JUnit, TDD, CPTC, Web Penetration Training Classes in Pittsburg, California
Learn JUnit, TDD, CPTC, Web Penetration in Pittsburg, California and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current JUnit, TDD, CPTC, Web Penetration related training offerings in Pittsburg, California: JUnit, TDD, CPTC, Web Penetration Training
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Blog Entries publications that: entertain, make you think, offer insight
When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.
In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption. After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.
After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.
There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.
Microsoft has now come up with a surface tablet to compete with the Apple iPad. The Surface is the known as the ‘iPad killer’ and ‘Microsoft iPad’. Microsoft has stuck to production of software till date but this is one of its latest hardware devices that is expected to take over the Apple iPad. This is a new challenge posed by Microsoft to Apple.
The Microsoft Surface saw its official release on 19th June in the city of Los Angeles. It has made a great first impression and seems to be beginning a new start in the competition between the best tablets in the international market. It has 10.6’’ screen and a magnetic cover that can be used as a keyboard and also as a kickstand in order to place the device upright on tables. There has been a paradigm shift in Microsoft’s policy when it decided to do away with the tile-based Metro theme for its Desktop that is almost a trademark with it.
There are many features that make the Surface more like a laptop than like a tablet- the most prominent one being the built- in keyboard that will be useful for business customers. As Microsoft Surface employs Windows 8 as an operating system, which is also used in its computers and laptops, it will be a lot easier for customers to switch among their devices.
The tablet was announced by Microsoft’s CEO, Steve Ballmer, in Los Angeles at a special press conference. It was hailed to be the first of an entirely new family of a number of devices being created and developed by the company. The Surface has a thickness of 9.3mm and weighs 1.5 pounds. It has a kickstand and keyboard for its cover. It is 0.1 mm thinner than the iPad 3, which is the latest iPad from Apple.
Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.
Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.
Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?
One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.
The original article was posted by Michael Veksler on Quora
A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.
The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.
Readability is a tricky thing, and involves several aspects:
- Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
- Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
- Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
- Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
- Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
- Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
- As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
- The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.
Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.
Don’t blindly use C++ standard library without understanding what it does - learn it. You look at
documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::vector::push_back()
, and with std::map
. Knowing the difference between these two maps, you’d know when to use each one of them.std::unordered_map
Never call
or new
directly, use delete
and [cost c++]std::make_shared[/code] instead. Try to implement std::make_unique
yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.usique_ptr, shared_ptr, weak_ptr
Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.
Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.
Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.
Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.
These are the most important things, which will make you a better programmer. The other things will follow.
Tech Life in California
Company Name | City | Industry | Secondary Industry |
---|---|---|---|
Mattel, Inc. | El Segundo | Retail | Sporting Goods, Hobby, Book, and Music Stores |
Spectrum Group International, Inc. | Irvine | Retail | Retail Other |
Chevron Corp | San Ramon | Energy and Utilities | Gasoline and Oil Refineries |
Jacobs Engineering Group, Inc. | Pasadena | Real Estate and Construction | Construction and Remodeling |
eBay Inc. | San Jose | Software and Internet | E-commerce and Internet Businesses |
Broadcom Corporation | Irvine | Computers and Electronics | Semiconductor and Microchip Manufacturing |
Franklin Templeton Investments | San Mateo | Financial Services | Investment Banking and Venture Capital |
Pacific Life Insurance Company | Newport Beach | Financial Services | Insurance and Risk Management |
Tutor Perini Corporation | Sylmar | Real Estate and Construction | Construction and Remodeling |
