Application of linguistic techniques for Use Case analysis

Fantechi, Alessandro; Gnesi, Stefania; Lami, Giuseppe; Maccari, Alessandro

doi:10.1109/icre.2002.1048518

Cited by 54 publications

(41 citation statements)

References 4 publications

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“…Defect types: Most works in this area focus on the detection of various forms of ambiguity, e.g. [8], [12], [13], [14]. Other works try to detect violations of syntactic [11] or even semantic duplications [15].…”

Section: Related Workmentioning

confidence: 99%

Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study

Femmer

Unterkalmsteiner

Gorschek

2017

2017 IEEE 25th International Requirements Engineering Conference Workshops (REW)

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Abstract-[Context:]The quality of requirements engineering artifacts, e.g. requirements specifications, is acknowledged to be an important success factor for projects. Therefore, many companies spend significant amounts of money to control the quality of their RE artifacts. To reduce spending and improve the RE artifact quality, methods were proposed that combine manual quality control, i.e. reviews, with automated approaches.

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Section: Related Workmentioning

confidence: 99%

Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study

Femmer

Unterkalmsteiner

Gorschek

2017

2017 IEEE 25th International Requirements Engineering Conference Workshops (REW)

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“…Bertolino et al are expressed (in the "Extensions" row) as alternatives to the main flow, linked by their index to the point of the main flow from which they branch as a variation. This natural language form of Use Cases has been widely used in industrial practice to specify Use Cases, e.g., at Nokia [9]. In [1] we extended the classical Use Case definition given by Cockburn to product lines, adding variability to this formalism.…”

Section: Pluc Notationmentioning

confidence: 99%

Product Line Use Cases: Scenario-Based Specification and Testing of Requirements

Bertolino

Fantechi

Gnesi

et al. 2006

Software Product Lines

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Use Cases can be employed in system requirements engineering to capture requirements from an external point of view. In product line modeling, commonalities and variabilities of a family of systems have to be described. To this purpose, we have defined extensions and modifications of the Use Cases notation, called Product Line Use Cases (PLUCs). In order to guarantee the conformance of the derived product with respect to the product line we add the capability of expressing constraints over the Product Use Cases that can be derived from a PLUC. Using this notation, it is possible to express in the requirements specification of the product line not only the possible variant characteristics that can differentiate products of the same line, but also which combinations of variant characteristics are "legal" and which are not. Testing is another activity in which PLUCs show their utility. Indeed, for a product belonging to a product line, testing is a crucial and expensive part of software development. Yet the derivation of test cases for product lines has so far received little attention. We outline a simple methodology for this purpose, which relies on the early requirements specification expressed as PLUCs.

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“…Another area where application of natural language processing tools would have been conceivable is in preventing ambiguity in the documents we generated. For example, Fantechi et al [19] present an approach that analyzes use cases written in natural language and provide certain metrics for measuring aspects related to ambiguity. These might have improved the consistency of the use case documents we created in Phase I as described in section 3.1.…”

Section: Could Automated Support For Requirements Analysis Have Been mentioning

confidence: 99%

Could an Agile Requirements Analysis Be Automated?—Lessons Learned from the Successful Overhauling of an Industrial Automation System

Aschauer¹,

Dauenhauer²,

Derler³

et al. 2008

Lecture Notes in Computer Science

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Abstract. This paper sketches a recent successful requirements analysis of a complex industrial automation system that mainly required a talented expert, with a beginner's mind, who has been willing to dig into the domain details together with a committed customer and a motivated team. With these key factors and the application of an appropriate combination of well-established and some newer methods and tools, we were able to efficiently elicit, refine, and validate requirements. From this specific context, we try to derive implications for innovative requirements analysis. We argue that in projects that go beyond simple, well defined, and well understood applications, automated requirements analysis is unlikely to lead to a successful specification of a system.

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Application of linguistic techniques for Use Case analysis

Cited by 54 publications

References 4 publications

Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study

Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study

Product Line Use Cases: Scenario-Based Specification and Testing of Requirements

Could an Agile Requirements Analysis Be Automated?—Lessons Learned from the Successful Overhauling of an Industrial Automation System

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