Rather than starting with everything but the kitchen sink, start with the bare minimum and add dependencies on an as needed basis. Preferred technologies. Data Engineer and Hadoop administrator. Helped create Hadoop clusters for Data Science. Trained staff in using Git and GitLab. Documentation partly with OpenAPI. Developed a system to spread Java properties to all Maven submodules. Introduced the idea of project website for customer. Merged individual repositories to one repo to make development quicker.
Introduced SonarQube to project. Configured Gitlab-CI. Introduced transactions and sequences to database facing code how business objects are stored into MySQL database. Started testing with temporary databases. Organized the migration from Subversion to Git version control system , without losing version history. Applied a set of hooks Perl for quality control to Git repository. Same hooks can be installed locally with install script and updated automatically. Automated activation of Jenkins builds when pushes are made to repository. Designed GpsLocator Java 7 to convert gps coordinates from mobile device to named locations.
I programmed the dataset import routines and the Java language "framework" for the lookup. The lookup is implemented as an internal Java service. The project was done by a two-person team. My colleague implemented a visual interface for checking the polygons areas against a background map.
Reconfigured parts of the CMake build system. General and in-house Perl, maintenance and new features in a team. System integrates different media handling systems, e. Baton, Avid Interplay and Flipfactory, file transport and archiving systems, e. PreCut and EasyCut. Customer Avanza Bank: Developer of web form and backend processing for Internet bank.
Customer Kelisec: Developer of server-client system to exchange private keys. Interacted with customer's analysts for technical and business requirement analysis. Lead the development of GELMonitor, integration tool for monitoring constant message flow and system resources. Lead a team of application support people to develop instructions and guidelines for support work and Support Tool application, Unix command line tool which integrates often used application support processes.
Trained customer's key users on message traffic and on using the system PTDi. Supervised one analysis team member's work in China and trained a successor. Business domains: Paper Supply Chain, Logistics. Worked in support customer analysis team: Communication between customer and the development team to find and fix bugs, and keep things running in the live system when a bug can not be fixed on the spot but has to be circumvented. Linux system administration. Software Engineer Koodaripalvelut.
Consultant for software projects in several companies. In-house software development. Participated in the development of Tuntinetti, a payroll computation system and database. Platform: Linux, Oracle. As signal centre team leader I supervised people during field exercises.
When not in field excercises I worked in a team using and developing RF analysis equipment, methods and databases. Trained personnel in using signals equipment. Used WAP. Platform: Solaris. Programmed according to a previously completed specification. Designed and implemented a program to create on the fly a set of teletext pages for MTV3. Worked as a team member consultant for designing a load balancing system for Iltalehti tabloid magazine Internet site. Implemented a parallel copy system for Iltalehti's publishing software in Perl. Designed and implemented Perl modules for debugging, parallel execution and data structure traversing.
As deputy leader of the Signals Centre I supervised the work of three signals specialists. Supervised permanent cable and device installations telephone and network and RF cabling, network nodes and trunk line encryptors and telephone switch Ericsson MD configurations. Trained personnel in the usage of signals equipment. Training: Signals, Electronics. Leadership Training NCO course. Rank: Reservist Staff Sergeant. Designed a new website for the organization.
Worked with organization's general secretary and members of the board to gather requiments, decide layout and design graphics clickable maps. Implemented in HTML 4. Maintained the completed homepages as webmaster. Gathered requirements from users and Icenet customer service. Contributions to Aminet Designer, Developer. A Rubik cube simulator with a terminal UI. A unit testing framework for C. More hooks for Perl package Git::Hooks. Client Libraries to Iron. Architect, developer, testing. Maven Enforcer plugin: Force the character set of all or any file in the project.
Most importantly, sometimes the best solution is achieved by using a combination of features from Object-Oriented, Generic and Functional programming styles, whereas trying to restrict oneself to one particular approach may lead to a suboptimal solution. Generic programming techniques using templates are an important way to develop large, complex software applications and systems.
