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What is SDLC?
SDLC is a process followed for a software project, within a software organization. It consists of a detailed plan describing how to develop, maintain, replace and alter or enhance specific software. The life cycle defines a methodology for improving the quality of software and the overall development process.
The following figure is a graphical representation of the various stages of a typical SDLC.

A typical Software Development Life Cycle consists of the following stages −
Stage 1: Planning and Requirement Analysis
Requirement analysis is the most important and fundamental stage in SDLC. It is performed by the senior members of the team with inputs from the customer, the sales department, market surveys and domain experts in the industry. This information is then used to plan the basic project approach and to conduct product feasibility study in the economical, operational and technical areas.
Planning for the quality assurance requirements and identification of the risks associated with the project is also done in the planning stage. The outcome of the technical feasibility study is to define the various technical approaches that can be followed to implement the project successfully with minimum risks.
Stage 2: Defining Requirements
Once the requirement analysis is done the next step is to clearly define and document the product requirements and get them approved from the customer or the market analysts. This is done through an SRS (Software Requirement Specification) document which consists of all the product requirements to be designed and developed during the project life cycle.
Stage 3: Designing the Product Architecture
SRS is the reference for product architects to come out with the best architecture for the product to be developed. Based on the requirements specified in SRS, usually more than one design approach for the product architecture is proposed and documented in a DDS - Design Document Specification.
This DDS is reviewed by all the important stakeholders and based on various parameters as risk assessment, product robustness, design modularity, budget and time constraints, the best design approach is selected for the product.
A design approach clearly defines all the architectural modules of the product along with its communication and data flow representation with the external and third party modules (if any). The internal design of all the modules of the proposed architecture should be clearly defined with the minutest of the details in DDS.
Stage 4: Building or Developing the Product
In this stage of SDLC the actual development starts and the product is built. The programming code is generated as per DDS during this stage. If the design is performed in a detailed and organized manner, code generation can be accomplished without much hassle.
Developers must follow the coding guidelines defined by their organization and programming tools like compilers, interpreters, debuggers, etc. are used to generate the code. Different high level programming languages such as C, C++, Pascal, Java and PHP are used for coding. The programming language is chosen with respect to the type of software being developed.
Stage 5: Testing the Product
This stage is usually a subset of all the stages as in the modern SDLC models, the testing activities are mostly involved in all the stages of SDLC. However, this stage refers to the testing only stage of the product where product defects are reported, tracked, fixed and retested, until the product reaches the quality standards defined in the SRS.
Stage 6: Deployment in the Market and Maintenance
Once the product is tested and ready to be deployed it is released formally in the appropriate market. Sometimes product deployment happens in stages as per the business strategy of that organization. The product may first be released in a limited segment and tested in the real business environment (UAT- User acceptance testing).
Then based on the feedback, the product may be released as it is or with suggested enhancements in the targeting market segment. After the product is released in the market, its maintenance is done for the existing customer base.Video link:Embedded video link:Link: https://projects.invisionapp.com/d/main#/console/20294675/458743820/preview 

Game gerdara 
If you're trying to learn Greek Articles you will find some useful resources including a course about Definite and Indefinite Articles... to help you with your Greek grammar. Try to concentrate on the lesson and notice the pattern that occurs each time the word changes its place. Also don't forget to check the rest of our other lessons listed on Learn Greek. Enjoy the rest of the lesson!

Game gerdara 
If you're trying to learn Greek Articles you will find some useful resources including a course about Definite and Indefinite Articles... to help you with your Greek grammar. Try to concentrate on the lesson and notice the pattern that occurs each time the word changes its place. Also don't forget to check the rest of our other lessons listed on Learn Greek. Enjoy the rest of the lesson!

common myths
for Advanced
AI:A captivating conversation is taking place about the future of artificial intelligence and what it will/should mean for humanity. There are fascinating controversies where the world’s leading experts disagree, such as AI’s future impact on the job market; if/when human-level AI will be developed; whether this will lead to an intelligence explosion; and whether this is something we should welcome or fear. But there are also many examples of boring pseudo-controversies caused by people misunderstanding and talking past each other. 

TIMELINE MYTHS



The first myth regards the timeline: how long will it take until machines greatly supersede human-level intelligence? A common misconception is that we know the answer with great certainty.
One popular myth is that we know we’ll get superhuman AI this century. In fact, history is full of technological over-hyping. Where are those fusion power plants and flying cars we were promised we’d have by now? AI has also been repeatedly over-hyped in the past, even by some of the founders of the field. For example, John McCarthy (who coined the term “artificial intelligence”), Marvin Minsky, Nathaniel Rochester, and Claude Shannon wrote this overly optimistic forecast about what could be accomplished during two months with stone-age computers: “We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College […] An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”

CONTROVERSY MYTHS



Another common misconception is that the only people harboring concerns about AI and advocating AI safety research are Luddites who don’t know much about AI. When Stuart Russell, author of the standard AI textbook, mentioned this during his Puerto Rico talk, the audience laughed loudly. A related misconception is that supporting AI safety research is hugely controversial. In fact, to support a modest investment in AI safety research, people don’t need to be convinced that risks are high, merely non-negligible — just as a modest investment in home insurance is justified by a non-negligible probability of the home burning down.

Forest ecosystems are a critical component of the world’s biodiversity as many forests are more biodiverse than other ecosystems.
Forests cover 31 percent of the global land area. Approximately half the forest area is relatively intact, and more than one-third is primary forest (i.e. naturally regenerated forests of native species, where there are no visible indications of human activities and the ecological processes are not significantly disturbed).
The total forest area is 4.06 billion hectares, or approximately 5 000m2 (or 50 x 100m) per person, but forests are not equally distributed around the globe.
More than half of the world’s forests are found in only five countries (the Russian Federation, Brazil, Canada, the United States of America and China) and two-thirds (66 percent) of forests are found in ten countries.





 

The coronavirus pandemic continues to hit the US economy, with another 5.2 million Amercians seeking unemployment benefits last week.
More than 20 million Americans have applied for benefits in the last month.
Economists believe that the U.S. economy contracted at its sharpest rate since World War II in the first quarter of the year.



Another 5.2 million more Americans sought unemployment benefits last week, lifting total filings for claims over the past month above an astounding 20 million, which would underscore the deepening economic slump caused by the novel coronavirus outbreak.

 

Eating a wide variety of nutritious foods, including fruit, vegetables, nuts, seeds, and lean protein can help support your overall health.

Many foods are both healthy and tasty. By filling your plate with fruits, vegetables, quality protein sources, and other whole foods, you’ll have meals that are colorful, versatile, and good for you.
 
Here are 50 healthy and delicious to include in your diet.YT video URL: YT video embedded video URL:Testing... 

Eating a wide variety of nutritious foods, including fruit, vegetables, nuts, seeds, and lean protein can help support your overall health.

Many foods are both healthy and tasty. By filling your plate with fruits, vegetables, quality protein sources, and other whole foods, you’ll have meals that are colorful, versatile, and good for you.
 
Here are 50 healthy and delicious to include in your diet.



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