This Technical Note outlines binary instance data loading capabilities. Creation of instances for PIM domain classes is a key capability for PI-MDD systems, and different systems – and even different domains within a system – require different solutions to meet the overall functional and performance requirements.
The binary instance data can be sent to the application as a socket-based stream, or loaded via a process-local file. Binary instance loading provides the most concise data format and best performance for loading and inter-processor transport of large instance populations.
Open LDAP as A directory serviceis a system for storing and retrieving information in a tree-like structure with the following key properties:
Optimized for reading Distributed storage model Extensible data storage types Advanced search capabilities Consistent replication possibilities
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Open LDAP as A directory serviceis a system for storing and retrieving information in a tree-like structure with the following key properties:
Optimized for reading Distributed storage model Extensible data storage types Advanced search capabilities Consistent replication possibilities
DUCAT offers exclusive JAVA Training & Certification program with live project by industry expert In Noida,Ghaziabad,Gurgaon,Faridabad,Greater Noida,Jaipur
For further enquiry
DUCAT, NOIDA
A - 43 & A - 52 Sector - 16, Noida (U.P) (Near McDonalds)
PHONE: 0120-4646464
MOBILE OR WHATSAPP: +91- 9871055180
This Technical Note describes extensions to PathMATE’s C and C++ Maps to improve
static buffer management. These extensions support task-local memory management pools. They are based on the buffer manager.
The goals of this feature are to:
Reduce the run-time overhead associated with dynamic memory allocation, which normally goes through the BufferManager, an intertask-safe resource.
Allow for the specific sizing and allocation of dynamic memory blocks for specific classes.
The PI-MDD method for constructing software for complex and high performance systems
separates the complexities of the problem space subject matters from the strategies and
details of the implementation platforms the system executes within.
In PI-MDD one of the most fundamental disciplines pushes nearly all aspects of this complexity from the modeling space. So how is this clearly important, nearly ubiquitous, and non-trivial concern addressed with PI-MDD and PathMATE? The distributed deployment of PI-MDD models to multiple execution units is managed with an integrated set of model markings (properties), specialized code generation rules/templates and a flexible set of implementation mechanisms. The PIMDD models remain independent of this target environment topology, and can be deployed to
a range of topologies to support unit testing, system testing, and alternative deployment architectures.
This Technical Note describes the Message formats used in PathMATE Multi-Process
deployments when communicating between any two process instances.
Section 2 provides an overview of the different message protocol layers involved during
transmission defining basic terminology and the basic concepts.
Section 3 describes in the detail the PathMATE Application Messaging Protocol and all supported message formats, as defined for the CPP Transformation Maps in 8.2.0 software releases.
Appendix A lists sources for referenced information for Ethernet and TCPIP protocols.
This Technical Note describes the Message formats used in PathMATE Multi-Process deployments when communicating between any two process instances.
Section 2 provides an overview of the different message protocol layers involved during
transmission defining basic terminology and the basic concepts.
Section 3 describes in the detail the PathMATE Application Messaging Protocol and all supported message formats, as defined for the CPP Transformation Maps in 8.2.0 software releases.
Appendix A lists sources for referenced information for Ethernet and TCPIP protocols.
Index-based instance identification allows for the efficient retrieval of object instances from an instance population. Object instances using index-based instance identification contain an “identifier” attribute - indicated by the IndexID marking -
that uniquely identifies the instance. This marking will result in the generation of an instance population structure that uses the C++ Standard Template Library std::map, reducing FIND/WHERE constructs based on the id attribute to map lookup
via std::map::find().
Alternatively when used in conjunction with the MaxIndex class marking, this will result in the generation of an instance population structure using an array, reducing FIND/WHERE constructs based on the id attribute to a direct array element access.
Munching & crunching - Lucene index post-processingabial
Lucene EuroCon 10 presentation on index post-processing (splitting, merging, sorting, pruning), tiered search, bitwise search, and a few slides on MapReduce indexing models (I ran out of time to show them, but they are there...)
Oracle exalytics deployment for high availabilityPaulo Fagundes
This white paper contains technical details about how to configure a two node cluster of Oracle Exalytics systems running Oracle Business Intelligence Enterprise Edition with Oracle Exadata to enable high availability. The Maximum Availability Architecture (MAA) configuration requires horizontal scale out to be configured for scalability and performance (load balancing).
Dissolving the Problem (Making an ACID-Compliant Database Out of Apache Kafka®)confluent
Presenter: Tim Berglund, Senior Director of Developer Experience, Confluent
It has become a truism in the past decade that building systems at scale, using non-relational databases, requires giving up on the transactional guarantees afforded by the relational databases of yore. ACID transactional semantics are fine, but we all know you can’t have them all in a distributed system. Or can we?
