This document discusses factors to consider when selecting a programming language for a project. It outlines dimensions for selection like capabilities, productivity, and costs. Key criteria include whether the language can meet expectations, development costs, ramp up time, and community support. The document also evaluates common languages like Java, PHP, Python and Ruby based on their strengths and weaknesses. It predicts trends in language popularity and adoption of functional programming concepts.

1. Programming Language Selection
Dhananjay Nene
March 28, 2009
A PuneTech event

2. Why language selection ?
There is no universally superior language
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Language selection is fitment of language
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strengths and weaknesses to a context
Language selection often has long term
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implications including those of business
capability, cost and technology lock-in
It is therefore a technology + management
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decision

3. Dimensions of Selection
Capability : What the languages can / cannot
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do
Productivity : How efficiently can one write
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programs using the languge
Ramp Up : How easily can you get online
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Extraneous Factors
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Costs : What are the costs of using the
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language

4. Questions to be answered
Can the language deliver on expectations ?
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What is the cost of delivering on expectations
How long does it take to write and debug
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code ?
If I don't already have the skill sets what is the
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cost and time required to build them ?
What is the support structure available from
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community and corporate groups ?
What are the hardware and deployment costs ?
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5. Capability
Style Memory Usage
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Object Orientation Performance
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Function Orientation / Generic Classes
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Higher Order
Garbage Collection
Functions 
Typing Integration
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Static Error Handling
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Dynamic
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Multi-threading
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Reflection
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Library coverage and
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Metaprogramming support
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6. Object Orientation
Encapsulation / Information Hiding
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Inheritance
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Polymorphism
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Are all types objects ?
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Are all operations performed by sending
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messages to objects ?
Are all user defined types objects ?
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7. Functional Programming Elements
Higher Order Functions
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Code Blocks
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Generators (potentially infinite data, lazy
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evaluation)
List operations eg. map / reduce etc
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Closures
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Traditional : Haskell,Erlang
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Upcoming : Scala, Clojure, F#
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8. Static or Dynamic Types ?
In static typing, type is associated with a
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variable, in case of dynamic typing, it is
associated to the runtime value
Thus dynamic typing cannot often infer type
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until at runtime
Static typing catches more errors at compile
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time. Makes debugging easier
Dynamic types allows more flexibilities (eg
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metaprogramming) and lower compile idle
times

9. Metaprogramming
Inspect existing classes / methods
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Instantiate classes / Invoke methods using
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dynamic class / method structures
Create new classes / functions / methods on
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the fly ?
Modify existing classes / methods on the fly ?
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10. Productivity
Expressiveness
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Eg Wikipedia : Comparison of Programming Langs
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C / C++ =>1, JAVA => 1.5, Perl => 6, Python => 6.5
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Speed of writing code
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LOC per hour can also vary based on language
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http://page.mi.fu-
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berlin.de/prechelt/Biblio/jccpprt2_advances2003.pdf
Compilation overheads
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IDE speeds
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Refactoring capability
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11. Performance / Scalability /
Reliability
Performance : How fast can the programs run
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for given hardware
Scalability : How easily / cost effectively can the
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software be scaled to handle higher loads
Reliability : How fault tolerant can the resultant
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software be

12. Extraneous Factors
These are very important factors
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Customer Preferences
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Architecture Standards
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Frameworks and Libraries
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Community
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13. Deployment characteristics
Hardware Requirements
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Ease of cloud / virtualised hosting
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Hosting requirements for Small vs. Medium vs.
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Big apps
Clustering capabilities
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14. Adaptability / Agility
How quickly can you change based on
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changing requirements / objectives
Language is only one part of the mix
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Frameworks
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Design
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Processes
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15. Costs
Training
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Writing and Testing code
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Development Infrastructure
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Deployment Infrastructure
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16. Checklist
What do my customers want
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What does my architecture body state
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Can I meet performance / memory / app
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specific constraints ?
What is the performance sensitivity
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How critical is time to market
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How critical is adaptability and agility
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How critical are the budget constraints
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How quickly can I ramp up
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What is the available community
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17. My opinions on language futures
These are my own
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These are empirical
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These are subjective
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Languages under pressure :
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Java under pressure due to productivity issues
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PHP under pressure due to performance / hardware
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/ cormplex topologies
Python / Ruby under pressure due to smaller
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installed base and multicore concerns

18. Trends
Innovation in Web development is maturing
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Web and Pre-web architectures are both
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starting to get used
The VM is the new OS
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CPUs/Disks/RAM/Networks have grown fast
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enough for traditional transaction processing
Service Integration becoming critical
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Scaling, Multicore becoming important issue for
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many apps

19. Java
The big daddy - #1. But high entry barriers
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Long time to train, high requirements to deploy
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Low development productivity
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Superb performance, scalability, community
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Multi threading powerful but tough
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Considerable risk from other languages on the
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JVM eg. Jython, JRuby, Groovy, Scala, Clojure
Likely to loose share to competition
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20. PHP
Language with lowest entry barriers
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Easy to learn, easy to train
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Large community and supporters
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Phenomenally wide libraries coverage
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Scaling up is feasible but costs prohibitive
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Tougher acceptance when web + non web are
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used together
Unlikely to change share much due to a defined
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niche

21. Python / Ruby
High productivity and capability languages
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Have small but vibrant communities. Finding
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trained people can be tougher
Excellent Framework support
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Current runtimes have difficulties in multi
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threading
Lot of investments still continuing in VM
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development.
Likely to continue to grab more share.
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22. Functional Programming Langs
Lot of current interest. Am studying these with
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great interest.
Primarily useful for computation / algorithm
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intensive apps. As yet am unable to find them
useful for typical CRUD apps
Maturing still in progress. Too much rethinking
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and retraining required currently. Many items
still unclear (eg. ORMs, state maintenance,
performance)
Invest in short term only if very obvious benefits
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Suggest incremental FP usage to learn more
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