Using simulated annealing for producing software architectures

Räihä, Outi; Mäkinen, Erkki; Poranen, Timo

doi:10.1145/1570256.1570289

Cited by 7 publications

(4 citation statements)

References 13 publications

(14 reference statements)

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“…Performance (84) ADL(4) [145], [160], [161], [170], ANY(2) [133], [153], CUSTOMAM(5) [90], [152], [196]- [198], OPTIMPL(3) ALLOCATION(20) [61], [83], [88], [121]- [123], [133], [153], [155], [160], [161], [164], [175]- [178], [186], [187], [192], [214], CLUSTERING(3) [67], [122], [214], COMPONENT SELECTION(12) [7], [18], [96], [97], [147], [149], [160], [161], [177], [178], [182], [232], HARDWARE PARAMETERS(2) [160], [161], HARDWARE REPLICATION(29) [31], [51]- [57], …”

Section: Qa Architecture Representation Quality Evaluation Degrees Ofmentioning

confidence: 99%

“…Performance(84) EXACT PROBLEM-SPECIFIC(3) [1], [112], [126], EXACT STANDARD(14) [12]- [15], [42]- [44], [69], [117], [169], [174], [218], [236], [241], GENERAL(1) [153], METAHEURIS-TIC(45) [2], [3], [23], [29], [32], [35], [38]- [40], [45], [46], [66], [73], [77], [83], [84], [88], [114], [122]- [124], [130], [133], [141], [143], [145], [160], [161], [170], [175]- [177], [188], [189], [196]- [198], [200], [220], …”

Section: Qa Optimization Strategy Type Constraint Handlingmentioning

confidence: 99%

See 1 more Smart Citation

Software Architecture Optimization Methods: A Systematic Literature Review

Aleti

Bühnová

Grunske

et al. 2013

IIEEE Trans. Software Eng.

244

146

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Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Abstract-Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.

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Section: Qa Architecture Representation Quality Evaluation Degrees Ofmentioning

confidence: 99%

Section: Qa Optimization Strategy Type Constraint Handlingmentioning

confidence: 99%

Software Architecture Optimization Methods: A Systematic Literature Review

Aleti

Bühnová

Grunske

et al. 2013

IIEEE Trans. Software Eng.

244

146

View full text Add to dashboard Cite

show abstract

“…A longer annealing was also experimented with by setting the starting temperature to 10 000 (cooling ratio 0.05), and a faster annealing was tested by setting the cooling ratio to 0.15 (starting temperature 7500). A lower starting temperature had also been tested previously with no obvious benefits [31]. The values were selected based on trial-and-error experiments.…”

Section: Using Sa Firstmentioning

confidence: 99%

Simulated Annealing for Aiding Genetic Algorithm in Software Architecture Synthesis

Sievi-Korte¹,

Mäkinen²,

Poranen³

2013

Acta Cybern

Self Cite

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Automatic synthesis of software architecture has already been shown to be feasible with genetic algorithms. A natural problem is to augment -if not replace -genetic algorithms with some other search methods in the process of searching good architectures. The present paper studies the possibilities of using simulated annealing for synthesizing software architecture. We start from functional requirements which form a null architecture and consider three quality attributes, modifiability, efficiency and complexity. Synthesis is performed by adding design patterns and architecture styles; the end result being a software architecture which corresponds to the quality attributes. It is concluded that simulated annealing as such does not produce good architectures, but it is useful for speeding up the evolution process by quickly fine-tuning a base solution achieved with a genetic algorithm.

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“…However, tests have shown [13] that the fitness function based on traditional quality metrics does not fully satisfy the needs in the search process of a software architecture. To this end, the present paper aims at a more accurate fitness function, which is tailored for the design process at hand.…”

Section: Related Workmentioning

confidence: 99%

Scenario-Based Genetic Synthesis of Software Architecture

Räihä

Koskimies

Mäkinen

2009

2009 Fourth International Conference on Software Engineering Advances

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Software architecture design can be regarded as finding an optimal combination of known general solutions and architectural knowledge with respect to given requirements. Based on previous work on synthesizing software architecture using genetic algorithms, we propose a refined fitness function for assessing software architecture in genetic synthesis, taking into account the specific anticipated needs of the software system under design. Inspired by real life architecture evaluation methods, the refined fitness function employs scenarios, specific situations possibly occurring during the lifetime of the system and requiring certain modifiability properties of the system. Empirical studies based on two example systems suggest that using this kind of fitness function significantly improves the quality of the resulting architecture.

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Using simulated annealing for producing software architectures

Cited by 7 publications

References 13 publications

Software Architecture Optimization Methods: A Systematic Literature Review

Software Architecture Optimization Methods: A Systematic Literature Review

Simulated Annealing for Aiding Genetic Algorithm in Software Architecture Synthesis

Scenario-Based Genetic Synthesis of Software Architecture

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