CAST Imaging
Living knowledge base of your software inner workings
L. Perard & D. Charlemagne | CAST Product Marketing & Management
castsoftware.com
Software teams are struggling
Massive Complexity
Multiple technologies, millions of lines of code, 100,000 interdependent elements
Constant Change
Non-stop business-driven requests – from ‘small tweaks’ to all-out modernization
Knowledge Loss
Perennial 10-20%+ attrition and internal mobility diluting key tech knowledge
page 2
castsoftware.com
58% of developers’ time is spent understanding existing code structures
What are good candidates
for microservices?
What are the
dependencies with
other applications?
What is this application
made of?
How can I reduce
my consumption of
cloud services? What’s blocking to run this
in AWS?
How do I migrate to
Cosmos DB?
Have they correctly
implemented the designed
architecture?
What’s degrading the
performance efficiency
of my application?
What elements are
tightly coupled?
Why is this taking
so long?
Where else is this
DB table used?
IEEE study - Measuring
program comprehension
page 3
castsoftware.com
Finding answers is inefficient and slow
Lack of technical
knowledge base
Incomplete, outdated,
hard-to-find documentation
Manual digging
Through massive amount of code
Lack of business agility
and reactivity
To fix bugs, add features,
modernize applications
Awaiting SME responses
Interrupting them with basic questions
page 4
castsoftware.com
CAST Imaging automatically ‘understands’ software inner workings
Interactive blueprints
Reverse-engineered system logic
150+ languages, frameworks, databases
Source
code files
Property
files
Config
files
Database
scripts
page 5
castsoftware.com
CAST Imaging acts as a living knowledge base of your application internals
Powerful
Navigation
Precise
Analysis
Smart
Guidance
zooming, e2e transactions,
data access paths
decoupling, microservices,
change impact
structural flaws, cloud blockers,
modernization
technologies, code elements,
dependencies
Automatic
Discovery
“I can see in minutes what took three months to find before”
David Ruggiero | Modernization & Cloud Advisory Leader |
page 6
castsoftware.com
Typical benefits
Up to 25% faster
application modernization
Up to 50% faster
application discovery
Knowledge of systems, applications,
modules, architecture, dependencies
Ramping up newcomers
Assessing applications
Transitioning ADM teams
Up to 15% greater
ADM efficiency
Discovery of as-is inside architecture
and impact of structural changes
Breaking monoliths to microservices
Replacing DB engine or frameworks
Modernizing mainframe applications
Estimation & documentation of change
impact, architecture adherence
Adding new features or fixing bugs
Enforcing architectural specs
Remediating structural flaws
page 7
castsoftware.com
CAST Imaging client examples
Challenge
LTI was transitioning
2 extensive projects with about
a hundred applications to take
over maintenance and support.
Development teams were
spread out and could not work
all together at the same place
sharing knowledge.
Solution
LTI armed all teams on the
projects with CAST Imaging,
which automatically created
a living knowledge base of
the software internals. The
architects and developers were
able to discover, navigate, and
understand all the mechanics
of the applications on their own.
Results
LTI measured 20 to 30%
reduction in knowledge transition
time for those using CAST
Imaging. That was followed by a
decrease of rework and coding
effort by 30 to 40%. In addition,
due to precise identification of
impact of changes, defect density
dropped by 20 to 30%.