In this talk, I will argue that by designing our systems around a distributed log like Apache Kafka®, we can in fact achieve ACID semantics at scale. We can ensure that distributed write operations can be applied atomically, consistently, in isolation between services, and of course with durability. What seems to be a counterintuitive conclusion ends up being straightforwardly achievable using existing technologies, as an elusive set of properties becomes relatively easy to achieve with the right architectural paradigm underlying the application.
Near Real time Indexing Kafka Messages to Apache Blur using Spark StreamingDibyendu Bhattacharya
My presentation at recently concluded Apache Big Data Conference Europe about the Reliable Low Level Kafka Spark Consumer I developed and an use case of real time indexing to Apache Blur using this consumer
This Technical Note describes extensions to PathMATE’s C and C++ Maps to improve
static buffer management. These extensions support task-local memory management pools. They are based on the buffer manager.
The goals of this feature are to:
Reduce the run-time overhead associated with dynamic memory allocation, which normally goes through the BufferManager, an intertask-safe resource.
Allow for the specific sizing and allocation of dynamic memory blocks for specific classes.
The PI-MDD method for constructing software for complex and high performance systems
separates the complexities of the problem space subject matters from the strategies and
details of the implementation platforms the system executes within.
In PI-MDD one of the most fundamental disciplines pushes nearly all aspects of this complexity from the modeling space. So how is this clearly important, nearly ubiquitous, and non-trivial concern addressed with PI-MDD and PathMATE? The distributed deployment of PI-MDD models to multiple execution units is managed with an integrated set of model markings (properties), specialized code generation rules/templates and a flexible set of implementation mechanisms. The PIMDD models remain independent of this target environment topology, and can be deployed to
a range of topologies to support unit testing, system testing, and alternative deployment architectures.
This Technical Note describes the Message formats used in PathMATE Multi-Process
deployments when communicating between any two process instances.
Section 2 provides an overview of the different message protocol layers involved during
transmission defining basic terminology and the basic concepts.
Section 3 describes in the detail the PathMATE Application Messaging Protocol and all supported message formats, as defined for the CPP Transformation Maps in 8.2.0 software releases.
Appendix A lists sources for referenced information for Ethernet and TCPIP protocols.
This Technical Note describes the Message formats used in PathMATE Multi-Process deployments when communicating between any two process instances.
Section 2 provides an overview of the different message protocol layers involved during
transmission defining basic terminology and the basic concepts.
Section 3 describes in the detail the PathMATE Application Messaging Protocol and all supported message formats, as defined for the CPP Transformation Maps in 8.2.0 software releases.
Appendix A lists sources for referenced information for Ethernet and TCPIP protocols.
Index-based instance identification allows for the efficient retrieval of object instances from an instance population. Object instances using index-based instance identification contain an “identifier” attribute - indicated by the IndexID marking -
that uniquely identifies the instance. This marking will result in the generation of an instance population structure that uses the C++ Standard Template Library std::map, reducing FIND/WHERE constructs based on the id attribute to map lookup
via std::map::find().
Alternatively when used in conjunction with the MaxIndex class marking, this will result in the generation of an instance population structure using an array, reducing FIND/WHERE constructs based on the id attribute to a direct array element access.
Munching & crunching - Lucene index post-processingabial
Lucene EuroCon 10 presentation on index post-processing (splitting, merging, sorting, pruning), tiered search, bitwise search, and a few slides on MapReduce indexing models (I ran out of time to show them, but they are there...)
Oracle exalytics deployment for high availabilityPaulo Fagundes
This white paper contains technical details about how to configure a two node cluster of Oracle Exalytics systems running Oracle Business Intelligence Enterprise Edition with Oracle Exadata to enable high availability. The Maximum Availability Architecture (MAA) configuration requires horizontal scale out to be configured for scalability and performance (load balancing).
Dissolving the Problem (Making an ACID-Compliant Database Out of Apache Kafka®)confluent
Presenter: Tim Berglund, Senior Director of Developer Experience, Confluent
It has become a truism in the past decade that building systems at scale, using non-relational databases, requires giving up on the transactional guarantees afforded by the relational databases of yore. ACID transactional semantics are fine, but we all know you can’t have them all in a distributed system. Or can we?
In this talk, I will argue that by designing our systems around a distributed log like Apache Kafka®, we can in fact achieve ACID semantics at scale. We can ensure that distributed write operations can be applied atomically, consistently, in isolation between services, and of course with durability. What seems to be a counterintuitive conclusion ends up being straightforwardly achievable using existing technologies, as an elusive set of properties becomes relatively easy to achieve with the right architectural paradigm underlying the application.
