About SDL
Simple
DirectMedia Layer (SDL) is a cross-platform software development library
designed to provide a low level hardware abstraction layer to computer
multimedia hardware components. Software developers can use it to write
high-performance computer games and other multimedia applications that can run
on many operating systems such as Android, iOS, Linux, Mac OS X, Windows and
other platforms.[4]
SDL
manages video, audio, input devices, CD-ROM, threads, shared object loading,
networking and timers.[5] For 3D graphics it can handle an OpenGL or Direct3D
context.
The
library is internally written in C and Objective-C[clarification needed] and
provides the application programming interface in C, with bindings to other
languages available.[6] It is free and open-source software subject to the
requirements of the zlib License since version 2.0 and with prior versions
subject to the GNU Lesser General Public License.[3] Under the zlib License,
SDL 2.0 is freely available for static linking in closed-source projects,
unlike SDL 1.2.[7]
SDL
is extensively used in the industry in both large and small projects. Over 700
games, 180 applications, and 120 demos have also been posted on the library
website.
A
common misconception is that SDL is a game engine, but this is not true.
However, the library is well-suited for building an engine on top of it.
Advantages Of Using SDL
Machine Translation
SDL is the leader in language
translation and global content management. With more than 20 years of
experience, SDL helps companies build relevant digital experiences that deliver
transformative business results on a global scale.
Bespoke, high-quality output
Complete your projects faster than
ever, while preserving translation quality, with the ability to train your own
machine translation engines. SDL Language Cloud Custom MT Engines provide
translators with a source of bespoke, high-quality MT output that requires
minimal post-editing before publishing.
Boost
translation productivity
Achieve
new levels of productivity by tailoring your own engines to your specific
requirements; specific clients, projects or industry verticals. A trained
engine can translate industry terminology 24% more consistently than an
untrained engine, helping you work more efficiently.
The
benefits of Custom MT Engines
• Trainable -
Enhance translation quality with the ability to train your own engines
• Secure
- Your data is protected and translated over a secure, encrypted connection
• Cloud-based -
No hardware costs, easy to get started, no maintenance
• 100
baseline language pairs - Try various language pairs
quickly and easily with no additional costs
• Seamless
- Designed to integrate with SDL's world leading language technologies
• Flexible
pricing - A flexible package that allows you to use machine
translation as often as you wish
SDL
Translate is your 'all in one' translation solution. It's a communication
platform, phrase dictionary, language teacher, and travel companion. With over
90 language pairings including Spanish, German, French, Italian, Chinese and
Arabic (www.freetranslation.com), SDL Translate covers every corner of the
globe.
Key Features:
-
Text to speech (TTS) * : Write a sentence and tap the translation to hear it.
-
Speech to text (STT) * : Tap the microphone button and speak to get your
sentence translated.
-
Phrases: Introductory Phrases in Spanish, German, and French. Available without
a network connection.
-
Idiomatic Expressions: Ever wanted to know how to say "Piece of Cake"
in another language? Now you can translate 65 Idiomatic expressions from
English to Spanish, French, or German.
*
This feature depends on the available languages on your device.
The following languages are
available for Translation:
Western Europe:
Danish ⇨ English
Dutch ⇨ English
English ⇨ Albanian
English ⇨ Arabic
English ⇨ Bengali
English ⇨ Bulgarian
English ⇨ Chinese (Simplified)
English ⇨ Chinese (Traditional)
English ⇨ Czech
English ⇨ Danish
English ⇨ Dutch
English ⇨ Estonian
English ⇨ Finnish
English ⇨ French
English ⇨ German
English ⇨ Greek
English ⇨ Pashto
English ⇨ Hausa
English ⇨ Hebrew
English ⇨ Hindi
English ⇨ Hungarian
English ⇨ Indonesian
English ⇨ Italian
English ⇨ Japanese
English ⇨ Korean
English ⇨ Latvian
English ⇨ Lithuanian
English ⇨ Malay
English ⇨ Norwegian
English ⇨ Polish
English ⇨ Portuguese
English ⇨ Persian
English ⇨ Romanian
English ⇨ Russian
English ⇨ Spanish
English ⇨ Somali
English ⇨ Serbian
English ⇨ Slovak
English ⇨ Slovenian
English ⇨ Swedish
English ⇨ Thai
English ⇨ Turkish
English ⇨ Ukrainian
English ⇨ Urdu
English ⇨ Vietnamese
Finnish ⇨ English
French ⇨ English
French ⇨ Arabic
French ⇨ Spanish
French ⇨ German
Spanish ⇨ Italian
German ⇨ English
German ⇨ French
German ⇨ Spanish
Greek ⇨ English
Italian ⇨ English
Italian ⇨ Spanish
Norwegian ⇨ English
Portuguese ⇨ English
Spanish ⇨ English
Spanish ⇨ Arabic
Spanish ⇨ French
Spanish ⇨ German
Swedish ⇨ English
Dutch ⇨ English
English ⇨ Albanian
English ⇨ Arabic
English ⇨ Bengali
English ⇨ Bulgarian
English ⇨ Chinese (Simplified)
English ⇨ Chinese (Traditional)
English ⇨ Czech
English ⇨ Danish
English ⇨ Dutch
English ⇨ Estonian
English ⇨ Finnish
English ⇨ French
English ⇨ German
English ⇨ Greek
English ⇨ Pashto
English ⇨ Hausa
English ⇨ Hebrew
English ⇨ Hindi
English ⇨ Hungarian
English ⇨ Indonesian
English ⇨ Italian
English ⇨ Japanese
English ⇨ Korean
English ⇨ Latvian
English ⇨ Lithuanian
English ⇨ Malay
English ⇨ Norwegian
English ⇨ Polish
English ⇨ Portuguese
English ⇨ Persian
English ⇨ Romanian
English ⇨ Russian
English ⇨ Spanish
English ⇨ Somali
English ⇨ Serbian
English ⇨ Slovak
English ⇨ Slovenian
English ⇨ Swedish
English ⇨ Thai
English ⇨ Turkish
English ⇨ Ukrainian
English ⇨ Urdu
English ⇨ Vietnamese
Finnish ⇨ English
French ⇨ English
French ⇨ Arabic
French ⇨ Spanish
French ⇨ German
Spanish ⇨ Italian
German ⇨ English
German ⇨ French
German ⇨ Spanish
Greek ⇨ English
Italian ⇨ English
Italian ⇨ Spanish
Norwegian ⇨ English
Portuguese ⇨ English
Spanish ⇨ English
Spanish ⇨ Arabic
Spanish ⇨ French
Spanish ⇨ German
Swedish ⇨ English
Eastern Europe:
Albanian ⇨ English
Bulgarian ⇨ English
Czech ⇨ English
Estonian ⇨ English
Hungarian ⇨ English
Latvian ⇨ English
Lithuanian ⇨ English
Polish ⇨ English
Romanian ⇨ English
Russian ⇨ English
Slovak ⇨ English
Serbian ⇨ English
Slovenian ⇨ English
Ukrainian ⇨ English
Bulgarian ⇨ English
Czech ⇨ English
Estonian ⇨ English
Hungarian ⇨ English
Latvian ⇨ English
Lithuanian ⇨ English
Polish ⇨ English
Romanian ⇨ English
Russian ⇨ English
Slovak ⇨ English
Serbian ⇨ English
Slovenian ⇨ English
Ukrainian ⇨ English
Middle East & Africa:
Arabic ⇨ English
Arabic ⇨ Spanish
Arabic ⇨ French
Hausa ⇨ English
Hebrew ⇨ English
Pashto ⇨ English
Persian ⇨ English
Somali ⇨ English
Turkish ⇨ English
Arabic ⇨ Spanish
Arabic ⇨ French
Hausa ⇨ English
Hebrew ⇨ English
Pashto ⇨ English
Persian ⇨ English
Somali ⇨ English
Turkish ⇨ English
Asia:
Bengali ⇨ English
Hindi ⇨ English
Korean ⇨ English
Urdu ⇨ English
Chinese (Simplified) ⇨ English
Chinese (Traditional) ⇨ English
Indonesian ⇨ English
Malay ⇨ English
Vietnamese ⇨ English
Japanese ⇨ English
Thai ⇨ English
Hindi ⇨ English
Korean ⇨ English
Urdu ⇨ English
Chinese (Simplified) ⇨ English
Chinese (Traditional) ⇨ English
Indonesian ⇨ English
Malay ⇨ English
Vietnamese ⇨ English
Japanese ⇨ English
Thai ⇨ English
1.
More Secure Software
The
SDL Helps You Build Software That's More Secure by Reducing the Number and
Severity of Vulnerabilities in Your Code
The
ultimate test of the SDL is the extent to which it can reduce the number and
severity of vulnerabilities in software. In order to measure the extent to
which these goals are met, security experts analyzed public vulnerability
counts in "pre-SDL" and "post-SDL" versions of the same
product in the 12 months (or more) following the release.
Although
these results do not imply that all vulnerabilities will be found, the examples
below demonstrate the effectiveness of the SDL in reducing the number of
security vulnerabilities of products that were developed with it.
Microsoft
SQL Server: 91% Fewer Vulnerabilities in SQL Server 2005
SQL
Server serves as an excellent example for security improvements resulting from
incorporating the SDL. Within the three years after release, Microsoft has
issued three security bulletins for the SQL Server 2005 database engine.
2.
Help Address Compliance Requirements
Organizations
that develop software need to comply with a variety of complex, ever-changing
regulations. Incorporating the SDL into the application development process
helps meet compliance requirements and produce a return on investment (ROI) by
guiding organizations to make smart choices early in the design process,
thereby minimizing expensive inefficiencies.
The
SDL encourages organizations to:
- Go beyond today's compliance requirements, enabling organizations to take a proactive, forward-thinking approach.
- Eliminate redundancies and coordinate processes, thereby streamlining the efficiency of application development.
- Improve productivity while helping ensure compliance.
- Improve application security with a holistic, step-by-step approach.
- Improve productivity while helping ensure compliance.

