Complex Networks Analysis for Software Architecture: a Case Study on Hibernate (P)

Falci, Daniel Henrique Mourão; Rodrigues, Bruno Rafael de Oliveira; Gomes, Orlando; Parreiras, Fernando Silva

doi:10.18293/seke2019-232

Cited by 2 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a more recent study, topological properties of the call graph of the Hibernate software, written in Java programming language, were analyzed [8]. Similar to the previous studies, the analysis revealed that the network showed scale-free and small-world properties.…”

Section: Related Workmentioning

confidence: 58%

Analysis of function-call graphs of open-source software systems using complex network analysis

Tunalı¹,

Tuysuz²

2020

Pamukkale J Eng Sci

View full text Add to dashboard Cite

ÖzSoftware systems are usually designed in a modular and hierarchical fashion, where functional responsibility of a system is decomposed into multiple functional software elements optimally such as subsystems, modules, packages, classes, methods, and functions. These elements are coupled with each other with some kind of dependency relationships to some degree, and their interactions naturally form a graph or network structure. In this study, we generated the static function-call graphs of several open-source software systems, where functions were the most basic type of interacting elements calling each other. Then, we analyzed the call graphs both visually and topologically using the techniques of complex network analysis. We found the call graphs to reveal scale-free and small-world network properties similar to the findings of the previous studies. In addition, we identified the most central and important functions in each call-graph using several centrality measures. We also performed community analysis and found that the call graphs exhibited a tendency to form communities. Finally, we showed that analysis of static function-call graphs of software systems through complex network analysis has the potential to reveal useful information about them.Yazılım sistemleri genellikle sistemin işlevsel sorumluluğunun optimal bir şekilde altsistemler, modüller, paketler, sınıflar, metodlar, ve fonksiyonlar gibi çok sayıda işlevsel yazılım elemanına ayrıştırıldığı, modüler ve hiyerarşik bir biçimde tasarlanırlar. Bu elemanlar birbirleriyle çeşitli ilişki türleri ile bağlıdırlar ve bunların etkileşimleri doğal olarak bir graf veya ağ yapısı oluşturur. Bu çalışmada, etkileşim halindeki en temel eleman türü olarak birbirini çağıran fonksiyonları dikkate alarak, çeşitli açık-kaynak yazılım sistemlerinin statik fonksiyon-çağırma graflarını oluşturduk. Ardından, karmaşık ağ analizi teknikleri kullanarak, çağırma graflarını hem görsel hem de topolojik olarak analiz ettik. Daha önceki çalışmaların bulgularına benzer olarak, grafların ölçekten-bağımsız ve küçük-dünya ağı özellikleri sergilediklerini gördük. Ek olarak, çeşitli merkezîlik ölçütleri kullanarak, her bir çağırma grafındaki en merkezi ve önemli fonksiyonları tespit ettik. Ayrıca, topluluk analizi gerçekleştirdik ve çağırma graflarının topluluk oluşturma eğilimi gösterdiğini bulduk. Son olarak, yazılım sistemlerinin statik fonksiyon-çağırma graflarının karmaşık ağ analizi yoluyla analizinin, sistemlerle ilgili yararlı bilgiler sağlama potansiyeli olduğunu gösterdik.

show abstract

Section: Related Workmentioning

confidence: 58%

Analysis of function-call graphs of open-source software systems using complex network analysis

Tunalı¹,

Tuysuz²

2020

Pamukkale J Eng Sci

View full text Add to dashboard Cite

show abstract

“…• Software comprehension, e.g., learning code structure by interactive code visualization and browsing, applying data analysis to find the most important code elements, answering reachability questions [12], or facilitating semantic code search [73]. • Software quality assessment, e.g., measuring software metrics through graph properties [6], [15], [30], [74]. • Software refactoring, e.g., supporting software modularization through suggested code partitioning, suggesting method movements, or code structure improvements [16], [20], [75].…”

Section: Semantic Code Graph a Source Code Dependency Model Requirementsmentioning

confidence: 99%

“…On the other hand, the code to analyze the SCG data may be written in different suitable languages, such as Python or R. Consequently, it is crucial to provide APIs to write and read the format in multiple programming languages. 6) Conversion to other data formats -for more advanced data analysis we need to be able to convert the SCG representation to other data formats, such as data frames, or graph file formats specific for existing tools, e.g., as GDF 15 or DOT 16 ). Many different graph formats were proposed for exporting huge graph structures [80], but none of them satisfies all our requirements.…”

Section: G Scg Storage Formatmentioning

confidence: 99%

“…For each project, we build and analyze the full SCG graph, and then extract the Class Collaboration Network and the Call Graph from the SCG data. We have chosen these two models in addition to SCG, as both the Call Graph [11], [15], [34], [36], [83], [84] and the Class Collaboration Network [10], [38], [62], [63], [85] are models that are popular among researchers and have been used for software comprehension.…”

Section: Empirical Software Comprehension With Semantic Code Graphmentioning

confidence: 99%

“…One of the major code comprehension challenges is understanding and managing dependencies of software entities. Understanding code dependencies may comprise finding key code entities [10], localizing connected elements [2], [11], answering different reachability questions [12], reasoning about entire software structure including software architecture understanding [13]- [15]. Managing code dependencies denotes introducing required bug fixes or new features and, at the same time, guarding the project structure against decay signs, such as high coupling between modules or classes [16], data abstraction coupling or message passing coupling [17], forming god objects [18], introducing unintended dependencies between code entities, etc.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Semantic Code Graph—An Information Model to Facilitate Software Comprehension

Borowski,

Balis,

Orzechowski

2024

IEEE Access

View full text Add to dashboard Cite

Software comprehension can be extremely time-consuming due to the ever-growing size of codebases. Consequently, there is an increasing need to accelerate the code comprehension process to facilitate maintenance and reduce associated costs. A crucial aspect of this process is understanding and preserving the high quality of the code dependency structure. While a variety of code structure models already exist, there is a surprising lack of models that closely represent the source code and focus on software comprehension. As a result, there are no readily available and easy-to-use tools to assist with dependency comprehension, refactoring, and quality monitoring of code. To address this gap, we propose the Semantic Code Graph (SCG), an information model that offers a detailed abstract representation of code dependencies with a close relationship to the source code. We establish the critical properties of the SCG model and demonstrate its implementation for Java and Scala languages. To validate the SCG model's usefulness in software comprehension, we compare it to nine other source code representation models. Additionally, we select 11 well-known and widelyused open-source projects developed in Java and Scala and perform a range of software comprehension activities on them using three different code representation models: the proposed SCG, the Call Graph, and the Class Collaboration Network. We then qualitatively analyze the results to compare the performance of these models in terms of software comprehension capabilities. These activities encompass project structure comprehension, identifying critical project entities, interactive visualization of code dependencies, and uncovering code similarities through software mining. Our findings demonstrate that the SCG enhances software comprehension capabilities compared to the prevailing Class Collaboration Network and Call Graph models. Moreover, the SCG-based data analysis yields actionable software comprehension insights. We also release an open-source tool, scg-cli, to assist with result reproduction and further research. We believe that the work described is a step towards the next generation of tools that streamline code dependency comprehension and management.

show abstract

Complex Networks Analysis for Software Architecture: a Case Study on Hibernate (P)

Cited by 2 publications

References 7 publications

Analysis of function-call graphs of open-source software systems using complex network analysis

Analysis of function-call graphs of open-source software systems using complex network analysis

Semantic Code Graph—An Information Model to Facilitate Software Comprehension

Contact Info

Product

Resources

About