This document provides a framework for establishing a software measurement process within an organization. It outlines a four step architecture for designing such a process, including identifying what data to collect, how to collect and report it, how to use the data to make decisions, and how to evolve the process over time. The document also recommends establishing a focal group to lead the measurement effort, designing the initial process, testing it on projects, documenting results, and integrating the process fully within the organization. The goal is to provide managers visibility into the software development lifecycle through measurement in order to improve processes, products, planning, and decision making.
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.
Aliaa delivered a session in the topic of “Test planning” using a new technique of delivering content through games and knowledge sharing instead of instructive technique. The session covered all test planning activities including defining test items, risk assessment techniques, testing strategies, planning for testing resources, testing scheduling, and test deliverables and the final test plan documents.
The session introduced to quality team at ITWorx (June , 2013)
In the software measurement validations, assessing the validation of software metrics in software
engineering is a very difficult task due to lack of theoretical methodology and empirical methodology [41,
44, 45]. During recent years, there have been a number of researchers addressing the issue of validating
software metrics. At present, software metrics are validated theoretically using properties of measures.
Further, software measurement plays an important role in understanding and controlling software
development practices and products. The major requirement in software measurement is that the measures
must represent accurately those attributes they purport to quantify and validation is critical to the success
of software measurement. Normally, validation is a collection of analysis and testing activities across the
full life cycle and complements the efforts of other quality engineering functions and validation is a critical
task in any engineering project. Further, validation objective is to discover defects in a system and assess
whether or not the system is useful and usable in operational situation. In the case of software engineering,
validation is one of the software engineering disciplines that help build quality into software. The major
objective of software validation process is to determine that the software performs its intended functions
correctly and provides information about its quality and reliability. This paper discusses the validation
methodology, techniques and different properties of measures that are used for software metrics validation.
In most cases, theoretical and empirical validations are conducted for software metrics validations in
software engineering [1-50].
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.
Aliaa delivered a session in the topic of “Test planning” using a new technique of delivering content through games and knowledge sharing instead of instructive technique. The session covered all test planning activities including defining test items, risk assessment techniques, testing strategies, planning for testing resources, testing scheduling, and test deliverables and the final test plan documents.
The session introduced to quality team at ITWorx (June , 2013)
In the software measurement validations, assessing the validation of software metrics in software
engineering is a very difficult task due to lack of theoretical methodology and empirical methodology [41,
44, 45]. During recent years, there have been a number of researchers addressing the issue of validating
software metrics. At present, software metrics are validated theoretically using properties of measures.
Further, software measurement plays an important role in understanding and controlling software
development practices and products. The major requirement in software measurement is that the measures
must represent accurately those attributes they purport to quantify and validation is critical to the success
of software measurement. Normally, validation is a collection of analysis and testing activities across the
full life cycle and complements the efforts of other quality engineering functions and validation is a critical
task in any engineering project. Further, validation objective is to discover defects in a system and assess
whether or not the system is useful and usable in operational situation. In the case of software engineering,
validation is one of the software engineering disciplines that help build quality into software. The major
objective of software validation process is to determine that the software performs its intended functions
correctly and provides information about its quality and reliability. This paper discusses the validation
methodology, techniques and different properties of measures that are used for software metrics validation.
In most cases, theoretical and empirical validations are conducted for software metrics validations in
software engineering [1-50].
Testability measurement model for object oriented design (tmmood)ijcsit
Measuring testability early in the development life cycle especially at design phase is a criterion of crucial importance to software designers, developers, quality controllers and practitioners. However, most of the
mechanism available for testability measurement may be used in the later phases of development life cycle.
Early estimation of testability, absolutely at design phase helps designers to improve their designs before
the coding starts. Practitioners regularly advocate that testability should be planned early in design phase.
Testability measurement early in design phase is greatly emphasized in this study; hence, considered significant for the delivery of quality software. As a result, it extensively reduces rework during and after implementation, as well as facilitate for design effective test plans, better project and resource planning in a practical manner, with a focus on the design phase. An effort has been put forth in this paper to recognize the key factors contributing in testability measurement at design phase. Additionally, testability
measurement model is developed to quantify software testability at design phase. Furthermore, the relationship of Testability with these factors has been tested and justified with the help of statistical measures. The developed model has been validated using experimental tryout. Finally, it incorporates the empirical validation of the testability measurement model as the author’s most important contribution.
