TY - GEN
T1 - Optimizing IaC Configurations
T2 - 6th International Conference on Computational Intelligence and Intelligent Systems, CIIS 2023
AU - Osaba, Eneko
AU - Benguria, Gorka
AU - Lobo, Jesus L.
AU - Diaz-De-Arcaya, Josu
AU - Alonso, Juncal
AU - Etxaniz, Iñaki
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/11/25
Y1 - 2023/11/25
N2 - In the last years, one of the fields of artificial intelligence that has been investigated the most is nature-inspired computing. The research done on this specific topic showcases the interest that sparks in researchers and practitioners, who put their focus on this paradigm because of the adaptability and ability of nature-inspired algorithms to reach high-quality outcomes on a wide range of problems. In fact, this kind of methods has been successfully applied to solve real-world problems in heterogeneous fields such as medicine, transportation, industry, or software engineering. Our main objective with this paper is to describe a tool based on nature-inspired computing for solving a specific software engineering problem. The problem faced consists of optimizing Infrastructure as Code deployment configurations. For this reason, the name of the system is IaC Optimizer Platform. A prototypical version of the IOP was described in previous works, in which the functionality of this platform was introduced. With this paper, we take a step forward by describing the final release of the IOP, highlighting its main contribution regarding the current state-of-the-art, and justifying the decisions made on its implementation. Also, we contextualize the IOP within the complete platform in which it is embedded, describing how a user can benefit from its use. To do that, we also present and solve a real-world use case.
AB - In the last years, one of the fields of artificial intelligence that has been investigated the most is nature-inspired computing. The research done on this specific topic showcases the interest that sparks in researchers and practitioners, who put their focus on this paradigm because of the adaptability and ability of nature-inspired algorithms to reach high-quality outcomes on a wide range of problems. In fact, this kind of methods has been successfully applied to solve real-world problems in heterogeneous fields such as medicine, transportation, industry, or software engineering. Our main objective with this paper is to describe a tool based on nature-inspired computing for solving a specific software engineering problem. The problem faced consists of optimizing Infrastructure as Code deployment configurations. For this reason, the name of the system is IaC Optimizer Platform. A prototypical version of the IOP was described in previous works, in which the functionality of this platform was introduced. With this paper, we take a step forward by describing the final release of the IOP, highlighting its main contribution regarding the current state-of-the-art, and justifying the decisions made on its implementation. Also, we contextualize the IOP within the complete platform in which it is embedded, describing how a user can benefit from its use. To do that, we also present and solve a real-world use case.
KW - Combinatorial Optimization
KW - Multi-objective Optimization
KW - Nature-inspired Computing
KW - PIACERE
UR - http://www.scopus.com/inward/record.url?scp=85187557559&partnerID=8YFLogxK
U2 - 10.1145/3638209.3638223
DO - 10.1145/3638209.3638223
M3 - Conference contribution
AN - SCOPUS:85187557559
T3 - ACM International Conference Proceeding Series
SP - 85
EP - 90
BT - CIIS 2023 - 2023 The 6th International Conference on Computational Intelligence and Intelligent Systems
PB - Association for Computing Machinery
Y2 - 25 November 2023 through 27 November 2023
ER -