Skip to content
#software testing Open access

Uncertainty-Permeable Analytics for the Software Release Planning Problem

Sep 2026 · Mathematics · 0 citations

TL;DR

A novel fuzzy model is presented that accounts for the penetration and exploitation of uncertainty related to the effort required to implement each requirement, a Consonant Family of Plans, which allows for the determination of confidence measures regarding the release in which each requirement will be implemented.

Abstract

Software development processes present a number of challenges due to the impact of uncertainty. In this context, the problem of deciding which requirements will be implemented in the next k releases is known as the Software Release Planning Problem. This article presents a novel fuzzy model for Software Release Planning that accounts for the penetration and exploitation of uncertainty related to the effort required to implement each requirement. The solution is a Consonant Family of Plans, which allows for the determination of confidence measures regarding the release in which each requirement will be implemented. The model is tested on an example instance, and a “what-if” analysis is conducted, demonstrating how the solution responds to updates in parameters and the arrival of new data on work completed. This information constitutes a flexible prescriptive analysis that supports decision-making, and the paper shows how the solution responds as the context changes. Also, an initial computational study is carried out. The results show that the solution’s usefulness is maintained over time as new information becomes available, which poses new challenges and encourages further research.

Read PDF

Similar papers

#artificial intelligence Preprint Sep 2026

Planning and Scheduling Business Processes under Control-Flow Uncertainty: Extended Version

A decomposed approach with two stages, a planning stage that minimizes the expected number of superfluous activities subject to a feasibility constraint, and a scheduling stage that minimizes the makespan over the planned activities; and an integrated approach that combines planning and scheduling into a single formula...

Michel Kunkler, Stefanie Rinderle-Ma · 0 citations
Book Open access Oct 2026

Uncertainty-aware Design Decisions through Probabilistic Uncertainty Quantification and Consistent Merging

When developing complex, software-intensive or cyber-physical systems, uncertainty must be managed during all stages. Especially if made explicit, it can significantly affect the design decisions of various stakeholders. A necessary requirement for determining the effect of uncertainty on a system and deciding whether...

Nathan Hagel, Johannes Mäkelburg, Alireza Maleki et al. · 1 citation
Conference

A Mixed-Integer Optimization Tool for System-Level Proactive Obsolescence Risk Management

Diminishing manufacturing sources and material shortages (DMSMS) pose a significant risk to the reliability and maintainability of many modern complex systems due to part obsolescence. Part obsolescence increases the risk of system failure or downtime, which is often not only undesirable, but non-negotiable. As such, i...

Chad Uhles, Hugh Medal · 0 citations
Conference Open access 2026

AI-enabled hybrid project management framework for software operations excellence

A conceptual framework that connects traditional project governance, agile execution and artificial intelligence (AI)-supported decision-making within one operating model is developed and argues that AI creates value only when its outputs are connected to an existing decision process at the point where action is still...

Sanjay Kumar, S. R. · 0 citations
2026

System: Case of a Mining-Based Service Provider

The study investigates the implementation of an Enterprise Resource Planning (ERP) system in a case study organisation to reduce system complexity and achieve improved operational efficiency. It was established that the operational system for the case study firm had become complex to manage using manual systems. The re...

P. Matarauka, I. Madanhire, Tafadzwa Gotora · 0 citations

Related blog posts

Microsoft Research Blog Oct 30, 2026

From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence

Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.

Microsoft Research Blog Oct 29, 2026

Microsoft Research Focus – Edition #97

Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.