model driven development and code generation of software systems

Model-Driven Development and Code Generation of Software Systems

Marco BrambillaPolitecnico di Milano [email protected]

@marcobrambi

Agenda

• Research field

• Research path

• A sample of research topics• From business processes to software applications

• Generating code for crowdsourcing

• Impact and perspectives

Field

Marco BrambillaPolitecnico di Milano

@marcobrambi

• Improving software development and maintenance productivity

Context

Liberated programmingSelf-healing and self-

evolving programs

End-user Development (EUP), Mashups, …

Agile development

Modeling and Code Generation Approaches

(MDE)

[B1] Brambilla, Cabot, Wimmer. Model-Driven Software Engineering In Practice.

Morgan & Claypool, USA, 2012.

• Engineering practices based on models

Model-based Engineering

Model

Features:• Mapping • Reduction• Pragmatism

System

Represents

Purposes: • Descriptive• Prescriptive

• Model-Based Engineering (MBE)

• Model-Driven Engineering (MDE)

• Model-Driven Development (MDD)

• Model-driven Architecture (MDA)

The MD* Acronyms Map

• Models (M)

• Model Transformations (MT)

The MDE Ingredients

MDE Basic ArchitectureR

ealiz

atio

nM

odel

ing

Model

Artifacts(e.g. code)

Modelinglanguage

Platform

Meta-modelinglanguage

Transformationdefinition

Transformationlanguage

uses

defined using

defined by

Application domainApplication Meta-Level

Aut

omat

ion

Transformation

Abstraction (bottom-up)Reuse

Construction (top-down)

Research Path


@marcobrambi

Research pathS

uppo

rted

sub

syst

ems

and

data

sou

rces

SW Devel. Process Span

Crowds

Social Net.

Search Eng.

Ontologies

Processes

Web Serv.

Relational

Requirements Business Design Application Design Code Gen.

Data intensive

SOA

BPM

Sem. Web / LD

Structured Web Data

SN Integr. & Expert finding

Crowd control & integr.

Social BPM

Advanced Search UI

Main research resultsS

uppo

rted

sub

syst

ems

and

data

sou

rces

Crowds.

Social Net.

Search Eng.

Ontologies/ Sem. Web

Processes

Web Serv.

Relational (& MDE)

• Reactive CrowdSourcing. ACM Conf. on World Wide Web WWW 2013• Answering search queries with CrowdSearcher. ACM Conf. on World Wide Web

WWW 2012

• Choosing the Right Crowd: Expert Finding in Social Networks, EDBT 2013• From Requirements to Implementation of Ad-hoc Social Web Applications: an

Empirical Pattern-Based Approach. IET-Sw, 2012

• A bottom-up, knowledge-aware approach to integrating and querying web data services. ACM Trans. on the Web (TWEB), 2013

• Exploratory search framework for Web data sources. VLDB Journal, 2013

• Model-Driven Design and Development of Semantic Web Service Applications, ACM Trans. on Internet Technology (TOIT), 2007

• Process modeling in Web applications. ACM Trans. Softw. Eng. Methodol (TOSEM), 2006

• Exception Handling in Workflow-Driven Web Applications. ACM Conf. on World Wide Web WWW 2005

• Model-driven design and deployment of service-enabled web applications. ACM Trans. Internet Technology (TOIT), 2005

• Designing Data-Intensive Web Applications, Morgan-Kaufmann, 2003• The Role of Visual Tools in a Web Application Design and Verification

Framework: A Visual Notation for LTL Formulae.Conf. Web Eng. ICWE 2005• Content search over model repositories. ACM Transactions on the Web (TWEB),

2014 in print.

Topic 1From Business Processesto Software Applications


@marcobrambi

Addressed problem

• Communication chasm between business and IT is one of the main weaknesses of large organizations• Different language

• Different objectives

• Different quality metrics

• Bridging the gap between business requirements and IT realizations (from design to deployment)

• My challenge: • Business business processes (BPMN)

• IT SOA-oriented and Web-based implementation

• Manual specification of BPMN process model

• Automatic transformation of BPMN to WebML

• Possible manual refinement of WebML models

• Automatic full code generation

Model-driven Development Process

BPM Application model transformation

Transformation rulesINPUT: BPMN model enriched with data and activity typing

• typed activities enable reusable application models• data dependencies are specified at high level

BPM Application model transformation

Transformation rulesOUTPUT: fine-grained Application Model, needing few refinements by the designer

BPMN WebML transformation

20

(1) One control siteview per pool: Human interaction


21

(1) One control siteview per pool: Human interaction(2) One control view per pool: Choreography


22

(1) One control siteview per pool: Human interaction(2) One control serviceview per pool: WS Choreography(3) One site view per lane: user navigation


23

(4) One site view per lane: business logics of activities and gateways

BPMN WebML transformationTransformation rules

finer-grained Application Model, needing few refinements by the designer

• typed activities enables reusable application models• data dependencies are specified at a higher level

less errors in Application Model design

Faster development

24

(1) One control siteview per pool: Human interaction(2) One control serviceview per pool: WS Choreography(3) One site view per lane: user navigation(4) One site view per lane: business logics of activities and gateways(4) One site view per lane: business logics of activities and gateways(5) Orchestration view: a controller component invokes the activities

• Backward engineering (2): modularization of hypertext pieces and reuse as activity types through catalogues

• Reverse Engineering (3): decomposition of the web application and extraction of the BP model

• Aspect-oriented adaptation of transformation rules: • Higher order transformations for: security, company-specific integration, …

• Cross-model validation &coherence

Additional investigations

Topic 2Crowdsourcing based

web applications


@marcobrambi

•Schema of the process decided and deployed centrally•Tasks defined rigidly •Actor roles predefined and assigned to tasks

Closed BPM

•Opens the process design to multiple actors•Stakeholders can participate and fuse processes•End users can define their processes

Participatory Design

•Social tools integrated into the process execution•Collateral communications allowed, like following up the status, commenting, voting, etc.

Participatory Enactment

•Process execution open (in part) to actors that are not known a priori•Collective (community or crowd based) execution of a task allowed.

Social/Crowd Enactment

From BPM to Social and Crowd Performers

Crowd-based Applications

Emerging crowd-based applications:opinion mining

localized information or expert response gathering

content annotation and enrichment

General structure of crowdsourcing: the requestor poses some questions

a wide set of responders (typically unknown to the requestor)are in charge of providing answers

the crowdsourcing system organizes a response collection campaign

Crowd Control is tough…

Crowd engineering is complicated Task design, planning, assignment

Workers discovery, assessment, engagement

Controlling crowdsourcing is fundamentalCost

Time

Quality

Need for higher level abstraction and tools

My take on crowdsourcing: CrowdSearcher

Crowdsearcher comprises • a conceptual framework

• a specification paradigm and tool

• a reactive execution control environment

Supports designing, deploying, monitoring, and controlling crowd-based systems

Design is top-down, platform-independent

Deployment turns declarative specifications into platform-specific implementations which include social networks and crowdsourcing platforms

(simplified) example: crowdsourcing opinions on new job position (1)

(simplified) example: crowdsourcing opinions on new job position (2)

The CrowdSearcher features and architecture

Cross-platform integration: social networks and Q&A websites in addition to crowdsourcing platforms

Crowd control: model-driven engine controls application deployment and execution

CrowdSearcher

API Access

A simple task design and deployment process, based on specific data structures

created using model-driven transformations

driven by the task specification

The Design Process of crowd-based apps within CrowdSearcher

Task Specification Task Planning Control Specification

• Task Specification: task operations, objects, and performers• Task Planning: work distribution• Control Specification: task control policies

Model-driven engineering setting

Task Specification

Task Planning

Control Specification

CrowdSearcher Meta-Model

CrowdSearcher Datamart for Runtime Control

Example experiment: Professors’ images

Classification of images retrieved from Google

• 16 professors within 2 research groups in DEIB (DB and AI groups)

• The top 50 images returned by the Google Image API for each query

• Each microtask consisted of classifying 5 images regarding a professor

• Agreement of multiple performers checked on the image

• Randomization of the image order

Experiment objectives

Validating impact of model-driven change of:• Crowdsourcing strategies (majority, agreement)

• Crowd communities

• Control rules (order of invitations, …)

Measures:• Speed of result collection (number of closed objects in time)

• Quality of classification results (precision of responses)

The communities:• the research group of the professor

• the research area containing the group (e.g. Computer Science)

• and the whole department (more than 600 people in different areas)

• Polimi-related social networks

Precision of communities

Control rules: order of invitation

Precision decreases with less expert communities

Outside-in strategy (from generic to expert users) outperforms inside-out strategy (from expert to generic)

Strategies Evaluation: different majorities

Evaluations

• Different strategies and communities impact on quality, cost and time

• Cost of adapting is very low thanks to definition of strategies and rules at design level and model-driven generation of running system

Impact


@marcobrambi

User interaction has been overlooked in software engineering standards

Hence the Interaction Flow Modeling Language (IFML)

Final voting on version 1.0, after 3+ years of work

Standardization

Proposed as a standard in OMG (Object Management Group)

In less than 2 years (a record in OMG!), we obtained approval of the IFML standard (March 2013)

Brambilla, Fraternali. “Model-driven UI Engineering of Web and Mobile Apps with IFML”. Morgan Kauffmann, USA, 2014.

IFML (and formerly WebML)has been exploited by the spinoff WebRatio

Commercial modeler and code generator based on IFML and BPMN

17,000 academic licenses

150+ industrial customers (including Acer, Ikea, Unicredit, General Electrics, …)

US and LA branches

Different time-to-market for research ideas• From 0 (web service modeling) to 4 (BPM) years!

Industrial exploitation

Conclusion: innovation-enabling ecosystem

Research (Research group

at Polimi)

Method, Language

and Platform

Spin-off(WebRatio)

Customers (including EU

projects)

Teaching (Polimi and int.l courses)

innovation

innovation toolsuite

Toolsuite, industrial requirements

innovation

requirementsuse cases

Standard

& other SME Partners

Thanks


@marcobrambi

model driven development and code generation of software systems

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