ABOUT ME

ADAPTIVE SOFTWARE |

Samudra KanankearachchiSenior Software Architect@99XTechnologyData Science Specialist

NEXT GENERATION OF ADAPTIVE ENTERPRISE APPS

GOOGLE SEARCH ON

LET’S RE-THINK WHAT DARWIN SAID

It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change

Evolution = Variation + Natural SelectionEMPIRICAL STUDIES IN WILD

1. Price Sensitive Variations.

2. Quality Sensitive Variations

3. Feature Sensitive Variations

EXAMPLE FROM TELEPHONE MARKET

One variation

Few variation

Many variation

Redesign Redesign

REPRODUCTION BY ENGINEERS (LESS ADAPTIVE)

Mon

olit

hic

Arch

itec

ture

s

Mic

ro S

ervi

ce

Arch

itec

ture

s

SOA

Arc

hite

ctur

es

vari

atio

ns a

re m

ade

at

appl

icat

ion

desi

gn t

ime

(A

stat

ic a

ppro

ach)

Evolution = Variation + End User Selection

HOW DO WE MAKE THE EVOLUTION PROCESS DYNAMIC

SAMPLE USE CASE (TOURISM DOMAIN)

Feature set:

1. Search location2. Book hotels3. Search flights4. Discounts5. Popular places

USER NEEDS ARE DIFFERENT

A MONOLITHIC APPLICATION/ DIFFERENT USERS

Budgeter

Explorer

Traveler

STEP1 : DECOMPOSE THE APPLICATION INTO MICRO FEATURES

USER APP = F ( FEATURE, ACTIVITY , DEVICE TYPE, USER BEHAVIOR)

DEMO

Starter Layout

STEP 2 - DYNAMIC APP GENERATION

CONFIGURATION BASE DYNAMIC APP GENERATION

Dyna

mic

Appl

icatio

n Ge

nera

tor

Feature Configurati

on

Activity Configurati

on

Layout Configurati

on

Application

STEP 3 SUPERVISED LEARNING PROCESS

Trai

n bu

dget

er

Trai

n Ex

plor

er

Trai

n

trav

eler

AWS Integration Service(Node JS)

ML APIAdaptive Query API

Analytics on user events

Models for (B , T, E)

AWS Integration Service(Node JS)

ML APIAdaptive Query API

Analytics on user events

Question : What is my type

Answer :Budgeter

A regular user

Models for (B , T, E)

THANK YOU