endorsedCompleted

UML XML-to-AsciiDoc Extraction Script for Automotive Standardization Org

Services Covered:

Custom Software Development

Industry

Automotive

Duration

1 month

Budget

Confidential

Start Date

1 January 2023

Team Size

1-5 Employees

Engagement Model

Nearshore

Project Capability Score (PCS)

81/100

Strong

Project Capability Score (PCS) estimates how capable DATAFOREST is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

Munich, Germany

Project Summary

An automotive standardization organization hired DATAFOREST to extend an existing Python script to extract UML data from XML (XMI) into multiple AsciiDoc files and store them in a folder structure. DATAFOREST extended the prior May 2021 script, delivered several iterations, incorporated bug fixes and change requests on time, and maintained efficient communication throughout the engagement. The client praised the team's professionalism and high-quality deliverables.

Key Challenges

Script development for UML data extraction

Project Deliverables

Python script to extract data from XML into AsciiDoc
AsciiDoc (.adoc) files generated from UML XML
Organized folder structure for output files
Extension of an existing extraction script (based on May 2021 script)

Project Solution

DATAFOREST extended an existing Python script to extract data from an exported UML XML (XMI 1.1) file into multiple AsciiDoc (.adoc) text files and save them in a structured folder layout. The work adapted a prior script (from May 2021), handled the specifics of Enterprise Architect XMI export, and included iterative bug fixes and requested changes during the engagement.

Project Outcome

Several deliverables were produced during project runtime
Bug fixes and requested changes were incorporated on time
Project management was easy and fast to communicate with
Client highlighted professionalism, strong communication, and high-quality deliverables

Platforms

Desktop

Tech Stack

Python
XML

Client Endorsement

Overall Review Rating

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“The client was happy with DATAFOREST's high-quality deliverables. The team incorporated the changes requested, fixed bugs on time, and communicated efficiently, ensuring a good project management experience. Moreover, their professionalism contributed to the project's success.”
Anonymous
Technology Manager
Date: 03/13/2023