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Parallelization of genetic algorithms for software architecture recovery

AUTOMATED software ENGINEERING 2025年第1期32卷 1-24页

作者： Varol, Taha Elyasi, Milad Aktas, T. Huzeyfe Ozener, O. Orsan Sozer, Hasan Ozyegin Univ TR-34794 Istanbul Turkiye

software architecture recovery (SAR) techniques analyze dependencies between software modules and automatically cluster them to achieve high modularity. Many of these approaches employ Genetic Algorithms (GAs) for clustering software modules. A major drawback of these algorithms is their lack of scalability. In this paper, we address this drawback by introducing generic software components that can encapsulate subroutines (operators) of a GA to execute them in parallel. We use these components to implement a novel hybrid GA for SAR that exploits parallelism to find better solutions faster. We compare the effectiveness of parallel algorithms with respect to the sequential counterparts that are previously proposed for SAR. We observe that parallelization enables a greater number of iterations to be performed in the search for high-quality solutions. The increased efficiency achieved through parallel processing allows for faster convergence towards optimal solutions by harnessing the power of multiple processing units in a coordinated manner. The amount of improvement in modularity is above 50%, which particularly increases in the context of large-scale systems. Our algorithm can scale to recover the architecture of a large system, Chromium, which has more than 18,500 modules and 750,000 dependencies among these modules.

关键词： software architecture recovery software module clustering software modularity Genetic algorithms Parallel algorithms

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software architecture recovery of a program family

Software architecture recovery of a program family

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20th International Conference on software Engineering - Forging New Links (ICSE 98)

作者： Eixelsberger, W Ogris, M Gall, H Bellay, B ABB Corp Res Informat Technol & Control Syst Grp N-1361 Billingstad Norway

ISBN: (纸本)0818683686

The concept of software architecture has gained a lot of attention in the last few years and has found its way into the software development process in industry. software architecture recovery focuses on the recovery of architectural information from existing systems. This paper presents a framework for recovering the software architecture of a program family. Based on the available system information architectural properties such as safety or system control are recovered using different reverse engineering methods and tools in combination with architectural descriptions. We describe our architecture recovery process and discuss the recovery of system structure as one example out of the case study. The framework was developed while working on the recovery of the family architecture of a train control system.

关键词： software architecture re-engineering software architecture recovery

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software architecture recovery from Multiple Dependency Models 24

Software Architecture Recovery from Multiple Dependency Mode...

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39th Annual ACM Symposium on Applied Computing (SAC)

作者： Altinisik, Metin Sozer, Hasan Gursun, Gonca Turkcell Technol Istanbul Turkiye Ozyegin Univ Istanbul Turkiye Bosch Ctr Artificial Intelligence Renningen Germany

ISBN: (纸本)9798400702433

software architecture recovery tools cluster software modules based on their inter-dependencies to suggest a gross-level decomposition with high modularity. However, there are usually multiple types of dependencies among software modules, each of which can be captured with a separate dependency model. In this paper, we evaluate the effectiveness of a software architecture recovery approach that utilizes multiple such dependency models. First, we perform clustering based on various models separately. These models reflect different types of dependencies, including call dependencies, evolutionary coupling and dependencies of modules on commonly used database tables. Then, we perform cluster aggregation on the obtained clustering results to propose a packaging structure to the designer. We present an industrial case study on a large-scale legacy system from the telecommunications domain. The highest accuracy is achieved with the aggregation of clustering results obtained based on 3 dependency models. The accuracy in terms of matching between the proposed packaging and the existing one is above 65%. The non-matching results mostly pinpoint architectural anomalies as confirmed by domain experts.

关键词： reverse engineering software architecture recovery software module clustering software modularity cluster aggregation industrial case study

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software architecture recovery with Information Fusion 2023

Software Architecture Recovery with Information Fusion

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31st ACM Joint Meeting of the European software Engineering Conference / Symposium on the Foundations-of-software-Engineering (ESEC/FSE)

作者： Zhang, Yiran Xu, Zhengzi Liu, Chengwei Chen, Hongxu Sun, Jianwen Qiu, Dong Liu, Yang Nanyang Technol Univ Singapore Singapore Huawei Technol Co Ltd Shenzhen Peoples R China

ISBN: (纸本)9798400703270

Understanding the architecture is vital for effectively maintaining and managing large software systems. However, as software systems evolve over time, their architectures inevitably change. To keep up with the change, architects need to track the implementation-level changes and update the architectural documentation accordingly, which is time-consuming and error-prone. Therefore, many automatic architecture recovery techniques have been proposed to ease this process. Despite efforts have been made to improve the accuracy of architecture recovery, existing solutions still suffer from two limitations. First, most of them only use one or two type of information for the recovery, ignoring the potential usefulness of other sources. Second, they tend to use the information in a coarse-grained manner, overlooking important details within it. To address these limitations, we propose SARIF, a fully automated architecture recovery technique, which incorporates three types of comprehensive information, including dependencies, code text and folder structure. SARIF can recover architecture more accurately by thoroughly analyzing the details of each type of information and adaptively fusing them based on their relevance and quality. To evaluate SARIF, we collected six projects with published ground-truth architectures and three open-source projects labeled by our industrial collaborators. We compared SARIF with nine state-of-the-art techniques using three commonly-used architecture similarity metrics and two new metrics. The experimental results show that SARIF is 36.1% more accurate than the best of the previous techniques on average. By providing comprehensive architecture, SARIF can help users understand systems effectively and reduce the manual effort of obtaining ground-truth architectures.

关键词： software architecture recovery software module clustering reverse engineering architecture comparison

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Directory-Based Dependency Processing for software architecture recovery

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IEEE ACCESS 2018年 6卷 52321-52335页

作者： Kong, Xianglong Li, Bixin Wang, Lulu Wu, Wensheng Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Jiangsu Peoples R China Huawei Technol Co Ltd Shenzhen 518129 Peoples R China

Directory structure contains a wealth of software design information;it is used to transfer thoughts of architects to developers. Information extracted from directory paths should play an important role in architecture recovery techniques, but it has been proved that modules or components directly represented by directories are not accurate due to the inconsistency between stages of development and design. To make better use of information extracted from directories, we propose a directory-based dependency processing technique to utilize the information of directories in the process of structure-based architecture recovery. The technique groups the selected inter-coupling files and intra-coupling files in the same directory into a submodule and generates submodule-level dependency graph based on file-level dependency graph. We apply both manual and automatic architecture recovery techniques on submodule-level dependency graph, and the results show that our technique can greatly improve the efficiency and effectiveness of manual and automatic architecture recovery techniques;the technique can also make other structure-based recovery techniques easily scalable to large-sized projects.

关键词： software architecture recovery dependency graph directory path

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Genetic algorithms and heuristics hybridized for software architecture recovery

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AUTOMATED software ENGINEERING 2023年第2期30卷 1-24页

作者： Elyasi, Milad Simitcioglu, M. Esad Saydemir, Abdullah Ekici, Ali Ozener, O. Orsan Sozer, Hasan Ozyegin Univ Comp Sci Dept TR-34794 Istanbul Turkiye Ozyegin Univ Ind Engn Dept TR-34794 Istanbul Turkiye CNRS IMT Atlantique LS2N 4 Rue Alfred Kastler F-44300 Nantes France

Large scale software systems must be decomposed into modular units to reduce maintenance efforts. software architecture recovery (SAR) approaches have been introduced to analyze dependencies among software modules and automatically cluster them to achieve high modularity. These approaches employ various types of algorithms for clustering software modules. In this paper, we discuss design decisions and variations in existing genetic algorithms devised for SAR. We present a novel hybrid genetic algorithm that introduces three major differences with respect to these algorithms. First, it employs a greedy heuristic algorithm to automatically determine the number of clusters and enrich the initial population that is generated randomly. Second, it uses a different solution representation that facilitates an arithmetic crossover operator. Third, it is hybridized with a heuristic that improves solutions in each iteration. We present an empirical evaluation with seven real systems as experimental objects. We compare the effectiveness of our algorithm with respect to a baseline and state-of-the-art hybrid genetic algorithms. Our algorithm outperforms others in maximizing the modularity of the obtained clusters.

