In software engineering, Configuration Management (CM) refers to the systematic process of identifying, organising, controlling, and tracking all changes made to a software system throughout its lifecycle. It ensures that:
According to ISO/IEC/IEEE 828:2012, CM is defined as: “A discipline applying technical and administrative direction and surveillance to identify and document the functional and physical characteristics of a configuration item, control changes to those characteristics, and record and report change processing and implementation status.”
In other words, Configuration Management keeps the software stable while it evolves. Configuration management exists to:
To understand CM, several foundational terms must be defined.
Configuration Item (CI) A Configuration Item is any component of the system that is subject to configuration control. Examples include:
Each CI is uniquely identified, versioned, and tracked over time [3].
Baseline A baseline is a formally approved version of one or more configuration items that serves as a reference point. Once established, any changes to the baseline must follow a defined change control process. Types of baselines:
Baselines create stability checkpoints in the lifecycle [4].
Version Control Version control systems (VCS), such as Git, Mercurial, or Subversion, track and manage modifications to source code and other files. They enable:
Version control forms the technical backbone of configuration management.
Change Management Change management defines how modifications are proposed, evaluated, approved, and implemented. Typical steps:
This structured approach ensures accountability and quality control [5].
Configuration Audit A configuration audit verifies that the configuration items and documentation:
Two common types:
Audits maintain integrity and compliance, especially in defence and aerospace projects [6].
Even though CM brings structure and order, it faces numerous practical challenges, particularly in distributed and complex systems.
Complexity and Scale Modern systems can contain millions of lines of code, hundreds of dependencies, and multiple configurations for different platforms. Managing all these variations manually is infeasible. Example: An autonomous vehicle might include distinct configurations for:
Solution: Automated configuration management with metadata-driven tools (e.g., Ansible, Puppet, Kubernetes Helm).
Multiple Development Streams In large projects, teams work on multiple branches or versions simultaneously (e.g., development, testing, release). This increases the risk of:
Solution:
Hardware–Software Interdependencies In embedded or cyber-physical systems, configurations depend on hardware variants (processors, sensors, memory). Maintaining alignment between software builds and hardware specifications is difficult. Mitigation:
Frequent Updates and Continuous Delivery In the DevOps era, software may be updated multiple times per day across thousands of devices. Each update must maintain consistency and rollback capability. Challenge:
Solution:
Data and Configuration Drift Configuration drift occurs when the system’s actual state deviates from its documented configuration — common in dynamic, cloud-based systems. Causes:
Prevention:
Regulatory and Compliance Demands In domains like aerospace, medical, and automotive, configuration management is a compliance requirement under standards such as ISO/IEC/IEEE 12207, ISO 26262 or IEC 61508 Challenge:
Solution:
Human and Organisational Factors The most difficult aspect of CM is often cultural, not technical. Teams may resist documentation or formal change control due to perceived bureaucracy. As a result:
Solution: