Availability analysis of software architecture decomposition alternatives for local recovery

Hasan Sözer, Mariëlle Stoelinga, Hichem Boudali, Mehmet Aksit

    Research output: Contribution to journalArticleAcademicpeer-review

    3 Citations (Scopus)

    Abstract

    We present an efficient and easy-to-use methodology to predict—at design time—the availability of systems that support local recovery. Our analysis techniques work at the architectural level, where the software designer simply inputs the software modules’ decomposition annotated with failure and repair rates. From this decomposition, we automatically generate an analytical model (a continuous-time Markov chain), from which an availability measure is then computed, in a completely automated way. A crucial step is the use of intermediate models in the input/output interactive Markov chain formalism, which makes our techniques efficient, mathematically rigorous, and easy to adapt. In particular, we use aggressive minimization techniques to keep the size of the generated state spaces small. We have applied our methodology on a realistic case study, namely the MPlayer open-source software. We have investigated four different decomposition alternatives and compared our analytical results with the measured availability on a running MPlayer. We found that our predicted results closely match the measured ones .
    Original languageEnglish
    Pages (from-to)553-579
    Number of pages27
    JournalSoftware quality journal
    Volume25
    Issue number2
    DOIs
    Publication statusPublished - 2017

    Fingerprint

    Software architecture
    Availability
    Decomposition
    Recovery
    Markov processes
    Analytical models
    Repair

    Cite this

    @article{0c7713ed229a49269a143c5f15f586f6,
    title = "Availability analysis of software architecture decomposition alternatives for local recovery",
    abstract = "We present an efficient and easy-to-use methodology to predict—at design time—the availability of systems that support local recovery. Our analysis techniques work at the architectural level, where the software designer simply inputs the software modules’ decomposition annotated with failure and repair rates. From this decomposition, we automatically generate an analytical model (a continuous-time Markov chain), from which an availability measure is then computed, in a completely automated way. A crucial step is the use of intermediate models in the input/output interactive Markov chain formalism, which makes our techniques efficient, mathematically rigorous, and easy to adapt. In particular, we use aggressive minimization techniques to keep the size of the generated state spaces small. We have applied our methodology on a realistic case study, namely the MPlayer open-source software. We have investigated four different decomposition alternatives and compared our analytical results with the measured availability on a running MPlayer. We found that our predicted results closely match the measured ones .",
    author = "Hasan S{\"o}zer and Mari{\"e}lle Stoelinga and Hichem Boudali and Mehmet Aksit",
    year = "2017",
    doi = "10.1007/s11219-016-9315-9",
    language = "English",
    volume = "25",
    pages = "553--579",
    journal = "Software quality journal",
    issn = "0963-9314",
    publisher = "Springer",
    number = "2",

    }

    Availability analysis of software architecture decomposition alternatives for local recovery. / Sözer, Hasan; Stoelinga, Mariëlle; Boudali, Hichem; Aksit, Mehmet.

    In: Software quality journal, Vol. 25, No. 2, 2017, p. 553-579.

    Research output: Contribution to journalArticleAcademicpeer-review

    TY - JOUR

    T1 - Availability analysis of software architecture decomposition alternatives for local recovery

    AU - Sözer, Hasan

    AU - Stoelinga, Mariëlle

    AU - Boudali, Hichem

    AU - Aksit, Mehmet

    PY - 2017

    Y1 - 2017

    N2 - We present an efficient and easy-to-use methodology to predict—at design time—the availability of systems that support local recovery. Our analysis techniques work at the architectural level, where the software designer simply inputs the software modules’ decomposition annotated with failure and repair rates. From this decomposition, we automatically generate an analytical model (a continuous-time Markov chain), from which an availability measure is then computed, in a completely automated way. A crucial step is the use of intermediate models in the input/output interactive Markov chain formalism, which makes our techniques efficient, mathematically rigorous, and easy to adapt. In particular, we use aggressive minimization techniques to keep the size of the generated state spaces small. We have applied our methodology on a realistic case study, namely the MPlayer open-source software. We have investigated four different decomposition alternatives and compared our analytical results with the measured availability on a running MPlayer. We found that our predicted results closely match the measured ones .

    AB - We present an efficient and easy-to-use methodology to predict—at design time—the availability of systems that support local recovery. Our analysis techniques work at the architectural level, where the software designer simply inputs the software modules’ decomposition annotated with failure and repair rates. From this decomposition, we automatically generate an analytical model (a continuous-time Markov chain), from which an availability measure is then computed, in a completely automated way. A crucial step is the use of intermediate models in the input/output interactive Markov chain formalism, which makes our techniques efficient, mathematically rigorous, and easy to adapt. In particular, we use aggressive minimization techniques to keep the size of the generated state spaces small. We have applied our methodology on a realistic case study, namely the MPlayer open-source software. We have investigated four different decomposition alternatives and compared our analytical results with the measured availability on a running MPlayer. We found that our predicted results closely match the measured ones .

    U2 - 10.1007/s11219-016-9315-9

    DO - 10.1007/s11219-016-9315-9

    M3 - Article

    VL - 25

    SP - 553

    EP - 579

    JO - Software quality journal

    JF - Software quality journal

    SN - 0963-9314

    IS - 2

    ER -