Greater responsiveness and efficiency
We now spend 30% less
time documenting and
understanding applications
Reema Gaurav
Engineering Manager
CAST Imaging minimizes
upgrade and testing efforts
Alan Capper
Global Leader
Application Modernization
We cut by 50% discovery
and documentation time
Narendra Kumar
Head of Engineering
We now have 10 to 15%
better productivity
Naresh Chaudhary
Associate Vice President
30%
faster knowledge
transition
40%
less rework and
coding
30%
lower defect
density
page 8
CAST Imaging Demo
page 9
castsoftware.com
Our Challenges
Performance
Software vendor
On-prem
Packaged
Complexity
Volume of data processed
Transactional context
Graphs overlay
Multi technos, multi systems
page 10
castsoftware.com
System and Application Architecture
page 11
By layers (East - West) By transaction (North - South)
11
• Technology used
• Processes and Practices
• Enterprise Architecture
• Application Architecture
Improve
Measure
Track the improvement
castsoftware.com
Origin of Neo4j at CAST
CAST
Knowledge
base
1995
2017
Neo4j Prototype
Benchmark
Docker/Windows
Modeling
ETL process
2018
2019
Official Product
CAST – NEO4J
OEM license
> 31 releases
Neo4j – 4.4.21
2023
page 12
castsoftware.com
CAST Imaging Technical Flow
page 13
Relational
database
Graph database
Config files CAST Imaging
Analysis
ETL
castsoftware.com
ETL process - Functional zoom
page 14
CSV files
NEO4J
POSTGRESQL
castsoftware.com
ETL process
Transactional context, regular update, transformation of data, delete -> one of our difficulties
Cypher queries in GO language, APOC usage
page 15
ETL
csv
Relational
database
castsoftware.com
Web application Technologies
page 16
Services
Web
Database
castsoftware.com
Volume of data in Neo4j
Application: up to 100 M Locs
Up to hundreds of applications aggregated into Neo4j
Multi tenant for data isolation
Sample of the number of links and nodes per application
Average
10 M of nodes, 100 M of relationships
Few customers
Up to 100 M of nodes to 500M of relationships
-> Full-text index implemented for Search. Works 45x faster than normal text based seraching
page 17
Objects Links LOC
JEE application 459 832 2 093 127 4 866 749
Mainframe application 149 821 368 448 4 141 163
SAP application 163 848 341 819 3 646 011
castsoftware.com
Why choosing Neo4J?
Technical reasons
Global reasons
A worldwide company with excellent
reactivity
Packaged
Technical skills
Market leader, long-term view
Technical support
Native and mature technology aligned
with our data
Easy to deploy
Cypher capability and simplicity
Flexible data model
High Performance for relationship
queries
page 18
castsoftware.com
Need to be improved…
Capability to write performant queries whatever our customer context
Make the Performance stable
Simplify our ETL Process
We get the limit of some of the functions like MERGE
• Should we develop our own User-defined procedures? …
Upgrade to Neo4j 5
Stabilization
page 19
Thank You
castsoftware.com/imaging

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  • 1.
    CAST Imaging Living knowledgebase of your software inner workings L. Perard & D. Charlemagne | CAST Product Marketing & Management
  • 2.
    castsoftware.com Software teams arestruggling Massive Complexity Multiple technologies, millions of lines of code, 100,000 interdependent elements Constant Change Non-stop business-driven requests – from ‘small tweaks’ to all-out modernization Knowledge Loss Perennial 10-20%+ attrition and internal mobility diluting key tech knowledge page 2
  • 3.
    castsoftware.com 58% of developers’time is spent understanding existing code structures What are good candidates for microservices? What are the dependencies with other applications? What is this application made of? How can I reduce my consumption of cloud services? What’s blocking to run this in AWS? How do I migrate to Cosmos DB? Have they correctly implemented the designed architecture? What’s degrading the performance efficiency of my application? What elements are tightly coupled? Why is this taking so long? Where else is this DB table used? IEEE study - Measuring program comprehension page 3
  • 4.
    castsoftware.com Finding answers isinefficient and slow Lack of technical knowledge base Incomplete, outdated, hard-to-find documentation Manual digging Through massive amount of code Lack of business agility and reactivity To fix bugs, add features, modernize applications Awaiting SME responses Interrupting them with basic questions page 4
  • 5.
    castsoftware.com CAST Imaging automatically‘understands’ software inner workings Interactive blueprints Reverse-engineered system logic 150+ languages, frameworks, databases Source code files Property files Config files Database scripts page 5
  • 6.
    castsoftware.com CAST Imaging actsas a living knowledge base of your application internals Powerful Navigation Precise Analysis Smart Guidance zooming, e2e transactions, data access paths decoupling, microservices, change impact structural flaws, cloud blockers, modernization technologies, code elements, dependencies Automatic Discovery “I can see in minutes what took three months to find before” David Ruggiero | Modernization & Cloud Advisory Leader | page 6
  • 7.
