing, used to mitigate the test oracle problem in testing complex non-testable programs. MTAF stands for Metamorphic Testing Automation Framework, introduced to eliminate the human intervention in creating test cases, mapping the relations, executing the statements and identifying the errors from input programs. MTAF is especially designed to address the test oracle problem of two most popular non-testable program domains are Multi Precision Arithmetic (MPA) and Graph Theory (GT) applications. In this paper, the researcher explains the results of conducted experiments and identified bug information with MTAF. Several Multi Precision Arithmetic and Graph Theory related hidden bugs are discussed in this paper to show the performance of MTAF.
Using Data Mining to Identify COSMIC Function Point Measurement Competence IJECEIAES
Cosmic Function Point (CFP) measurement errors leads budget, schedule and quality problems in software projects. Therefore, it’s important to identify and plan requirements engineers’ CFP training need quickly and correctly. The purpose of this paper is to identify software requirements engineers’ COSMIC Function Point measurement competence development need by using machine learning algorithms and requirements artifacts created by engineers. Used artifacts have been provided by a large service and technology company ecosystem in Telco. First, feature set has been extracted from the requirements model at hand. To do the data preparation for educational data mining, requirements and COSMIC Function Point (CFP) audit documents have been converted into CFP data set based on the designed feature set. This data set has been used to train and test the machine learning models by designing two different experiment settings to reach statistically significant results. Ten different machine learning algorithms have been used. Finally, algorithm performances have been compared with a baseline and each other to find the best performing models on this data set. In conclusion, REPTree, OneR, and Support Vector Machines (SVM) with Sequential Minimal Optimization (SMO) algorithms achieved top performance in forecasting requirements engineers’ CFP training need.
Quality aware approach for engineering self-adaptive software systemscsandit
Self-adaptivity allows software systems to autonomously adjust their behavior during run-time to reduce
the cost complexities caused by manual maintenance. In this paper, an approach for building an external
adaptation engine for self-adaptive software systems is proposed. In order to improve the quality of selfadaptive
software systems, this research addresses two challenges in self-adaptive software systems. The
first challenge is managing the complexity of the adaptation space efficiently and the second is handling the
run-time uncertainty that hinders the adaptation process. This research utilizes Case-based Reasoning as
an adaptation engine along with utility functions for realizing the managed system’s requirements and
handling uncertainty.
One of the core quality assurance feature which combines fault prevention and fault detection, is often known as testability approach also. There are many assessment techniques and quantification method evolved for software testability prediction which actually identifies testability weakness or factors to further help reduce test effort. This paper examines all those measurement techniques that are being proposed for software testability assessment at various phases of object oriented software development life cycle. The aim is to find the best metrics suit for software quality improvisation through software testability support. The ultimate objective is to establish the ground work for finding ways reduce the testing effort by improvising software testability and its assessment using well planned guidelines for object-oriented software development with the help of suitable metrics.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Online course registration system development software engineering project pr...MD.HABIBUR Rahman
Autometed Online Course Registration System is a software development project final presentation. here , I applyed . and software development waterfall feedback model. Development Software Engineering Project Presentation
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
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.
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
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.
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. CONTENT
1. INTRODUCTION
2. PROBLEM STATEMENT
3. OBJECTIVES
4. PROCESS MODEL
5. DATA MODEL
6. SOLUTION COMPLEXITY
7. PROOF OF CONCEPT
8. REFERENCES
3. 1. INTRODUCTION
Before hiring an applicant for a job position, a company goes through a step-
by-step hiring process. This process has three key phases
1. Planning
2. recruitment
3. employee selection
4. 1. INTRODUCTION
Hiring process usually begin by employer putting up the advertisement or announcement for the
vacancies available in their departments or companies.
Employer put up
vacancies / job
openings
Applicants send
in their
application
letter/resume
and cover letter
Employers screen
the application
form and resume
Employers call
successful
candidates for
interviews
5. INTRODUCTION TO THE PROPOSED SYSTEM
Candidate Qualification Filtering System propose a way for employer to get a
shortlist of maybe 50-100 employees according to their preference to go to
the next stage of the hiring process . The main users of this system will be
employer and applicants. This system will consists of few components of tests
such as personality test, aptitude test and basic skill test. The applicants are
required to sign up to the system and fill in their personal details and take up
the tests in a specific timeframe.
6. How the System Works?
The system will calculate the scores of each components of tests and totals
them up to get an overall score in a form of percentage using weighted-sum
method. Then using data structure method which is sorting, the system will
rank a number of successful applicants from the highest to the lowest
percentage of score. Then, the employer will enter their preferred range of
number to get a shortlist of successful applicants. Applicants that is in the
shortlisted rank will be informed through the system.
7. 2. Problem Statement
Resumes are always self-scripted by the applicants itself, thus applicants will
only pick the best quality they can find and avoid to show their weaknesses
on the resume.
Resumes may contain events or details that are not the truth or half-truths.
The process of screening resume just to pick candidates for interview is too
time-consuming for employers.
8. 3. Objectives
To design the Applicant Qualification Filtering System.