Near Real time Indexing Kafka Messages to Apache Blur using Spark StreamingDibyendu Bhattacharya
My presentation at recently concluded Apache Big Data Conference Europe about the Reliable Low Level Kafka Spark Consumer I developed and an use case of real time indexing to Apache Blur using this consumer
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile AppsMongoDB
Realm Database is the fast, easy to use, and open source alternative to SQLite and Core Data that is popular with hundreds of thousands of developers. Learn what makes it special and how it can be used to build better apps, faster.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
2. Table Of Contents
1. Introduction .......................................................................................... 1
2. Feature Details...................................................................................... 1
User Selection ........................................................................................ 1
Data Format ........................................................................................... 1
3. Marking Rules ....................................................................................... 3
4. Creating and Using Binary Instance Data .............................................. 3
File Creation ........................................................................................... 4
Binary Instance Data Transmission ............................................................ 4
5. Feature Implementation Impact Areas ................................................. 4
System Router........................................................................................ 4
Domain Loader ....................................................................................... 4
Class CreateFromBinaryData Method.......................................................... 5
Linking Methods...................................................................................... 5
File Reader............................................................................................. 5
Interprocess Message Routing................................................................... 5
pfdsocket.hpp......................................................................................... 5
6. ISSUES, QUESTIONS AND OPEN DISCUSSION ....................................... 5
SW Domain ............................................................................................ 5
Technical Note: Binary Instance Loading
3. www.pathfindermdd.com
1. Introduction
This Technical Note outlines binary instance data loading capabilities. Creation of
instances for PIM domain classes is a key capability for PI-MDD systems, and
different systems – and even different domains within a system – require different
solutions to meet the overall functional and performance requirements. The binary
instance data can be sent to the application as a socket-based stream, or loaded via
a process-local file.
Binary instance loading provides the most concise data format and best performance
for loading and inter-processor transport of large instance populations.
2. Feature Details
User Selection
The binary instance loading feature is enabled by marking classes and associations
with the BinaryInstanceData property. Setting this to “TRUE” will generate
appropriate binary instance data packet routing code at the system and domain
levels, and instance creation and linking methods at the PIM class level.
Data Format
Records
Binary instance data is organized into a record format. These records may be sent
via tcp/ip socket message and are recognizable to the standard PfdProcess
interprocess message receiver, which routes them to the system dispatcher.
General Record Format
type domain # contents EOR marker
value 1 to 4 <domain #> <varies> 0XEEEEEEEE
# bytes 1 2 varies 4
A binary instance data record has a byte for the type (1 to 4), a domain number, the
contents, and then 4 bytes used as an inter-record marker. While the code
producing or consuming a record intrinsically knows its contents, a marker is
provided as a second check to aid in detecting corrupted or incomplete data.
Record Stream
Records are formed into a Stream that contain the Class Instance Records and Link
Records for a single domain. A Record Stream starts with a Population Record, and
ends with a Population Complete Record.
Records are conveyed via files or inter-process messages. A Record Stream can be
grouped into one or more Record Blocks, where a Record Block is an individual file or
Technical Note: Binary Instance Loading 1
4. www.pathfindermdd.com
message containing one or more whole records. Streams and Blocks are subject to
these constraints:
The first record of a Stream must be a Population Record
The last record of a Stream must be a Population Complete Record
All records in a Stream must be for the same domain
A Block must contain complete records only.
Population Record
value 1 <domain #> <count> 0XEEEEEEEE
# bytes 1 2 4 4
This record indicates the total number of class instances that are to be loaded for
this specified domain from this Stream (via the full set of records, regardless of
blocking). This allows the domain’s binary instance loader to allocate an
appropriately sized instance id-to-pointer table.
The instance id-to-pointer table is an array of pointers used to retain the information
needed to rapidly process Link Records. A simple array of PfdObject* (the base class
for all modeled classes), it has one entry for each instance in the Stream. It is
created when a Population Record is processed, and deallocated when a Population
Complete Record is processed.
Class Instance Record
value 2 <domain #> <class #> <instance id #> <attribute values> 0XEEEEEEEE
# bytes 1 2 2 4 varies 4
This record contains the attribute values for the specified class instance. The
address of the newly created instance is stored in the transient instance id-to-pointer
table for subsequent Link Records. This table is indexed by instance_id, therefore
instance ids must:
Be unique for each instance – of any class – in this Stream
Start at 0
Have no gaps in the value range
The attribute values are the serialized forms for each attribute (but without the type
identifiers since they are known), to be retrieved with the get_<type>_from_buffer
serialization utility functions.
Link Record
value 3 <domain #> <assoc #> <part. 1 instance id> <part. 2 instance id> 0XEEEEEEEE
Technical Note: Binary Instance Loading 2
5. www.pathfindermdd.com
# bytes 1 2 2 4 4 4
This record contains the information to link two instances participating in an
association. The referenced instances must have been loaded previously in this
Stream.