So are object oriented techniques. Both are important ways to express polymorphism — at compile time and at run time, respectively. Generic programming is a way of developing software that maximizes code reuse in a way that does not sacrifice performance. Generic programming is programming based on parameterization: You can parameterize a type with another such as a vector with its element types and an algorithm with another such as a sort function with a comparison function.
The aim of generic programming is to generalize a useful algorithm or data structure to its most general and useful form. For example, a vector of integers is fine and so is a function that finds the largest value in a vector of integers. However, a better generic find function will be able to find an element in a vector of any type or better still in any sequence of elements described with a pair of iterators:.
Generic programming is in some ways more flexible than object-oriented programming. In particular, it does not depend on hierarchies. For example, there is no hierarchical relationship between an int and a string. This has led generic programming to become dominant in areas where run-time performance is important. Please note that generic programming is not a panacea. There are many parts of a program that need no parameterization and many examples where run-time dispatch OOP is more approriate.
The other interesting feature is that they tend to make your code faster, particularly if you use them more. This creates a pleasant non-tradeoff: when you use the components to do the nasty work for you, your code gets smaller and simpler, you have less chance of introducing errors, and your code will often run faster. Most developers are not cut out to create these generic components, but most can use them. Fortunately generic components are, um, generic, so your organization does not often need to create a lot of them.
There are many off-the-shelf libraries of generic components. STL is one such library. Boost has a bunch more. Naturally, the main strength of multiparadigm programming is in programs where more than one paradigm programming style is used, so that it would be hard to get the same effect by composing a system out of parts written in languages supporting different paradigms. The most compelling cases for multiparadigm programming are found where techniques from different paradigms are used in close collaboration to write code that is more elegant and more maintainable than would be possible within a single paradigm.
A simple example is the traversal of a statically typed container of objects of a polymorphic type:. Here, Shape will be an abstract base class defining the interface to a hierarchy of geometric shapes.
Imperfect C++ practical solutions for real-life programming. Matthew Wilson
This example easily generalizes to any standard library container:. This question generates much much more heat than light. Please read the following before posting some variant of this question. These business considerations generally play a much greater role than compile time performance, runtime performance, static vs. Those who ignore the dominant! The most widely circulated comparisons tend to be those written by proponents of some language, Z, to prove that Z is better that other languages.
One problem is that there are always grains of truth in such comparisons. After all, no language is better than every other in all possible ways. When looking at a language comparison consider who wrote it, consider carefully if the descriptions are factual and fair, and also if the comparison criteria are themselves fair for all languages considered.
This is not easy. This I have decided against doing. Thereby, I have reaffirmed a long-standing and strongly held view: Language comparisons are rarely meaningful and even less often fair.
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A good comparison of major programming languages requires more effort than most people are willing to spend, experience in a wide range of application areas, a rigid maintenance of a detached and impartial point of view, and a sense of fairness. I also worry about a phenomenon I have repeatedly observed in honest attempts at language comparisons.
The authors try hard to be impartial, but are hopelessly biased by focusing on a single application, a single style of programming, or a single culture among programmers. Worse, when one language is significantly better known than others, a subtle shift in perspective occurs: Flaws in the well-known language are deemed minor and simple workarounds are presented, whereas similar flaws in other languages are deemed fundamental.
Often, the workarounds commonly used in the less-well-known languages are simply unknown to the people doing the comparison or deemed unsatisfactory because they would be unworkable in the more familiar language. Similarly, information about the well-known language tends to be completely up-to-date, whereas for the less-known language, the authors rely on several-year-old information.
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For languages that are worth comparing, a comparison of language X as defined three years ago vs. They too are huge compared to say, Pascal as Dr. Wirth originally defined it — for good reasons. The programming world is far more complex today than it was 30 years ago, and modern programming languages reflect that. Finally, the days where a novice programmer can know all of a language are gone, at least for the languages in widespread industrial use. What you must do - in any language — is to pick a subset, get working writing code, and gradually learn more of the language, its libraries, and its tools.