    castsoftware.com Typical benefits Up to25% faster application modernization Up to 50% faster application discovery Knowledge of systems, applications, modules, architecture, dependencies Ramping up newcomers Assessing applications Transitioning ADM teams Up to 15% greater ADM efficiency Discovery of as-is inside architecture and impact of structural changes Breaking monoliths to microservices Replacing DB engine or frameworks Modernizing mainframe applications Estimation & documentation of change impact, architecture adherence Adding new features or fixing bugs Enforcing architectural specs Remediating structural flaws page 7
  • 8.
    castsoftware.com CAST Imaging clientexamples Challenge LTI was transitioning 2 extensive projects with about a hundred applications to take over maintenance and support. Development teams were spread out and could not work all together at the same place sharing knowledge. Solution LTI armed all teams on the projects with CAST Imaging, which automatically created a living knowledge base of the software internals. The architects and developers were able to discover, navigate, and understand all the mechanics of the applications on their own. Results LTI measured 20 to 30% reduction in knowledge transition time for those using CAST Imaging. That was followed by a decrease of rework and coding effort by 30 to 40%. In addition, due to precise identification of impact of changes, defect density dropped by 20 to 30%. Greater responsiveness and efficiency We now spend 30% less time documenting and understanding applications Reema Gaurav Engineering Manager CAST Imaging minimizes upgrade and testing efforts Alan Capper Global Leader Application Modernization We cut by 50% discovery and documentation time Narendra Kumar Head of Engineering We now have 10 to 15% better productivity Naresh Chaudhary Associate Vice President 30% faster knowledge transition 40% less rework and coding 30% lower defect density page 8
  • 9.
  • 10.
    castsoftware.com Our Challenges Performance Software vendor On-prem Packaged Complexity Volumeof data processed Transactional context Graphs overlay Multi technos, multi systems page 10
  • 11.
    castsoftware.com System and ApplicationArchitecture page 11 By layers (East - West) By transaction (North - South) 11 • Technology used • Processes and Practices • Enterprise Architecture • Application Architecture Improve Measure Track the improvement
  • 12.
    castsoftware.com Origin of Neo4jat CAST CAST Knowledge base 1995 2017 Neo4j Prototype Benchmark Docker/Windows Modeling ETL process 2018 2019 Official Product CAST – NEO4J OEM license > 31 releases Neo4j – 4.4.21 2023 page 12
  • 13.
    castsoftware.com CAST Imaging TechnicalFlow page 13 Relational database Graph database Config files CAST Imaging Analysis ETL
  • 14.
    castsoftware.com ETL process -Functional zoom page 14 CSV files NEO4J POSTGRESQL
  • 15.
    castsoftware.com ETL process Transactional context,regular update, transformation of data, delete -> one of our difficulties Cypher queries in GO language, APOC usage page 15 ETL csv Relational database
  • 16.
  • 17.
    castsoftware.com Volume of datain Neo4j Application: up to 100 M Locs Up to hundreds of applications aggregated into Neo4j Multi tenant for data isolation Sample of the number of links and nodes per application Average 10 M of nodes, 100 M of relationships Few customers Up to 100 M of nodes to 500M of relationships -> Full-text index implemented for Search. Works 45x faster than normal text based seraching page 17 Objects Links LOC JEE application 459 832 2 093 127 4 866 749 Mainframe application 149 821 368 448 4 141 163 SAP application 163 848 341 819 3 646 011
  • 18.
    castsoftware.com Why choosing Neo4J? Technicalreasons Global reasons A worldwide company with excellent reactivity Packaged Technical skills Market leader, long-term view Technical support Native and mature technology aligned with our data Easy to deploy Cypher capability and simplicity Flexible data model High Performance for relationship queries page 18
  • 19.
    castsoftware.com Need to beimproved… Capability to write performant queries whatever our customer context Make the Performance stable Simplify our ETL Process We get the limit of some of the functions like MERGE • Should we develop our own User-defined procedures? … Upgrade to Neo4j 5 Stabilization page 19
  • 20.