Runtime Reasoning of Requirements for Self-Adaptive Systems using AI Planning Techniques

被引:0
|
作者
Hassan, Zara [1 ]
Qureshi, Nauman [2 ]
Hashmi, Muhammad Adnan [1 ]
Ali, Arshad [1 ]
机构
[1] Univ Lahore, Dept CS & IT, Lahore, Pakistan
[2] Natl Univ Sci & Technol, Sch Elect Engn & Comp Sci, Islamabad, Pakistan
关键词
Self-Adaptive Systems (SAS); reasoning; requirement engineering; AI planning; CARE framework; runtime reasoning of requirements;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Over the years, the domain of Self-Adaptive Systems (SAS) has gained significant importance in software engineering community. Such SAS must ensure high customizability and at the same time effective reasoning to meet their objectives by meeting end-user goals more effectively and efficiently. In this context, techniques related to Automated Planning have acquired substantial precedence owing to their adaptability to diverse scenarios based upon their enhanced knowledge extraction from available Knowledge Base. These AI planning techniques help in supporting self-adaptation mechanism of SAS. We have investigated these techniques to perform runtime reasoning of SAS requirements. This paper proposes an architecture for implementing the reasoning component of previously proposed Continuous Adaptive Requirement Engineering (CARE) framework. The proposed architecture has been experimentally verified by implementation of a prototype application using JSHOP2 (Java implementation of SHOP2, an HTN Planner).
引用
收藏
页码:129 / 137
页数:9
相关论文
共 50 条
  • [31] Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap
    Li, Jialong
    Zhang, Mingyue
    Li, Nianyu
    Weyns, Danny
    Jin, Zhi
    Tei, Kenji
    [J]. ACM Transactions on Autonomous and Adaptive Systems, 2024, 19 (03)
  • [32] An Experimental Evaluation on Runtime Verification of Self-adaptive Systems in the Presence of Uncertain Transition Probabilities
    Ogawa, Kento
    Nakagawa, Hiroyuki
    Tsuchiya, Tatsuhiro
    [J]. SOFTWARE ENGINEERING AND FORMAL METHODS (SEFM 2015), 2015, 9509 : 253 - 265
  • [33] Model Checking Goal-Oriented Requirements for Self-Adaptive Systems
    Abeywickrama, Dhaminda B.
    Zambonelli, Franco
    [J]. 2012 IEEE 19TH INTERNATIONAL CONFERENCE AND WORKSHOPS ON ENGINEERING OF COMPUTER BASED SYSTEMS (ECBS), 2012, : 33 - 42
  • [34] Requirements for modeling and simulation of self-adaptive systems: A hierarchical and modular approach
    Barros, FJ
    [J]. SIXTEENTH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2005, : 186 - 190
  • [35] The Generation and Evolution of Adaptation Rules in Requirements Driven Self-adaptive Systems
    Zhao, Tianqi
    [J]. 2016 IEEE 24TH INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE (RE), 2016, : 456 - 461
  • [36] AI PLANNING - SYSTEMS AND TECHNIQUES
    HENDLER, J
    TATE, A
    DRUMMOND, M
    [J]. AI MAGAZINE, 1990, 11 (02) : 61 - 77
  • [37] Analysing and modelling runtime architectural stability for self-adaptive software
    Salama, Maria
    Bahsoon, Rami
    [J]. JOURNAL OF SYSTEMS AND SOFTWARE, 2017, 133 : 95 - 112
  • [38] Runtime Verification of Multi-Agent Self-Adaptive System
    Ye, Xingyu
    Liu, Wei
    Wang, Ning
    [J]. PROCEEDINGS OF THE 2021 IEEE 24TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2021, : 12 - 17
  • [39] Proteus: Language and Runtime Support for Self-Adaptive Software Development
    Barati, Saeid
    Bartha, Ferenc A.
    Biswas, Swarnendu
    Cartwright, Robert
    Duracz, Adam
    Fussell, Donald S.
    Hoffmann, Henry
    Imes, Connor
    Miller, Jason E.
    Mishra, Nikita
    Arvind
    Dung Nguyen
    Palem, Krishna, V
    Pei, Yan
    Pingali, Keshav
    Sai, Ryuichi
    Wright, Andrew
    Yang, Yao-Hsiang
    Zhang, Sizhuo
    [J]. IEEE SOFTWARE, 2019, 36 (02) : 73 - 82
  • [40] Temporal pattern specifications for self-adaptive requirements
    Yahiaoui, Ayoub
    Bendjenna, Hakim
    Roose, Philippe
    Chung, Lawrence
    Amroune, Mohamed
    [J]. Recent Patents on Computer Science, 2019, 12 (01) : 58 - 68