Semi-automated Test Planning for e-ID Systems by Using Requirements Clustering

Güldali, Bariş; Funke, Holger; Jahnich, Michael; Sauer, Stefan; Engels, Gregor

doi:10.1109/ase.2009.86

Cited by 6 publications

(8 citation statements)

References 11 publications

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“…These are mainly manual activities. We have already reported on this process in [26]. In the next sections we briefly summarize the activities and explain the latest improvements in the process.…”

Section: Approachmentioning

confidence: 97%

“…In [26] we already reported on a case study on a national e-passport issuance system. It is distributed in offices in 10 cities and contains 70 workstations, 10 servers, and 6 personalization systems.…”

Section: Tool Support and Evaluationmentioning

confidence: 97%

“…In this case study, we showed that our prototype successfully identified initial clusters from a set of 405 requirements and indicated potential redundancies between requirements. Performance analysis showed that the annotation step including linguistic analysis is the most expensive step of the approach [26]. For approximately 400 requirements the annotation steps needed 141.859 milliseconds to run.…”

Section: Tool Support and Evaluationmentioning

confidence: 99%

“…Figure 5 shows how a requirement from the eID domain is represented as a syntax tree. We use some heuristics [26] to extract the semantic attributes Actor, Process and Object for each requirement from its syntax tree. In addition to the main sentence, we also extract semantic attributes for accessory clauses, e.g.…”

Section: Annotating Requirementsmentioning

confidence: 99%

“…We have already reported in [26] how clustering algorithms can be exploited to find sets of redundant, overlapping or interdependent requirements. In this paper, we focus on how these requirements clusters can be used to semi-automatically derive test plans from these requirements.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Pattern-based generation of test plans for open distributed processing systems

Güldali

Sauer

Winkelhane

et al. 2010

Proceedings of the 5th Workshop on Automation of Software Test

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Acceptance testing is a time-consuming task for complex software systems that have to fulfil a large number of requirements. To reduce efforts in acceptance testing, we have developed an approach that exploits redundancies and implicit relations in requirements specifications which are based on multi-viewpoint techniques, such as RM-ODP. We use linguistic analysis techniques, requirements clustering algorithms and pattern-based requirements collection for reducing the total number of test cases that are derived from the requirements specification. In particular, we present new capabilities for automatically deriving semi-formal test plans and acceptance criteria from the clustered informal textual requirements. Tool support for automated detection of redundancies and implicit relations is extended by new functionalities regarding measurement and the generation of quality plans. We apply our solution particularly in planning, procurement and acceptance testing of national electronic identification (eID) systems. In summary, we show that linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.

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Section: Approachmentioning

confidence: 97%

Section: Tool Support and Evaluationmentioning

confidence: 97%

Section: Tool Support and Evaluationmentioning

confidence: 99%

Section: Annotating Requirementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Pattern-based generation of test plans for open distributed processing systems

Güldali

Sauer

Winkelhane

et al. 2010

Proceedings of the 5th Workshop on Automation of Software Test

Self Cite

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TORC: test plan optimization by requirements clustering

et al. 2011

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Acceptance testing is a time-consuming task for complex software systems that have to fulfill a large number of requirements. To reduce this effort, we have developed a widely automated method for deriving test plans from requirements that are expressed in natural language. It consists of three stages: annotation, clustering, and test plan specification. The general idea is to exploit redundancies and implicit relationships in requirements specifications. Multi-viewpoint techniques based on RM-ODP (Reference Model for Open Distributed Processing) are employed for specifying the requirements. We then use linguistic analysis techniques, requirements clustering algorithms, and pattern-based requirements collection to reduce the total effort of testing against the requirements specification. In particular, we use linguistic analysis for extracting and annotating the actor, process and object of a requirements statement. During clustering, a similarity function is computed as a measure for the overlap of requirements. In the test plan specification stage, our approach provides capabilities for semi-automatically deriving test plans and acceptance criteria from the clustered informal textual requirements. Two patterns are applied to compute a suitable order of test activities. The generated test plans consist of a sequence of test steps and asserts that are executed or checked in the given order. We also present the supporting prototype tool TORC, which is available open source. For the evaluation of the approach, we have conducted a case study in the field of acceptance testing of a national electronic identification system. In summary, we report on lessons learned how linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.

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Empirical Principles and an Industrial Case Study in Retrieving Equivalent Requirements via Natural Language Processing Techniques

Falessi

Cantone²

2013

IIEEE Trans. Software Eng.

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Semi-automated Test Planning for e-ID Systems by Using Requirements Clustering

Cited by 6 publications

References 11 publications

Pattern-based generation of test plans for open distributed processing systems

Pattern-based generation of test plans for open distributed processing systems

TORC: test plan optimization by requirements clustering

Empirical Principles and an Industrial Case Study in Retrieving Equivalent Requirements via Natural Language Processing Techniques

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