SYNNEX Corporation | Fremont | Software and Internet | Data Analytics, Management and Storage |
Core-Mark International Inc | South San Francisco | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
Occidental Petroleum Corporation | Los Angeles | Manufacturing | Chemicals and Petrochemicals |
Yahoo!, Inc. | Sunnyvale | Software and Internet | Software and Internet Other |
Edison International | Rosemead | Energy and Utilities | Gas and Electric Utilities |
Ingram Micro, Inc. | Santa Ana | Computers and Electronics | Consumer Electronics, Parts and Repair |
Safeway, Inc. | Pleasanton | Retail | Grocery and Specialty Food Stores |
Gilead Sciences, Inc. | San Mateo | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
AECOM Technology Corporation | Los Angeles | Real Estate and Construction | Architecture,Engineering and Design |
Reliance Steel and Aluminum | Los Angeles | Manufacturing | Metals Manufacturing |
Live Nation, Inc. | Beverly Hills | Media and Entertainment | Performing Arts |
Advanced Micro Devices, Inc. | Sunnyvale | Computers and Electronics | Semiconductor and Microchip Manufacturing |
Pacific Gas and Electric Corp | San Francisco | Energy and Utilities | Gas and Electric Utilities |
Electronic Arts Inc. | Redwood City | Software and Internet | Games and Gaming |
Oracle Corporation | Redwood City | Software and Internet | Software and Internet Other |
Symantec Corporation | Mountain View | Software and Internet | Data Analytics, Management and Storage |
Dole Food Company, Inc. | Thousand Oaks | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
CBRE Group, Inc. | Los Angeles | Real Estate and Construction | Real Estate Investment and Development |
First American Financial Corporation | Santa Ana | Financial Services | Financial Services Other |
The Gap, Inc. | San Francisco | Retail | Clothing and Shoes Stores |
Ross Stores, Inc. | Pleasanton | Retail | Clothing and Shoes Stores |
Qualcomm Incorporated | San Diego | Telecommunications | Wireless and Mobile |
Charles Schwab Corporation | San Francisco | Financial Services | Securities Agents and Brokers |
Sempra Energy | San Diego | Energy and Utilities | Gas and Electric Utilities |
Western Digital Corporation | Irvine | Computers and Electronics | Consumer Electronics, Parts and Repair |
Health Net, Inc. | Woodland Hills | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
Allergan, Inc. | Irvine | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
The Walt Disney Company | Burbank | Media and Entertainment | Motion Picture and Recording Producers |
Hewlett-Packard Company | Palo Alto | Computers and Electronics | Consumer Electronics, Parts and Repair |
URS Corporation | San Francisco | Real Estate and Construction | Architecture,Engineering and Design |
Cisco Systems, Inc. | San Jose | Computers and Electronics | Networking Equipment and Systems |
Wells Fargo and Company | San Francisco | Financial Services | Banks |
Intel Corporation | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
Applied Materials, Inc. | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
Sanmina Corporation | San Jose | Computers and Electronics | Semiconductor and Microchip Manufacturing |
Agilent Technologies, Inc. | Santa Clara | Telecommunications | Telecommunications Equipment and Accessories |
Avery Dennison Corporation | Pasadena | Manufacturing | Paper and Paper Products |
The Clorox Company | Oakland | Manufacturing | Chemicals and Petrochemicals |
Apple Inc. | Cupertino | Computers and Electronics | Consumer Electronics, Parts and Repair |
Amgen Inc | Thousand Oaks | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
McKesson Corporation | San Francisco | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
DIRECTV | El Segundo | Telecommunications | Cable Television Providers |
Visa, Inc. | San Mateo | Financial Services | Credit Cards and Related Services |
Google, Inc. | Mountain View | Software and Internet | E-commerce and Internet Businesses |
training details locations, tags and why hsg
The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:
- Learn from the experts.
- We have provided software development and other IT related training to many major corporations in California since 2002.
- Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
- Discover tips and tricks about JUnit, TDD, CPTC, Web Penetration programming
- Get your questions answered by easy to follow, organized JUnit, TDD, CPTC, Web Penetration experts
- Get up to speed with vital JUnit, TDD, CPTC, Web Penetration programming tools
- Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
- Prepare to hit the ground running for a new job or a new position
- See the big picture and have the instructor fill in the gaps
- We teach with sophisticated learning tools and provide excellent supporting course material
- Books and course material are provided in advance
- Get a book of your choice from the HSG Store as a gift from us when you register for a class
- Gain a lot of practical skills in a short amount of time
- We teach what we know…software
- We care…