Abstract
Software development in DevOps practices has become popular with the collaborative intersection between development and operations teams. The notion of DevOps practices drives the software artefacts changes towards continuous integration and continuous delivery pipeline. Subsequently, traceability management is essential to handle frequent changes with rapid software evolution. This study explores the process and approaches to manage traceability ensuring the artefact consistency towards CICD in DevOps practice. We address the key notions in traceability management process including artefact change detection, change impact analysis, consistency management, change propagation and visualization. Consequently, we assess the applicability of existing change impact analysis models in DevOps practice. This study identifies the conceptualization of the traceability management process, explores the state-of-art solutions and suggests possible research directions. This study shows that the lack of support in heterogeneous artefact consistency management with well-defined techniques. Most of the related models are limited with the industry-level applicability in DevOps practice. Accordingly, there is inadequate tool support to manage traceability between heterogeneous artefacts. This study identifies the challenges in managing software artefact consistency and suggests possible research directions that can be applied to manage the traceability in the process of software development in DevOps practice.
Highlights
Software systems perform in a dynamic context, where changes arise due to different factors such as a change in business goals, performance improvements, fault corrections and change of technology
Tracing heterogeneous artefacts corresponding to all the stages of Software Development Life Cycle (SDLC) with Change Impact Analysis (CIA) remains challenging with respect to rapid changes
The influence of the CIA is important in the traceability management process in a DevOps practice as consistency management and change propagation depend on it
Summary
Software systems perform in a dynamic context, where changes arise due to different factors such as a change in business goals, performance improvements, fault corrections and change of technology. It is essential to detect artefact changes and identify their impact. The Change Impact Analysis (CIA) process identifies the affected artefacts by following the trace paths using different techniques such as traceability graphs [5], Information Retrieval (IR) and Machine Learning (ML) [6][7]. It is challenging to address the change ripple effects after the initial impacted endpoint identification, as the changes can propagate continuously. The main components of the traceability management process include trace-link creation, change detection, CIA, consistency management, change propagation and collaboration. This survey paper addresses the traceability management process in DevOps practice.
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