To use weighted-sum method as an algorithm to calculate test scores.
To implement the Applicant Qualification Filtering System to calculate test
scores and rank applicants according to the scores.
To allow employers to view a shortlisted candidates to call for interview.
22. METHODOLOGY
Methodology is a documented collection of policies,processes and procedures used by a
development team to practice system development life cycle.In this case,Spiral model
has been chosen as a methodology to develop this Applicants Qualification Filtering
System.
23. Spiral model combines the idea of iterative development with the sequential linear
development which is waterfall method.Spiral model however emphasize a lot on risk
analysis.It allows incremental refinement through each iteration around the spiral
model.
Each loop has four sections :
a) A requirement to determine the objectives, alternatives and constraints.
b) Risk analysis and evaluation of alternatives.
c) Designing
d) Implementing and testing before go to next phase
24.
25. The development of this system is separated to 4 modules;
1. Login Module
2. Evaluation Module
3. Mark Module
4. Report Module
26. i) Phase 1 (Login Module)
Requirement
In requirement phase, firstly the information was gathered by researching the current systems.From
the Internet, a requirement is retrieve by observing how the current job
employment system works.Research is done on several prominent websites such as Jobstreet and
other several websites.
Analysis
The data from the research done during analysis process is analysed to find out what is the
requirement of users that is using the websites.
Design
Before a GUI is created for this phase, a lot of sketch was done, this is because want to make sure
that the GUI will be in user friendly. It is very important the first impression to attract the user.
Implementation
A lot of sketch or mockup is designed to ensure that the design of the site suit the purpose of
the system.Then, a Bootstrap template is used as it is more time saving and the design is interesting
and user-friendly.A modification will be done on the interface to match the mockup that has been
pre-designed so that it will works according to the plan.
27. ii) Phase 2 (Evaluation Module)
Requirement
Analysis
In requirement phase, firstly the information was gathered by researching the current systems.From the Internet, a
requirement is retrieve by observing how the current job employment system evaluate their job candidates.Research is done
on several prominent websites such as Jobstreet and other several websites.
Design
The design for this module is important because it is the main component of the system.This module also involve calculation
process.
Implementation
For this implementation process, there is weighted sum method will be implementing in PHP language. The calculation
weighted sum method (WSM) as below :
Determine weight of each option.
Obtain score of option i using each criteria j for all i and j.
Compute the sum of weighted score for each option.
Si = ∑j wj Sij
S – Score
w – Weighted
i – Value of weighted
j – Value of component
28. iii) Phase 3 (Mark Module)
Requirement
In requirement phase, firstly the information was gathered by researching the algorithm
that is going to be used which is weighted-sum. A research is also done on how this
algorithm is implemented on a real life system as reference.
Analysis
Analyzing the requirement to get the overview of module to be done. From the analyzed
data, show that the mark will be display automatically after the calculation done.
Design
In designing this module, a lot of thing be study, such as the process flow to make a
calculation to get the total of mark.
Implementation
This process are involving the formula to get the total marks from the components of
test.Then,the candidates will be ranked and ranked from highest to lowest.A shortlisted
candidates will be the successful candidates.
29. v) Phase 4 (Report Module)
Requirement
In requirement phase, firstly the information was gathered by researching what report is required by
employer for their record.
Analysis
For this module, there involves of some analysis such as about how to determine what is the good graph
or chart that are need to be represent as report to employer. In order to get the best graph or the best
chart, there are some constraints in understanding the Google Application Programming Interface (API).
Design
A lot of study need to be done to find out the best method to represent a set of data as a report to
employer so that it can help employer to improve their performance in the future or only as a record.
Implementation
For this process, there still need a little of calculations to be used in order to produce a good report to
the user of the system.
31. Implementation of weighted-sum
method in the system
Weighted-sum method is decided as the best known and simplest MCDM
method to evaluate a number of alternatives and criteria. This method is the
best to evaluate the tests conducted on the system.
The reason of why this method is selected is because the final result of the
tests will be in percentage and also the incorporation of this method in the
coding stage of the system is within capabilities.
32. Weighted-sum method
Valuable decision making tool to evaluate alternatives(test scores) based on specific evaluation
criteria.
By evaluating alternatives based on their performance on the test in respect to individual
criteria, a value for the alternative can be identified.
The values for each alternative can then be compared to create a rank of order of the
performance related to the criteria as a whole.
33. Example of calculation of scores
COMPONENT
S
A1(0.02) A2(0.15) A3(0.40) A4(0.25) Total
C1 25 20 15 30 21.50
C2 10 30 20 30 22.00
C3 30 10 30 20 24.50
OPTIONS
Calculation:
C1=25(0.02)+20(0.15)+15(0.40)+30(0.25)=21.50
C2=10(0.02)+30(0.15)+20(0.14)+ 30(0.25)=22.00
C3=30(0.02)+10(0.15)+30(0.40)+20(0.25)=24.50
Total Marks=
34. Method To Rank The Successful Applicants
Using sorting method ,the system will rank a number of successful applicants from the
highest to the lowest percentage of score.