CSCI 578: Software Architectures - Center for Software Engineering

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Transcript CSCI 578: Software Architectures - Center for Software Engineering

CSCI 578
Software Architectures
Dr. Chris Mattmann
Tuesday, August 27, 2013
The Class
Will give you a complete treatment of the area of
software architecture
• The fundamental building blocks of software
systems
• Components (units of computation)
• Connectors (interactions between the
software components)
• Configurations (arrangements of
components and connectors)
Will equip you with the necessary skills to design
complex, real-world software
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General Class Information
Lecture, but…
• You can participate
• You should participate
• You will participate, that is, if you want
to do well :)
On-campus, and remote (DEN) sections
• DEN section capped at 20 students
• Not my limit, but DEN’s
• Please ask questions, if you need
to
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General Class Information
Syllabus/Web Site:
• http://sunset.usc.edu/classes/cs578_201
3b/
• Visit it often, as the schedule may
change!
• This is where all of your homework
assignments will be posted
• This site will point you to required
reading, and to lectures that you can
download before class
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What We’ll Cover
The entire spectrum of software architecture
• Where it fits in the overall software
engineering process -- it’s the linchpin!
• Software architectural styles, product line
architectures, components, connectors,
implementation frameworks, middleware, nonfunctional properties, visualization, the role of
the architect…lots of topics!
Topical research in software architecture
• (Optional) papers, data-intensive systems, etc.
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Me
Graduated with my Ph.D. in Computer Science from
USC in 2007
• Advisor: Dr. Nenad Medvidovic
Was a student at USC from 1998-2007
• B.S., Computer Science 2001
• M.S., Computer Science 2003
My research interests
• Open Source Software, Apache Software
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Foundation
Was one of the inventors of Hadoop (Nutch PMC)
Inventor of Apache Tika, http://tika.apache.org/
The intersection of software architectures, and
large-scale data dissemination
Information Retrieval
Search Engines – I’m teaching a class, CS572, on
this topic during Spring 2013
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My Other Day Job
• The Big Picture
• Astronomy, Earth science, planetary science, life/physical
science all drowning in data
• Fundamental technologies and emerging techniques in
archiving and data science
• Largely center around open source communities and
related systems
• Research challenges (adapted from NSF)
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More data is being collected than we can store
Many data sets are too large to download
Many data sets are too poorly organized to be useful
Many data sets are heterogeneous in type, structure
Data utility is limited by our ability to use it
U.S. National Climate Assessment (pic credit: Dr. Tom Painter)
• Proposal focus: Big Data Archiving
• Research methods for integrating intelligent
algorithms for data triage, subsetting, summarization
• Construct technologies for smart data movement
• Evaluate cloud computing for storage/processing
• Construct data/metadata translators “Babel Fish”
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SKA South Africa: Square Kilometre Array (pic credit: Dr. Jasper Horrell, Simon Ratcliffe)
Where we’re headed
Nature magazine piece
on “A Vision for Data
Science” in Jan. 24th
issue
• Big Data Initiative
highlighted
• Outline algorithm
integration (regridding,
metrics); automatic
understanding of data
metadata formats and
open source as “key issues”
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Software Architecture
Research Problem
•In a performant
manner?
•Fulfilling system
requirements?
NASA Planetary Data System
Archive Volume Growth
90
80
70
60
TB (Accum)
Content repositories are
growing rapidly in size
At the same time, we
expect more immediate
dissemination of this
data
How do we distribute it…
50
TBytes
40
30
20
10
0
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Year
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Data Distribution Technologies
GridFTP
XML-RPC
bbFTP
Which one is
Aspera
the
best one?
Bittorrent
SCP
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RMI
UFTP
Given
our Siena
current
architecture?
FTP
CORBA
Given ourSOAP SFTP
distributionJXTA
HTTP/REST
scenarios
and
GLIDE/PRISM-MW
requirements?
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Architectural Decisions
• Architectural decisions (such as connector selection) impact
functional and non-functional properties of the overall data
distribution system architecture
• It does matter what connector you select
• Functional (performance)
• Efficiency, consistency, scalability, dependability of the data
transfer
• Non-functional (e.g., interoperability, security)
• We assert that this process has largely remained an art
form and forces organizations to rely on organizational
gurus whose knowledge is never encoded or understood
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Overall Approach
“White Box” Guru
Connector KB
Data Distribution
System Architecture
Data System
Architect
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“Black Box” Guru
So, today…
You’re free to enjoy the day
Course book
(Possible) Reading assignment
• Chapter 1: The Big Idea
Be ready to get going on Thursday
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