Studying software descriptions in SourceForge and app stores for a better understanding of real-life requirements

Bäumer, Frederik Simon; Dollmann, Markus; Geierhos, Michaela

doi:10.1145/3121264.3121269

Cited by 5 publications

(6 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At any rate, apart from a rather theoretical starting point, it is basically the same approach to start data-driven and model such relationships for existing data in order to have not only theoretical but real-life samples that, enriched with linguistic and requirements information, can be used for semi-automatic and automatic requirement engineering. However, there are no linguistic resources that cover characteristics of requirement specification texts collected in the OTF Computing domain [15,16]. That is, there are neither resources for compensation, nor for providing examples with real service descriptions.…”

Section: Open Challenges: a Discussionmentioning

confidence: 99%

“…We here need a kind of knowledge base in the form of linguistic resources as a minimum, which are rare for the domain of software requirements [15]. There is even less in the OTF Computing domain [16]. The disambiguation service Babelfy is often used as a substitute for a domain-specific disambiguation but is hosted entirely on external servers [17,18].…”

Section: Automatic Detection and Compensation Of Inaccuracymentioning

confidence: 99%

“…After this step, from the on-topic sentences containing functional requirements, there are attribute-value pairs extracted in order to iteratively fill the template, starting with the most important elements such as subjects, actions, predicates and objects, e.g., indirect objects. However, even though this approach convinces with good performance values, there are no suitable resources to be used and it therefore fails [16]. Here, textual software requirements can be helpful though not or rarely being available [15].…”

Section: Requirements Extractionmentioning

confidence: 99%

“…Especially with the further development of the Semantic Web [34] and Linked (Open) Data approaches [35,36], additional possibilities arise to integrate increasingly structured knowledge from different domains. Much knowledge in the field of requirements engineering and NLP is already available online but cannot be used automatically [16].…”

Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 99%

See 3 more Smart Citations

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

2019

Self Cite

View full text Add to dashboard Cite

The vision of On-the-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language. Since non-technical users write their software requirements themselves and in unrestricted natural language, deficits occur such as inaccuracy and incompleteness. These deficits are usually met by natural language processing methods, which have to face special challenges in OTF Computing because maximum automation is the goal. In this paper, we present current automatic approaches for solving inaccuracies and incompletenesses in natural language requirement descriptions and elaborate open challenges. In particular, we will discuss the necessity of domain-specific resources and show why, despite far-reaching automation, an intelligent and guided integration of end users into the compensation process is required. In this context, we present our idea of a chat bot that integrates users into the compensation process depending on the given circumstances.

show abstract

Section: Open Challenges: a Discussionmentioning

confidence: 99%

Section: Automatic Detection and Compensation Of Inaccuracymentioning

confidence: 99%

Section: Requirements Extractionmentioning

confidence: 99%

Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 99%

See 2 more Smart Citations

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…This is mainly due to the fact that more extensive requirements are not accessible [19]. Our collection of NL requirements is, to the best of our knowledge, one of the largest available [38,39]. However, the design of our prototype should be scalable to enable the processing of requirements of complex real-life systems.…”

Section: Discussionmentioning

confidence: 99%

Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-Based Configuration of Text Analysis Pipelines

Bäumer¹,

Geierhos²

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

Self Cite

View full text Add to dashboard Cite

Naturallanguage software requirements descriptions enable end users to formulate their wishes and expectations for a future software product without much prior knowledge in requirements engineering. However, these descriptions are susceptible to linguistic inaccuracies such as ambiguities and incompleteness that can harm the development process. There is a number of software solutions that can detect deficits in requirements descriptions and partially solve them, but they are often hard to use and not suitable for end users. For this reason, we develop a software system that helps end-users to create unambiguous and complete requirements descriptions by combining existing expert tools and controlling them using automatic compensation strategies.In order to recognize the necessity of individual compensation methods in the descriptions, we have developed linguistic indicators, which we present in this paper. Based on these indicators, the whole text analysis pipeline is ad-hoc configured and thus adapted to the individual circumstances of a requirements description.

show abstract

How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges

Bäumer

Geierhos

2018

Natural Language Processing and Information Systems

View full text Add to dashboard Cite

Studying software descriptions in SourceForge and app stores for a better understanding of real-life requirements

Cited by 5 publications

References 16 publications

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-Based Configuration of Text Analysis Pipelines

How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges

Contact Info

Product

Resources

About