TY - BOOK
T1 - Fifth International Workshop on Variability and Evolution of Software-Intensive Systems (VariVolution 2022)
A2 - Felfernig, Alexander
A2 - Fuentes, Lidia
A2 - Cleland-Huang, Jane
A2 - Guez Assuncao, Wesley Klewerton
A2 - Falkner, Andreas
A2 - Azanza, M.
A2 - Luaces, Miguel Rodriguez
A2 - Bhushan, Megha
A2 - Semini, Laura
A2 - Devroey, Xavier
A2 - Werner, Claudia Maria Lima
A2 - Seidl, Christoph
A2 - Viet-Man, Le
A2 - Horcas, Jose Miguel
PY - 2022/4
Y1 - 2022/4
N2 - Engineering projects involve a variety of artifacts such as requirements, design, or source code. These artifacts, many of which tend to be interdependent, are often manipulated concurrently. To keep artifacts consistent, engineers must continuously consider their work in relation to the work of multiple other engineers. Traditional consistency checking approaches reason efficiently over artifact changes and their consistency implications. However, they do so solely within the boundaries of specific tools and their specific artifacts (e.g., consistency checking between different UML models). This makes it difficult to examine the consistency between different types of artifacts (e.g., consistency checking between UML models and the source code). Global consistency checking can help addressing this problem. However, it usually requires a disruptive and time consuming merging process for artifacts. This article presents a novel, cloud-based approach to global consistency checking in a multi-developer/-tool engineering environment. It allows for global consistency checking across all artifacts that engineers work on concurrently. Moreover, it reasons over artifact changes immediately after the change happened, while keeping the (memory/CPU) cost of consistency checking minimal. The feasibility and scalability of our approach were demonstrated by a prototype implementation and through an empirical validation.
AB - Engineering projects involve a variety of artifacts such as requirements, design, or source code. These artifacts, many of which tend to be interdependent, are often manipulated concurrently. To keep artifacts consistent, engineers must continuously consider their work in relation to the work of multiple other engineers. Traditional consistency checking approaches reason efficiently over artifact changes and their consistency implications. However, they do so solely within the boundaries of specific tools and their specific artifacts (e.g., consistency checking between different UML models). This makes it difficult to examine the consistency between different types of artifacts (e.g., consistency checking between UML models and the source code). Global consistency checking can help addressing this problem. However, it usually requires a disruptive and time consuming merging process for artifacts. This article presents a novel, cloud-based approach to global consistency checking in a multi-developer/-tool engineering environment. It allows for global consistency checking across all artifacts that engineers work on concurrently. Moreover, it reasons over artifact changes immediately after the change happened, while keeping the (memory/CPU) cost of consistency checking minimal. The feasibility and scalability of our approach were demonstrated by a prototype implementation and through an empirical validation.
M3 - Anthology
SN - 9781450396745
VL - 21
T3 - Communications in Computer and Information Science
BT - Fifth International Workshop on Variability and Evolution of Software-Intensive Systems (VariVolution 2022)
PB - Association for Computing Machinery
CY - New York, NY, USA
ER -