International Workshop on Data Driven Base Decision Making for Software Engineering (DDBDM 2024)

Description

In today's digital computing age, like cloud computing, software organizations gain advantages by providing a cost-effective solution. However, it causes several challenges and open problems for software engineers to handle 80% of semi or unstructured data for an effective software development process. The main cause of the flow of semi-structured or unstructured data is the involvement of huge volume repositories (such as GitHub, StackOverflow, or GitLab) in software development and the continuous integration process. Indeed, the effective use of this data will help the software engineer to make informed decisions about continuous process improvement activities such as requirements gathering, design, coding, experimentation and testing. This workshop aims to provide a meeting point for practitioners and researchers to discuss the theoretical and empirical studies conducted to describe the impact of data-driven approaches and/or decision making to evolve and manage software process activities.

Topics

The list of topics includes, but is not limited to:

• Empirical studies on data-driven approaches and decision making process
• Data-driven process life cycle
• Ways to implement a data-driven approach
• Data-driven based maturity models
• Studies on existing maturity models under the umbrella of the industrial revolution
• Maturity models for the digitalization process
• Data-driven Analytics
• Data-driven based product development process
• Knowledge discovery from unstructured data
• Data-driven approaches for software development life cycle activities such as requirement engineering, designing, testing, and so on
• Impact of Data-driven approaches to prevent bugs and customer loss
• Role of statistical learning approaches for data-driven modeling
• Privacy and security issues of data-driven decision making
• Ethics of data-driven based decision making
• Data-driven approaches for software product quality and maintainability
• Data-driven process models
• Data-driven based decision-making impacts operational and performance goals
• Approaches to plan and validate unstructured data integrity
• Understand how to create current and future state process maps
• Prioritize data gaps for root cause analysis

Submission

Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals, and review process can be found at QRS submission.

Each submission can have a maximum of ten pages. It should include a title, the name and affiliation of each author, a 300-word abstract, and up to 6 keywords. Shorter version papers (up to six pages) are also allowed.

All papers must conform to the QRS conference proceedings format (PDF | Word DOCX | Latex) and Submission Guideline set in advance by QRS 2024. At least one of the authors of each accepted paper is required to pay the full registration fee and present the paper at the workshop. Submissions must be in PDF format and uploaded to the conference submission site. Arrangements are being made to publish extended version of top-quality papers in selected SCI journals.

Target Audience

The target group for the proposed workshop will be academia and industry. On the academic side, relevant students and professors can join the workshop session, while from the software industry's point of view, all relevant stakeholders could participate.

Program Chairs

Shahid Hussain

Penn State University, USA

Arif Ali Khan

University of Oulu, Finland

Saif Ur Rahman Khan

COMSATS University, Islamabad, Pakistan

Muhammad Abdul Basit Ur Rahim

California State University Long Beach, USA

Program Committee

Previous DDBDM

• DDBDM 2023 - Chiang Mai (in conjunction with QRS 2023)
• DDBDM 2022 - Guangzhou (in conjunction with QRS 2022)