Unified use case statecharts: case studies

Svetinovic, Davor; Berry, Daniel M.; Day, Nancy A.; Godfrey, Michael W.

doi:10.1007/s00766-007-0053-1

Cited by 11 publications

(4 citation statements)

References 19 publications

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“…In spite of the positive observations and experience with KAOS for RICS, specifying all of the requirements of RICS is difficult: all the possible new goals and subsequently their means of achievement (subgoals) cannot be predicted. This is consistent with our findings on completeness of the requirements analysis models in general, and a need for proper model integration [Svetinovic et al., ]. The results depend on the selected documents coverage.…”

Section: Limitations and Validity Threatssupporting

confidence: 93%

Goal-Oriented Requirements Engineering for Research-Intensive Complex Systems: A Case Study

Woldeamlak¹,

Diabat²,

Svetinovic³

2016

Syst Eng

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Complex systems in research and development exhibit important characteristics that might present significant systems engineering challenges due to lack of clear customers, system goals, previous development experience, etc. Such systems are characterized through the existence of multiple proposed preliminary architectures, no implemented prototypes, and no agreed upon standards and protocols. We refer to these systems as Research-Intensive Complex Systems (RICS). RICS requirements are not well-defined, and RICS are exposed to a wide variety of risks and uncertainties. The main source of the RICS domain knowledge, requirements, and goals are research publications and reports. There is often a lack of clear goals, and many goals are ambiguous or conflicting. This paper evaluates the effectiveness of the Knowledge Acquisition in autOmated Specification (KAOS) method applied to smart metering system, as an example of a sustainability-related RICS. The evaluation is performed using a set of qualitative criteria with respect to KAOS's ability to elicit and specify goals for RICS in comparison to the implemented goal models. C⃝ 2016 Wiley Periodicals, Inc. Syst Eng 19: 322-333, 2016

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Section: Limitations and Validity Threatssupporting

confidence: 93%

Goal-Oriented Requirements Engineering for Research-Intensive Complex Systems: A Case Study

Woldeamlak¹,

Diabat²,

Svetinovic³

2016

Syst Eng

Self Cite

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“…However, the objectives and outputs are different. Nonautomated methods (e.g., [Glinz 2000]) have been suggested to transform NL requirements (e.g., use cases) into models such as Use Case Maps [Svetinovic et al 2007] and statecharts [Ryser and Glinz 1999].…”

Section: Related Workmentioning

confidence: 99%

aToucan

Yue

Briand

Labiche

2015

ACM Trans. Softw. Eng. Methodol.

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The transition from an informal requirements specification in natural language to a structured, precise specification is an important challenge in practice. It is particularly so for object-oriented methods, defined in the context of the OMG's Model Driven Architecture (MDA), where a key step is to transition from a use case model to an analysis model. However, providing automated support for this transition is challenging, mostly because, in practice, requirements are expressed in natural language and are much less structured than other kinds of development artifacts. Such an automated transformation would enable at least the generation of an initial, likely incomplete, analysis model and enable automated traceability from requirements to code, through various intermediate models. In this article, we propose a method and a tool called aToucan, building on existing work, to automatically generate a UML analysis model comprising class, sequence and activity diagrams from a use case model and to automatically establish traceability links between model elements of the use case model and the generated analysis model. Note that our goal is to save effort through automated support, not to replace human abstraction and decision making.Seven (six) case studies were performed to compare class (sequence) diagrams generated by aToucan to the ones created by experts, Masters students, and trained, fourth-year undergraduate students. Results show that aToucan performs well regarding consistency (e.g., 88% class diagram consistency) and completeness (e.g., 80% class completeness) when comparing generated class diagrams with reference class diagrams created by experts and Masters students. Similarly, sequence diagrams automatically generated by aToucan are highly consistent with the ones devised by experts and are also rather complete, for instance, 91% and 97% message consistency and completeness, respectively. Further, statistical tests show that aToucan significantly outperforms fourth-year engineering students in this respect, thus demonstrating the value of automation. We also conducted two industrial case studies demonstrating the applicability of aToucan in two different industrial domains. Results showed that the vast majority of model elements generated by aToucan are correct and that therefore, in practice, such models would be good initial models to refine and augment so as to converge towards to correct and complete analysis models. A performance analysis shows that the execution time of aToucan (when generating class and sequence diagrams) is dependent on the number of simple sentences contained in the use case model and remains within a range of a few minutes. Five different software system descriptions (18 use cases altogether) were performed to evaluate the generation of activity diagrams. Results show that aToucan can generate 100% complete and correct control flow information of activity diagrams and on average 85% data flAow information completeness. Moreover, we show that aToucan outperforms three commercial...

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“…The positive or negative word-of-mouth engendered by the interactions spreads through the open source software community, attracting or repelling users and developerstwo groups vital to a project's survival -to the developers' projects. These interactions are critical from the early requirements stages [5], through architectural design [6], to strategic requirements engineering and system evolution [7].…”

Section: Introductionmentioning

confidence: 99%

Software analytics study of Open-Source system survivability through social contagion

Low

Yathog

Svetinovic

2015

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

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Free, Libre and Open Source Software (FLOSS) development has grown in prominence in recent years as the software development approach of choice. However, the factors responsible for maintaining development interest in them are still poorly understood, as FLOSS projects differ significantly from traditional for-profit closed-source software development. To address that knowledge gap, we have analyzed data from GitHub, an open source code repository which provides extensive records on a multitude of collaborative software engineering projects. Using machine learning algorithms, we sought out patterns in the data that might help us understand how projects survive. Our findings suggest that the impressions propagated by the users of software projects to other users strongly influence the projects' survival, as one would expect in a social contagion model.

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Unified use case statecharts: case studies

Cited by 11 publications

References 19 publications

Goal-Oriented Requirements Engineering for Research-Intensive Complex Systems: A Case Study

Goal-Oriented Requirements Engineering for Research-Intensive Complex Systems: A Case Study

aToucan

Software analytics study of Open-Source system survivability through social contagion

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