Evaluating the Effects of Architectural Documentation: A Case Study of a Large Scale Open Source Project

Kazman, Rick; Goldenson, Dennis R.; Monarch, Ira; Nichols, William R.; Valetto, Giuseppe

doi:10.1109/tse.2015.2465387

Cited by 29 publications

(21 citation statements)

References 58 publications

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“…Similar observations have been made for industrial usage by Torchiano et al [32] and Forward et al [33]. The finding that UML is used for communication purposes within OSS aligns with observations that were already made about the use of documentation by Kazman et al [41] and about the use of sketches by Chung et al [42]. This aligns with the insights of Gorschek et al [34] and Hutchison et al~ [14], who also observed a use for communication within industrial and OSS programmers.…”

Section: Answer To Rq5 What Are Practices For Using Uml Modeling In supporting

confidence: 87%

“…Osman et al [40] studied to what extent classes in the diagrams are implemented in the code. Finally, Kazman et al [41] investigate the Hadoop Distributed File System to learn how documentation impacts communication and commit behavior in the open source system. There are some studies that approach model use in open source with a quantitative perspective, studying large numbers of projects.…”

Section: Uml In Oss Projectsmentioning

confidence: 99%

“…by Yatani et al, who found that models are used to describe system designs, but are rarely updated [39]. [41]. There are some studies that approach the use of models in OSS with a quantitative perspective, studying a large number of projects.…”

Section: Modeling In Open Source Softwarementioning

confidence: 99%

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An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Osman

Ho-Quang

Chaudron

2018

2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Context: In modern software development, software modeling is considered to be an essential part of the software architecture and design activities. The Unified Modeling Language (UML) has become the de facto standard for software modeling in industry. Surprisingly, there are only a few empirical studies on the practices and impacts of UML modeling in software development. This is mainly due to the lack of empirical data on real-life software systems that use UML modeling. Objective: This PhD thesis contributes to this matter by describing a method to build and curate a big corpus of open-source-software (OSS) projects that contain UML models. Subsequently, this thesis offers observations on the practices and impacts of using UML modeling in these OSS projects. Method: We combine techniques from repository mining and image classification in order to successfully identify more than 24.000 open source projects on GitHub that together contain more than 93.000 UML models. Machine learning techniques are also used to enrich the corpus with annotations. Finally, various empirical studies, including a case study, a user study, a large-scale survey and an experiment, have been carried out across this set of projects. Result: The results show that UML is generally perceived to be helpful to new contributors. The most important motivation for using UML seems to be to facilitate collaboration. In particular, teams use UML during communication and planning of joint implementation efforts. Our study also shows that the use of UML modeling has a positive impact on software quality, i.e. it correlates with lower defect proneness. Further, we find out that visualisation of design concepts, such as class role-stereotypes, helps developers to perform better in software comprehension tasks.

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Section: Answer To Rq5 What Are Practices For Using Uml Modeling In supporting

confidence: 87%

Section: Uml In Oss Projectsmentioning

confidence: 99%

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An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Osman

Ho-Quang

Chaudron

2018

2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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“…Leximancer analyzes the frequencies and co-occurrence relationships between words in a text corpus and produces concept maps that show and name the significant concepts in the corpus. Leximancer also shows the relationships among the most significant concepts used in a text corpus, including those that express sentiment [16] [24]. It enables rapid analysis of tens of thousands or more text entries in records like those collected in Gmane or CVE List, but also allows modulation of the results through researcher intervention and interpretation.…”

Section: Identifying Emerging Conceptsmentioning

confidence: 99%

“…The characterization differentiates, and the classification relates, the individuals, groups, communities and organizations, the systems and applications, and the processes, methods and techniques involved. The three processes are: 1) mining security data sources using nounphrase parsing, automated terminology construction, statistical analysis and clustering to determine the most salient concepts [16] in the corpora being analyzed and track their changes through time; 2) mapping the relationships among these concepts and also tracking their changes through time, employing Leximancer. This will generate a series of maps representing the changing networks of the most prominent, relevant, and important concepts mined, including concepts representing both positive and negative sentiments; 3) building a security ontology [17][19] [9], that we call the Emergent Vulnerabilities and Exploits Ontology (EVEO), based on the results of 1) and 2) that will help guide the construction and tracking of emerging concepts.…”

Section: Tracking Concept Evolutionmentioning

confidence: 99%

Can Cybersecurity Be Proactive? A Big Data Approach and Challenges

Chen

Kazman

Monarch

et al. 2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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The cybersecurity community typically reacts to attacks after they occur. Being reactive is costly and can be fatal where attacks threaten lives, important data, or mission success. But can cybersecurity be done proactively? Our research capitalizes on the Germination Period-the time lag between hacker communities discussing software flaw types and flaws actually being exploited-where proactive measures can be taken. We argue for a novel proactive approach, utilizing big data, for (I) identifying potential attacks before they come to fruition; and based on this identification, (II) developing preventive countermeasures. The big data approach resulted in our vision of the Proactive Cybersecurity System (PCS), a layered, modular service platform that applies big data collection and processing tools to a wide variety of unstructured data sources to predict vulnerabilities and develop countermeasures. Our exploratory study is the first to show the promise of this novel proactive approach and illuminates challenges that need to be addressed.

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Factors affecting architectural decision‐making process and challenges in software projects: An industrial survey

Demir,

Chouseinoglou,

Tarhan

2024

J Software Evolu Process

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Software architecture plays a fundamental role in overcoming the challenges of the development process of large‐scale and complex software systems. The software architecture of a system is the result of an extensive process in which several stakeholders negotiate issues and solutions, and as a result of this negotiation, a series of architectural decisions are made. This survey study aims to determine the experiences of the software industry experts with respect to architectural decision‐making, the factors that are effective in decision‐making, and the technical and social problems they encounter. An online questionnaire‐based survey was conducted with 101 practitioners. The responses were analyzed qualitatively and quantitatively. Analysis of responses revealed that the majority of the participants prefer to document some or all of the architectural decisions taken and to store these documents in web‐based collaboration software. Decisions are usually made by teams of two or three, and discussion‐based approaches (brainstorming and consensus) are adopted. In the software architecture decision‐making process, “major business impact” is the most challenging situation. Information sharing and keeping track of decisions and decision rationale are areas in need of improvement as identified by most participants. From the participants' feedback and their answers to open‐ended questions, we concluded that the software architecture decision‐making process has an important role in the industry. Our key findings are that decisions made in the architectural decision‐making process are taken by teams and generally all decisions are documented. In projects where decisions are made by a single person, peer pressure is found to be significantly different from pressure in projects where decisions are made by the group. This is an indication that as the number of people in the decision‐making process increases, the disagreements also increase.

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Evaluating the Effects of Architectural Documentation: A Case Study of a Large Scale Open Source Project

Cited by 29 publications

References 58 publications

An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Can Cybersecurity Be Proactive? A Big Data Approach and Challenges

Factors affecting architectural decision‐making process and challenges in software projects: An industrial survey

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