This is chapter 2 of ISTQB Advance Test Manager certification. This presentation helps aspirants understand and prepare the content of the certification.
One complete test plan for a Web Application . This test plan is for our official IIT website . Tanim Hasan along with shibbir hossain are worked on it
Testability measurement model for object oriented design (tmmood)ijcsit
Measuring testability early in the development life cycle especially at design phase is a criterion of crucial importance to software designers, developers, quality controllers and practitioners. However, most of the
mechanism available for testability measurement may be used in the later phases of development life cycle.
Early estimation of testability, absolutely at design phase helps designers to improve their designs before
the coding starts. Practitioners regularly advocate that testability should be planned early in design phase.
Testability measurement early in design phase is greatly emphasized in this study; hence, considered significant for the delivery of quality software. As a result, it extensively reduces rework during and after implementation, as well as facilitate for design effective test plans, better project and resource planning in a practical manner, with a focus on the design phase. An effort has been put forth in this paper to recognize the key factors contributing in testability measurement at design phase. Additionally, testability
measurement model is developed to quantify software testability at design phase. Furthermore, the relationship of Testability with these factors has been tested and justified with the help of statistical measures. The developed model has been validated using experimental tryout. Finally, it incorporates the empirical validation of the testability measurement model as the author’s most important contribution.
This is chapter 2 of ISTQB Advance Test Manager certification. This presentation helps aspirants understand and prepare the content of the certification.
One complete test plan for a Web Application . This test plan is for our official IIT website . Tanim Hasan along with shibbir hossain are worked on it
IBMがご提供するDBaaSである、オンライン・トランザクション処理アプリケーション用データベースの作成や管理をサポートする「DB2 on Cloud」と、クラウド型のDWHおよびアナリティクス・サービス「dashDB」をご紹介いたします。
IBM OnDemand Webセミナー(http://www.ibm.com/products/specialoffers/jp/ja/ondemand.html#15)のチャートです。
レッドハット 朝活セミナー(1/15, 2/18)の下記セッションでの発表予定資料です。
「Red Hat Enterprise Linux OpenStack Platform環境でのDocker活用テクニック」
https://www.redhat.com/ja/about/events/red-hat-asakatsu-seminar-2016
We need a QA team that works with development teams to help ship features quickly and safely. Traditional testers help to ship safely by doing the testing, but this can have the side-effect of slowing the team down. When bugs are found during the testing stage, they take longer to fix because they requires rework of existing code. The team is then put in a position where they have to decide between shipping quickly or safely. To ship features both quickly and safely we need to find defects as early in the development process as possible to prevent bugs instead of detecting them. In Son's presentation, he will share how to apply agile quality process to achieve this for product-centric teams.
Suggest an intelligent framework for building business process management [ p...ijseajournal
As companies enter into the digital world, information technology is playing a major role in bringing
process improvements to the forefront of business management. In the recent decades, many organizations
have struggled to redesign and improve their business processes to reduce their total cost. The main
contribution of this research study is to propose an intelligent framework that possesses the ability to
employ a database of best practices, business standards, and business activity history in order to permit the
manager to analyze and improve the design of the business processes.
In addition, the other objective of this research is to build a business process or workflow directly from its
process design logic in order to enable rapid process development and deployment. This procedure
requires some technical improvements of the business design, as it is mainly based on building the business
process using Microsoft Office Visio, which communicates the defined business process to the business
process management engine.
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.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
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
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/
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.
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.
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.
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.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
SOFTWARE MEASUREMENT ESTABLISHING A SOFTWARE MEASUREMENT PROCESS
1. SOFTWARE MEASUREMENT – CPSC 547:
ESTABLISHING A SOFTWARE MEASUREMENT PROCESS
Draft: Version 1
Date: June 10, 2009
Authors: Amin Bandeali (amin.bandeali@csu.fullerton.edu)
2.