Lots and lots of companies and government sites. The large number of developers and therefore the large amount of available support infrastructure including vendors, tools, training, etc. The current growth rate is steady and positive. Maybe, but then again, that is the timescale we have to consider to become better designers and programmers. Compared to the time required to learn to play the piano well or to become fluent in a foreign natural language, learning a new and different programming language and programming style is easy. To become one of these experts who can mentor others takes around 3 years.
Some people never make it. That depends on how you use it. Most people underestimate abstract classes and templates. Conversely, most people seriously overuse casts and macros. One way of thinking of abstract classes and templates is as interfaces that allow a more clean and logical presentation of services than is easy to provide through functions or single-rooted class hierarchies.
See other sections of this FAQ for some specific examples and ideas. Some people seem to believe that a programming language can or at least should solve most of their problems with system building. They are condemned to search forever for the perfect programming language and become repeatedly disappointed.
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Yes and no! The other is generic-programming-style static polymorphism, which you get by using templates, and you should often use for things that are known at compile time. Operator overloading and non- virtual member functions are great, but they are, after all, just syntactic sugar for the more typical C notion of passing a pointer to a struct to a function. All you have left is object-based programming, similar to the original Ada language the updated Ada language, by the way, supports true OO rather than just object-based programming.
They can improve reuse by letting old code call new code provided at run time virtual functions or compile time templates. Before OO and generic programming came along, reuse was accomplished by having new code call old code. For example, a programmer might write some code that called some reusable code such as printf. With OO and generic programming, reuse can also be accomplished by having old code call new code. For example, a programmer might write some code that is called by a framework that was written by their great, great grandfather.
Even if all you have left is the object file and the source code that great-great-grandpa wrote was lost 25 years ago, that ancient object file will call the new extension without anything falling apart. That is extensibility, and that is OO and generic programming for powerful reusable abstraction. At the time, Stroustrup considered C the best systems programming language available. Contrary to repeated rumors, Stroustrup was never told that he had to use C; nor was he ever told not to use C.
Stroustrup wanted to write efficient systems programs in the styles encouraged by Simula To do that, he added facilities for better type checking, data abstraction, and object-oriented programming to C. The more general aim was to design a language in which developers could write programs that were both efficient and elegant.
Many languages force you to choose between those two alternatives. It was first used in December of when it was edited into the final copies of [Stroustrup,] and [Stroustrup,c]. The language is not called D, because it is an extension of C, and it does not attempt to remedy problems by removing features. Naturally, it is the name of the language Dennis Ritchie designed. Because machines differ and because C left many things undefined. Note that the meaning of those terms differ from their definition of the ISO C standard and from some common usage.
This is a correct, if unsatisfactory, answer. Sizes of integers and the rounding behavior of floating-point computations fall into that category. The primitive operations on pointers map directly onto machine instructions. In particular, no range checking is done. Doing range checking would impose a cost in terms of run time and code size. C was designed to outcompete assembly code for operating systems tasks, so that was a necessary decision.
If you want range checking, use a suitable checked class vector , smart pointer, string , etc. A good compiler could catch the range error for a at compile time, catching the one for p is far more difficult, and in general it is impossible to catch every range error at compile time. Other examples of undefined behavior stems from the compilation model. A compiler cannot detect an inconsistent definition of an object or a function in separately-compiled translation units.
For example:. Compiling file1. In many cases, it can be quite difficult to catch inconsistencies between separately compiled translation units. Consistent use of header files helps minimize such problems and there are some signs that linkers are improving. Finally, we have the apparently unnecessary and rather annoying undefined behavior of individual expressions. The value of j is unspecified to allow compilers to produce optimal code. Similarly, the order of evaluation of arguments is unspecified.
Successful software is long-lived; life-spans of decades are not uncommon.
Imperfect C++: Practical Solutions for Real-Life Programming
Often, a good piece of software outlives the companies that supplied the basic technologies used to build it. The set of desirable platforms change as the user population changes. Obviously, complete platform independence is incompatible with the ability to use all platform specific facilities.
The ISO standard was finalized and adopted by unanimous vote in November , with minor updates in and now significant and valuable updates in Another set of updates is expected to be published in The U. The committee consists of a large number of people about out of whom about turn up at the week-long meetings two or three times a year.