Link Existing Instances Record
<part. 1 instance id <part. 2 instance id
value 3 <domain #> <assoc #> attribute value> attribute value> 0XEEEE
# bytes 1 2 2 4 4 4
This record contains the information to link two instances participating in an
association that were not necessarily part of this Stream. Each participant must
have an indentifying attribute. The referenced instances must have been created
before this record is processed.
Population Complete Record
Value 4 <domain #> 0XEEEEEEEE
# bytes 1 2 4
This record indicates all instances to be loaded via binary instance data have been
completed. The domain loader may deallocate the instance id-to-pointer table. After
the receipt of a Population Complete Record another population may be loaded by
sending a new Population Record.
Single Domain, Whole Record Blocking
It is generally assumed that a Block (file or message buffer) containing binary
instance data records will only contain records for a single domain. It is also
assumed to have whole records. That way code reading/receiving binary instance
data records does not have to concern itself with trying to detect if a complete record
has been read/received.
3. Marking Rules
Checking of the BinaryInstanceData markings ensures
No association has BinaryInstanceData == “TRUE” unless both participants
have BinaryInstanceData == “TRUE”.
o If a supertype class has BinaryInstanceData == “TRUE” then
BinaryInstanceData is set to “TRUE” automatically for all subtypes
4. Creating and Using Binary Instance Data
Technical Note: Binary Instance Loading 3
6. www.pathfindermdd.com
The suggested approach for creating binary instance data files is to build a Windows
deployment of the target domain, load in the required instance data via XML and use
the generated domain and class methods to create the binary instance data file.
Establishing the Instance Population
Use the standard XML instance file markings and run-time loading mechanisms to
create the instances needed.
Instance Selection
Each class with has BinaryInstanceData == “TRUE” gets a Boolean data member
writeBinary_ . This is set to TRUE by default when the instance is created. It is used
in the domain method BinaryWriteCurrentPopulation.
File Creation
Each domain with one or more classes marked with BinaryInstanceData generates a
static method BinaryWriteCurrentPopulation(String file_name). This method can be
invoked at any time and writes out a complete binary instance data stream of all
instances of class with BinaryInstanceData == “TRUE” and writeBinary_ == TRUE.
It also writes link records for all associations with BinaryInstanceData == “TRUE”
that have instances of both participants.
Binary Instance Data Transmission
To support the transmission of Binary Instance Data the new class
PfdBinaryInstanceData is used. It is a subtype of PfdSerializable. This SW domain
uses this to make messages containing binary instance data.
5. Feature Implementation Impact Areas
System Router
A system router method is generated when any class has its BinaryInstanceData
property set to “TRUE”. It gets a Binary Instance Data Block, checks the Domain #
in the first record and routs the block in its entirety to the appropriate domain.
Domain Loader
A domain loader method is generated when any of its classes has its
BinaryInstanceData property set to “TRUE”. It gets the Binary Instance Data Block
and steps through it one record at a time. For a Population Record it allocates an
instance id-to-pointer table. Class Instance Records are passed into the appropriate
class instance factory advancing the next record pointer appropriately. The pointer
to the newly created instance is put in the instance id-to-pointer table. Link Records
are decomposed by the loader and the appropriate instance pointers are passed into
Technical Note: Binary Instance Loading 4
7. www.pathfindermdd.com
link methods for each participant. A Population Complete Record triggers the
deallocation of the instance id-to-pointer table.
Class CreateFromBinaryData Method
If a class has its BinaryInstanceData property set to “TRUE” a class gets an
additional method: CreateFromBinaryData (message_buffer_t *binary_data_buffer,
int * binary_data_buffer_length). This method retrieves the attribute values from
the binary_data_buffer which has them in their serialized forms (but without the type
identifiers since they are known), retrieving them with the get_<type>_from_buffer
serialization utility functions. The binary_data_buffer pointer is incremented and the
byte count parameters is decremented for the data consumed.
After all attribute values are consumed, the binary_data_buffer is checked for an
EOR marker. If the marker is not found or any other error is encountered an error is
reported, the new instance is deleted and NULL is returned.
Linking Methods
Standard instance linking methods are used.
File Reader
See IDS domain below.
Interprocess Message Routing
See IDS domain below.
pfdsocket.hpp
Extend sw_socket_msg_type_e with SW_SOCK_MSG_BINARY_INSTANCE_RECORD.
6. ISSUES, QUESTIONS AND OPEN
DISCUSSION
SW Domain
We will add these services to the SoftwareMechanisms domain:
LoadBinaryInstanceData(String binary_instance_data_file_name);
SendBinaryInstanceData(DestinationHandle destination, String
binary_instance_data_file_name);
We may also want to include ReadXMLInstanceData.
Technical Note: Binary Instance Loading 5