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Interesting articles supporting Python from hackernoon blog

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keywords = {Computer software, Computers, Open source software, Programming languages, Research validity, Scientists, Software development, Software tools},
pages = {1--7},
}
@inproceedings{nanz_comparative_2015,
title = {A {Comparative} {Study} of {Programming} {Languages} in {Rosetta} {Code}},
volume = {1},
doi = {10.1109/ICSE.2015.90},
abstract = {Sometimes debates on programming languages are more religious than scientific. Questions about which language is more succinct or efficient, or makes developers more productive are discussed with fervor, and their answers are too often based on anecdotes and unsubstantiated beliefs. In this study, we use the largely untapped research potential of Rosetta Code, a code repository of solutions to common programming tasks in various languages, which offers a large data set for analysis. Our study is based on 7'087 solution programs corresponding to 745 tasks in 8 widely used languages representing the major programming paradigms (procedural: C and Go, object-oriented: C\# and Java, functional: F\# and Haskell, scripting: Python and Ruby). Our statistical analysis reveals, most notably, that: functional and scripting languages are more concise than procedural and object-oriented languages, C is hard to beat when it comes to raw speed on large inputs, but performance differences over inputs of moderate size are less pronounced and allow even interpreted languages to be competitive, compiled strongly-typed languages, where more defects can be caught at compile time, are less prone to runtime failures than interpreted or weakly-typed languages. We discuss implications of these results for developers, language designers, and educators.},
booktitle = {2015 {IEEE}/{ACM} 37th {IEEE} {International} {Conference} on {Software} {Engineering}},
author = {Nanz, S. and Furia, C. A.},
month = may,
year = {2015},
keywords = {Python, authoring languages, Java, Runtime, C\#, code repository, F\#, functional language, functional languages, Go, Haskell, Indexes, language interpretation, object-oriented language, object-oriented programming, procedural language, program compilers, program interpreters, Programming, programming languages, Rosetta Code, Ruby, scripting language, Standards, statistical analysis, Statistical analysis, strongly-typed language compilation},
pages = {778--788},
}
@article{ousterhout_scripting_1998,
title = {Scripting: higher level programming for the 21st {Century}},
volume = {31},
issn = {0018-9162},
shorttitle = {Scripting},
doi = {10.1109/2.660187},
abstract = {A fundamental change is occurring in the way people write computer programs, away from system programming languages such as C or C++ to scripting languages such as Perl or Tcl. Although many people are participating in the change, few realize that the change is occurring and even fewer know why it is happening. This article explains why scripting languages will handle many of the programming tasks in the next century better than system programming languages. System programming languages were designed for building data structures and algorithms from scratch, starting from the most primitive computer elements. Scripting languages are designed for gluing. They assume the existence of a set of powerful components and are intended primarily for connecting components},
number = {3},
journal = {Computer},
author = {Ousterhout, J. K.},
month = mar,
year = {1998},
keywords = {21st Century, Algorithm design and analysis, Application software, Assembly systems, authoring languages, Automatic generation control, Buildings, C, C++, Computer aided instruction, Computer languages, data structures, higher level programming, Perl, Program processors, programming, Programming profession, Registers, scripting, scripting languages, software components, system programming languages, Tcl},
pages = {23--30},
}
@article{prechelt_empirical_2000,
title = {An empirical comparison of seven programming languages},
volume = {33},
issn = {0018-9162},
doi = {10.1109/2.876288},
abstract = {Often heated, debates regarding different programming languages' effectiveness remain inconclusive because of scarce data and a lack of direct comparisons. The author addresses that challenge, comparatively analyzing 80 implementations of the phone-code program in seven different languages (C, C++, Java, Perl, Python, Rexx and Tcl). Further, for each language, the author analyzes several separate implementations by different programmers. The comparison investigates several aspects of each language, including program length, programming effort, runtime efficiency, memory consumption, and reliability. The author uses comparisons to present insight into program language performance},
number = {10},
journal = {Computer},
author = {Prechelt, L.},
month = oct,
year = {2000},
keywords = {Python, authoring languages, C++, Computer languages, Perl, Program processors, programming, Programming profession, Tcl, C language, C++ language, Java, memory consumption, phone-code program, Production, program language performance, program length, programming language comparison, Read-write memory, Rexx, Runtime, runtime efficiency, software reliability, Statistics, Sun, Workstations},
pages = {23--29},
}
@misc{language_productivity_infographic,
title = {language\_productivity.pdf},
url = {http://www.connellybarnes.com/documents/language_productivity.pdf},
urldate = {2018-02-08},
}
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