Ing. David Šenkýř

Článek

10.1007/s10844-022-00706-8

Katedra softwarového inženýrství

Functional requirements on a software system are traditionally captured as text that describes the expected functionality in the domain of a real-world system. Natural language processing methods allow us to extract the knowledge from such requirements and transform it, e.g., into a model. Moreover, these methods can improve the quality of the requirements, which usually suffer from ambiguity, incompleteness, and inconsistency. This paper presents a novel approach to using natural language processing. We use the method of grammatical inspection to find specific patterns in the description of functional requirement specifications (written in English). Then, we transform the requirements into a model of Normalized Systems elements. This may realize a possible component of the eagerly awaited text-to-software pipeline. The input of this method is represented by textual requirements. Its output is a running prototype of an information system created using Normalized Systems (NS) techniques. Therefore, the system is ready to accept further enhancements, e.g., custom code fragments, in an evolvable manner ensured by compliance with the NS principles. A demonstration of pipeline implementation is also included in this paper. The text processing part of our pipeline extends the existing pipeline implemented in our system TEMOS, where we propose and implement methods of checking the quality of textual requirements concerning ambiguity, incompleteness, and inconsistency.

Stať ve sborníku

10.5220/0010421602130220

Katedra softwarového inženýrství

In this contribution, we investigate the inconsistency problem in the textual description of functional requirements specifications. In the past, the inconsistency problem was investigated using analysis of the UML models. We argue that some sources of inconsistency can be revealed in the very first steps of textual requirements analysis using linguistic patterns that we developed. We cluster the sentences according to their semantic similarity given by their lexical content and syntactic structure. Our contribution focus on revealing linguistic contradictions (e.g., a combination of passive voice, antonyms, negated synonyms, etc.) of facts and rules described in different parts of requirements together with contradictions of the internally generated model.

Stať ve sborníku

10.1007/978-3-030-79022-6_7

Katedra softwarového inženýrství

In this paper, we describe our graph-oriented method used to find semantically similar sentences in external information sources that have a semantic enrichment potential in relation to sentences of textual functional requirements specification. Our motivation is to reduce the incompleteness of requirements that may be a source of inconsistency. We found there are some facts and rules so obvious for domain experts that they do not even mention them in requirements. We call such rules default consistency rules. These rules are often not implemented and can not be revealed from the requirements because they are not mentioned there.

Stať ve sborníku

10.5220/0009344202890296

Katedra softwarového inženýrství

In this contribution, we investigate the incompleteness problem in textual requirements specifications. Missing alternative scenarios are one of the incompleteness sources, i.e., descriptions of processing in the cases when something runs in another way as expected. We check the text of requirements specification using linguistic patterns, and we try to reveal scenarios and alternative scenarios. After that process is finished, we decide whether the set of alternative scenarios is complete. As a result, we generate warning messages. We illustrate our approach with examples.

Stať ve sborníku

10.5220/0007978003230330

Katedra softwarového inženýrství

In this contribution, we investigate the incompleteness problem in textual requirements specifications. Incompleteness is a typical problem that arises when stakeholders (e.g., domain experts) hold some information for generally known, and they do not mention it to the analyst. A model based on the incomplete requirements suffers from missing objects, properties, or relationships as we show in an illustrating example. Our presented methods are based on grammatical inspection, semantic networks (ConceptNet and BabelNet), and pre-configured data from on-line dictionaries. Additionally, we show how a domain model has to be used to reveal some missing parts of it. Our experiments have shown that the precision of our methods is about 60–82 %.

Stať ve sborníku

10.1007/978-3-030-16181-1_83

Katedra softwarového inženýrství

In this contribution, we investigate the ambiguity problem in textual requirements specifications. We focused on the structural ambiguity and extracted some patterns to indicate this kind of ambiguity. We show that the standard methods of linguistics are not enough in some cases, and we describe a class of ambiguity caused by coreference that needs an underlying domain model or a knowledge base to be solved. Part of our implemented solution is a cooperation of our tool TEMOS with the Prolog inference machine working with facts and rules acquired from OCL conditions of the domain model.

Stať ve sborníku

10.5220/0006827302310238

Katedra softwarového inženýrství

In this paper, we investigate methods of grammatical inspection to identify patterns in textual requirements specification. Unfortunately, a text in natural language includes additionally many inaccuracies caused by ambiguity, inconsistency, and incompleteness. Our contribution is that using our patterns, we are able to extract the information from the text that is necessary to fix some of the problems mentioned above. We present our implemented tool TEMOS that is able to detect some inaccuracies in a text and to generate fragments of the UML class model from textual requirements specification. We use external on-line resources to complete the textual information of requirements.