3.
Reduce Costs
SDL
Helps Reduce the Total Cost of Development
The
National Institute of Standards and Technology (NIST) estimates that code fixes
performed after release can result in 30 times the cost of fixes performed
during the design phase. Additional costs may include a significant loss of user
productivity and confidence. The SDL systematically addresses software security
during the development phase, ensuring that vulnerabilities are more likely to
be found and fixed prior to application deployment and thereby reducing your
total cost of software development.
The
Forrester Consulting State of Application Security study reported that
organizations implementing an SDL process showed better ROI results than the
overall surveyed population.
Aberdeen
Group demonstrated how adopting an SDL process increases security and reduces
the severity and cost of vulnerability incidents while generating a stronger
return on investment (four-times higher) than other application security
approaches.
Disadvantages Of Using
SDL Machine Translation
There
are some disadvantages when we use SDL as an alternative machine translation to
help us during translating the text, there are:
·
When we translate a text use SDL Machine Translation, the result of
translation isn’t natural. It depends on the original text. When the translator
tries to quote a sentence or idiom or paraphrase from a novel; nevertheless, SDL Machine Translation translates the
passage unnaturally.
·
The accuracy isn’t fully offered by SDL Machine Translation on a consistent
basis. Usually, we can get the gist of the texts or anything else like that,
but SDL Machine Translation only
does word to word translation without comprehending the information which might
have to be corrected manually later on. SDL
Machine Translation rarely reaches accuracy levels above 70%, while a human
translation almost always produces accuracy above 95%.
·
SDL
Machine Translation is based on formal and systematic
rules, the inferior translation quality of the texts with ambiguous words and
sentences. So, sometimes SDL Machine
Translation cannot solve the ambiguity by concentrating on a context and
using experience or mental outlook as a
human translator.
·
SDL
cannot
translate phrase, idiom, countable and uncountable noun correctly. It can be
proved in the next page of this assignment.
·
In summary, SDL Machine Translation is good enough and suitable to translate
just the official document or an article.
The
translation result of SDL
Due to the size of SDL application is very big, it
is about more than 300mb, we translate the text with the website of SDL
https://www.freetranslation.com/
1.
Translating
Noun Phrase with SDL

