Creating User Scenarios through User Interaction Diagrams by Non-Technical Customers

Lecture Notes in Business Information Processing

2018

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Abstract. It is estimated that 85% of the defects in the developed software are originated from ambiguous, incomplete and wishful thinking software requirements. Natural language is often used to write software requirements specifications as well as user requirements. However, natural language specifications can be confusing and hard to understand. Some agile methodologists consider that acceptance tests are more precise and accurate sources of information about the customer's needs than descriptions in natural language. Several studies have addressed the use of acceptance tests as software requirements specification. Therefore, none of the previous studies has performed experiments to compare the applicability of different acceptance testing techniques in order to support an organization in the selection of one technique over another. This paper addresses this problem reporting an experiment conducted with undergraduate students in Computer Science. This experiment compares the applicability of two acceptance testing techniques (Fit tables and Gherkin language) as software requirements specification. This research tries to answer three questions: (a) Which technique is the easiest to learn in order to specify acceptance test scenarios? (b) Which technique requires less effort to specify acceptance tests? (c) Which technique is the best one to communicate software requirements? The results show that there is no sufficient evidence to affirm that one technique is easier to specify test scenarios or better to communicate software requirements. Whereas, the comparison of effort in terms of time to specify acceptance testing shows that the mean time to specify test scenarios using Gherkin language is lower than Fit tables.

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated Acceptance Tests as Software Requirements: An Experiment to Compare the Applicability of Fit Tables and Gherkin Language

Santos

Lecture Notes in Business Information Processing

2018

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“…The small population of participants is a weakness. However, it is possible to reply the methodology to increase the data [6].…”

Section: Threats To Validitymentioning

confidence: 99%

“…The objective of the experiment is to demonstrate the use of UIDs as user scenarios to specify requirements in the agile development, and compare the outcomes from applying both the progressive and regressive methods [6].…”

Section: Introductionmentioning

confidence: 99%

User Scenarios Through User Interaction Diagrams

Longo

Int. J. Soft. Eng. Knowl. Eng.

2015

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This paper investigates the applicability of User Interaction Diagrams (UIDs) as user scenarios for the speci¯cation of software requirements by non-technical customers. Two methods for building user scenarios using UIDs were proposed: the progressive and the regressive methods. These two methods were applied in an experiment where the results demonstrated that the regressive method requires signi¯cantly less e®ort as compared to the progressive method. Furthermore, there was a signi¯cant di®erence in the quality of diagrams obtained from each of the two methods. In our experiment, the regressive method resulted in better quality factors.

“…The User Scenarios through User Interaction Diagrams (US-UIDs) are suggested to allow that non-technician users define software functional requirements in the ATDD approach [4,5]. The US-UIDs are used to specify primarily the values of the information exchanged between the user and the computer in tasks that represent functional requirements, mainly in information systems and can be used as automated acceptance tests [6].…”

Section: Introductionmentioning

confidence: 99%

Metrics for Data Uniformity of User Scenarios through User Interaction Diagrams (S)

Longo

International Conferences on Software Engineering and Knowledge Engineering

2018

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In the software development process, the acceptance testing may be used by non-technician users to define software requirements. In this article, we use the US-UIDs (User Scenarios through User Interaction Diagrams) as automated acceptance tests in order to provide communications and collaboration between programmers and users. We propose three metrics for measuring the data uniformity in the US-UIDs. These metrics are investigated in four projects. The resulting measures from the investigations of the four projects are used to build a scale with classes to classify the uniformity of the US-UIDs. The classes (duplication, uniformity, irregularity) were created from empiric evaluation and compared to the measures from the offered metrics. The classification purpose is to identify the US-UIDs as uniform or irregular.