关键词： Reverse engineering software architecture recovery software module clustering software modularity Genetic algorithms

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An automated approach for noise identification to assist software architecture recovery techniques

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JOURNAL OF SYSTEMS AND software 2015年 107卷 142-157页

作者： Constantinou, Eleni Kakarontzas, George Stamelos, Ioannis Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece Technol Educ Inst Thessaly Comp Sci & Engn Dept Larisa 41110 Greece

software systems' concrete architecture often drifts from the intended architecture throughout their evolution. Program comprehension activities, like software architecture recovery, become very demanding, especially for large and complex systems due to the existence of noise, which is created by omnipresent and utility classes that obscure the system structure. Omnipresent classes represent crosscutting concerns, utilities or elementary domain concepts. The identification and filtering of noise is a necessary preprocessing step before attempting program comprehension techniques, especially for undocumented systems. In this paper, we propose an automated methodology for noise identification. Our methodology is based on the notion that noisy classes are widely used in a system, directly or indirectly. We combine classes' usage significance with their participation in the system's subgraphs, in order to identify the classes that are persistently used. Usage significance is measured according to Component Rank, a well-established metric in the literature, which ranks software artifacts according to their usage significance. The experimental results show that the proposed methodology successfully captures classes that produce noise and improves the results of existing algorithms for software systems' architectural decomposition. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Noise identification Omnipresent classes software architecture recovery

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General methods for software architecture recovery: a potential approach and its evaluation

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EMPIRICAL software ENGINEERING 2018年第3期23卷 1457-1489页

作者： Tamburri, Damian A. Kazman, Rick Politecn Milan Milan Italy Univ Hawaii Honolulu HI 96822 USA Carnegie Mellon Univ Software Engn Inst Pittsburgh PA 15213 USA

software architecture is a critical artefact in the software lifecycle. It is a system blueprint for construction, it aids in planning teaming and division of work, and it aids in reasoning about system properties. But architecture documentation is seldom created and, even when it is initially created, it is seldom maintained. For these reasons organisations often feel the need to recover legacy architectures, for example, as part of planning for evolution or cloud migration. But there is no existing general architecture recovery approach nor tool that can be applied to any type of system, under any condition. We will show that one way of achieving such generality is to apply systematic code inspection following a Grounded Theory (GT) approach. Though relatively costly and human-intensive, a GT-based approach has several merits, for example: (a) it is general by design;(b) it can be partially automated;(c) it yields evidence-based results rooted of the system being examined. This article presents one theoretical formulation of a general architecture recovery method-called REM-and reports on the evaluation of REM in the context of a large architecture recovery campaign performed for the European Space Agency. Our results illustrate some intriguing properties and opportunities of GT-based architecture recovery approaches and point out lessons learned and venues for further research.

关键词： software architecture recovery Ground-truth software architectures Grounded theory QVT OCL UML profiles Model-driven engineering Model-driven architecture European space agency Industrial experience report

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Adaptive Weighting of Structural Dependency and Textual Similarity in software architecture recovery

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2016年第3期E99D卷 756-759页

作者： Um, Jae-Chul Lee, Ki-Seong Lee, Chan-Gun Chung Ang Univ Sch Comp Sci & Engn Seoul 156756 South Korea

software architecture recovery techniques are often adopted to derive a module view of software from its source code in case software architecture documents are unavailable or outdated. The module view is one of the most important perspectives of software architecture. In this paper, we propose a novel approach to derive a module view by adaptively integrating structural dependency and textual similarity. Our approach utilizes Newman modularity and Shannon information entropy to determine the appropriate weights of the dependencies during the integration. We apply our approach to various open-source projects and show the experimental results validating the effectiveness of the approach.

关键词： software architecture recovery module view dependency Newman modularity information entropy

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Evaluating the Effectiveness of Multi-level Greedy Modularity Clustering for software architecture recovery 13th

Evaluating the Effectiveness of Multi-level Greedy Modularit...

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13th European Conference on software architecture Engineering (ECSA)

作者： Sozer, Hasan Ozyegin Univ Istanbul Turkey

ISBN: (纸本)9783030299835;9783030299828

software architecture recovery approaches mainly analyze various types of dependencies among software modules to group them and reason about the high-level structural decomposition of a system. These approaches employ a variety of clustering techniques. In this paper, we present an empirical evaluation of a modularity clustering technique used for software architecture recovery. We use five open source projects as subject systems for which the ground-truth architectures were known. This dataset was previously prepared and used in an empirical study for evaluating four state-of-the-art architecture recovery approaches and their variants as well as two baseline clustering algorithms. We used the same dataset for an evaluation of multi-level greedy modularity clustering. Results showed that MGMC outperforms all the other SAR approaches in terms of accuracy and modularization quality for most of the studied systems. In addition, it scales better to very large systems for which it runs orders-of-magnitude faster than all the other algorithms.

关键词： software architecture recovery software architecture reconstruction Reverse engineering Modularity clustering Empirical evaluation

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