3. Establishing a to Software Measurement Process 1
This paper provides a very cohesive framework for establishing a measurement process
as part of an organization’s overall software process. This is very essential because software
engineering is a young discipline and so its theories, methods, models, and techniques still need
to be fully developed and assessed. Other engineering branches rely on older, well-consolidated
scientific disciplines. This report starts off with illustrating a four step architecture for designing
a software measurement process.
This report focuses on software measurement process elements which are software
estimation, software design, code, unit test, peer reviews and measurement. Using a process
definition method called ETVX, it develops an operational definition of the measurement
process. A Measurement Process contains of activities which include
• identifying what data to be collected,
• defining how the data are to be collected and reported,
• defining how the data are to be used to make decisions,
• defining how the process is to evolve and improve,
• collecting and analyzing the data,
• making decisions and starting over by continuing and/or adjusting the process [1].
Planning the measurement process involves the first two activities of the architecture and
the author applies the EVTX process definition method to all the rest of activities which help
determine the scope and purpose of the measurement effort, implementing and evolving the
process.
The next section, illustrations of use, describes different ways or methods that an
organization can apply at various levels. A baseline measurement process should communicate
clearly and throughout the different organizational levels and also be consistent. The methods
described in the initial section of the paper could be used to design processes that could include
common management objectives and issues, size, effort and problem measurements, etc. With a
baseline in place, a solid foundation for collecting measures is established. These measurements
could evolve; for example, problem reports could be expanded to track statuses, type, severity
and priority.
Using the above baseline measurements, managers can better manage projects by for
example, use historical data to calibrate software estimation models and then re-plan projects
based on deviations in status, progress, or renegotiations of requirements. The manager can also
describe the products more efficiently by describing how good a product is, or to classify product
characteristics by focusing on the basic measures like maintainability, reliability and problem
densities. A developer can use product descriptions to help them understand the quality of their
work and identify potential strengths and weaknesses in the process while the customers can
describe the products in their requirements specifications to indicate the desired level of quality.
A manager can improve processes of an organization by understanding and focusing on
the basic measures being used for managing their existing processes and products. By
aggregating measurement data across the organization, senior management can identify and
define measures that will help them make decisions with respect to organizational goals and
objectives. With measurement they can better understand the software process and organizational
capabilities, and get involved with the business aspects of software.
As projects and organizations evolve, they hire new staff and those staff needs to be part
of the dynamic changes that the company is going through. They will have to be part of the ever
changing measurement process so that the measurements are up to date and reflect the correct
organizational procedures.
4. Establishing a to Software Measurement Process 2
The last section of this paper completes the measurement process by building upon the
flagship section of this paper – designing the process. This section concentrates on the steps that
necessitate starting a software measurement program. It recommends creating a focal group by
allocating dedicated resources to this end. This group could provide the executives with the
insight to the projects that would otherwise be impossible to have.
The focal group should then meet the objectives set by the management. These objectives
may be the result of process assessment findings and recommendations or some other process
improvement activity. Once objectives are set, a process must be designed to leverage current
measurement capabilities to collect and define the future measurements to achieve
management’s objectives. Once designing is completed, a proof of concept prototype should be
created so that the process could be tested on actual projects focusing on current project
performance with respect to the organizational objectives, benefits and lessons learned from the
existing measurement process, and scope of the effort and resources necessary to initiate and
maintain the measurement process on projects.
Results of the above prototype should be documented and results should be discussed
with management, addressing the benefits and lessons learned and how measurements can
support the organization. Once measurement is documented, it should be implemented across the
organization by integrating measurement process with the software process. The focal group can
then proceed to find opportunities to integrate measurement with other process improvement
activities in the organization.
This paper emphasizes the need for visibility into the software development life cycle and
what better way than measurement? It gives a clear and concise framework for developing,
collecting, analyzing, maintaining and evolving a measurement process for an organization. I
liked the way it went into detail for the first couple of activities and then quickly moved into the
rest of the topics. Personally, I liked the presentation and the material of the paper; however it
could have been presented in a more interesting way. I had to go through the paper multiple
times to understand the depth of the concepts. Also, it seemed to me that the paper was more
tailored for big organizations rather than medium or small software development firms?