English for IT student, Английский язык для инженеров-программистов/экологов, Part 2, Малашенко Е.А., 2014

English for IT student, Английский язык для инженеров-программистов/экологов, Part 2, Малашенко Е.А., 2014.

   Учебное пособие по профессионально-ориентированному общению предназначено для развития лексических навыков в области специальной терминологии, совершенствовании умений и навыков устной речи, чтения и перевода текстов, имеющих профессиональную значимость для инженеров-программистов/экологов.
Данное пособие предназначено для студентов факультета мониторинга окружающей среды, а также для разных категорий учащихся, интересующихся данной тематикой.

English for IT student, Английский язык для инженеров-программистов/экологов, Part 2, Малашенко Е.А., 2014


ALGORITHMS.
When one writes a computer program, one is generally implementing a method of solving a problem, which has been previously devised. This method is often independent of the particular computer to be used: it’s likely to be equally appropriate for many computers. In any case, it is the method, not the computer program itself, which must be studied to learn how the problem is being attacked. The term algorithm is universally used in computer science to describe problem-solving methods suitable for implementation as computer programs. Algorithms are the “stuff” of computer science: they are central objects of study in many, if not most, areas of the field.

Most algorithms of interest involve complicated methods of organizing the data involved in the computation. Objects created in this way are called data structures, and they are central objects of study in computer science. Thus, algorithms and data structures go hand in hand: data structures exist as the byproducts or endproducts of algorithms, and thus need to be studied in order to understand the algorithms. Simple algorithms can give rise to complicated data structures and, conversely, complicated algorithms can use simple data structures. When a very large computer program is to be developed, a great deal of effort must go into understanding and defining the problem to be solved, managing its complexity, and decomposing it into smaller subtasks which can be easily implemented. It is often true that many of the algorithms required after the decomposition are trivial to implement. However, in most cases there are a few algorithms the choice of which is critical since most of the system resources will be spent running those algorithms.

Оглавление.
Unit 1 Computation: Algorithms.
Background to writing: Text features.
A. Organization Of The Text.
B. Paragraph.
C. Introduction.
D. Organizing the Main Body.
E. Conclusion.
Unit 2 Computer modeling: The computer modeling process.
Background to wilting: Elements of writing (1).
A. Cause and Effect.
B. Cohesion.
C. Definitions.
D. Discussion.
E. Examples.
F. Generalizations.
Unit 3 Programming languages & paradigms: What is what?.
Background to wilting: Elements of writing (2).
A. Numbers.
B. References and Quotations.
C. Style.
D. Synonyms.
E. Tables and Figures.
Unit 4 Data Types In Programming: Is Data type essential?.
Accuracy in wilting: Accuracy (1).
A. Abbreviations.
B. Adverbs.
C. Articles.
Unit 5 Visual Programming Environment: What is VPE?.
Accuracy in wilting: Accuracy (2).
A. Conjunctions.
B. Caution.
C. Formality in Verbs.
Unit 6 Databases: How databases work?.
Accuracy in wilting: Accuracy (3).
A. Modals.
B. Nouns and Adjectives.
C. Nouns: Countable and Uncountable.
Unit 7 Network.
Accuracy in writing: Accuracy (4).
A. Passives.
B. Prefixes and Suffixes.
C. Prepositions.
Unit 8 The Internet & World Wide Web: The Internet or WWW?.
Writing: Practice (1): Formal letters.
Unit 9 E-Mail And Its Transfer Protocols.
Writing: Practice (2): Designing and Reporting Surveys.
Appendix I.



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