From
the screenshot above, it shows that in translating Indonesian noun phrase wanita muda yang sangat cantik, the
result in English is the young woman was
very beautiful. If we look at the result of the translation, the structure
is grammatically correct, but the tense it should be simple present tense not
simple past tense. In source language the form is a noun phrase, meanwhile in the target language the form changes, become
a sentence.


TL:
the young woman was very beautiful
Comparing to Ginger

If
we compare SDL to Ginger, Ginger produces a better result than SDL. Indonesian
noun phrase wanita muda yang sangat
cantik is translated into a pretty
young lady, in source language the form is a noun phrase, meanwhile in the
source text the form is translated also into a noun phrase.


TL:
a pretty young
lady
2.
Translating
Idiom with SDL

In
translating Indonesian Idiom Raisa benar
– benar memiliki suara emas, in
English the result is Raissa really have
a voice of gold. In source language “Raisa” and in target language is
“Raissa”. It is grammatically incorrect. It should be Raisa really has a voice
of gold because “has” is used for subject
she, he or it and now we discuss about Raisa, we know Raisa is female
singer (she).
Compare with Ginger

In
ginger the result is grammaticaly is correct. It uses has. But we find the different
in the subject. In source language we discuss about Raisa but in Target
language it changes to be Katy Perry.
3. Translating Countable and
Uncountable Noun with SDL

From
the screenshot above, it shows that in translating countable and uncountable
noun using SDL from Indonesian source language kami membeli banyak sekali keju dan bunga into English target
language we buy a lot of cheese and
interest. In the target language the structure is grammatically correct,
and it uses simple present tense. The quantifier a lot of can be used for both countable and uncountable noun, so
the use of a lot of is correct. The
word cheese is uncountable noun, we cannot add suffix –s, SDL translates it
correctly. Unfortunately the source language bunga is translated into interest
in target language, it should be translated into flowers, it proves that SDL is not able to recognize context of the
text.






TL:
we buy a lot of cheese and interest
Comparing to Ginger

Ginger
translates the Indonesian source language kami
membeli banyak sekali keju dan bunga into English target language we bought lots of cheese and flowers. The structure is grammatically correct, it uses simple
past tense, which is correct. Unlike the result produced by SDL, ginger
translates banyak sekali into lots of, it is correct, because
quantifier lots of is used for both
countable and uncountable noun. Keju dan
bunga is translated into cheese and
flowers, ginger translates it correctly, we cannot add suffix –s in plural
form of the word cheese, because it
is uncountable noun. Unlike SDL, translating bunga into interest,
ginger translates it into flowers, which is correct. We add suffix –s in plural
form of countable noun, flower is countable noun, so we add suffix –s becomes
flowers. Ginger is able to recognize the context of the text.
We can take a conclusion, SDL doesn’t produce
a good translation, ginger translates better than SDL.






TL: we bought lots of cheese and flowers
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