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Exploration on Automated Software Requirement Document Readability Approaches

Context. The requirements analysis phase, as the very beginning of software development process, has been identified as a quite important phase in the software development lifecycle. Software Requirement Specification (SRS) is the output of requirements analysis phase, whose quality factors play an important role in the evaluation work. Readability is a quite important SRS quality factor, but there are few available automated approaches for readability measurement, because of the tight dependency on readers' perceptions. Low readability of SRS documents has a serious impact on the whole process of software development. Therefore, it's extremely urgent to propose effective automated approaches for SRS documents readability measurement. Using traditional readability indexes to analyze readability of SRS documents automatically is a potentially feasible approach. However, the effectiveness of this approach is not systematically evaluated before. Objectives. In this study, firstly, we aim to understand the readability of texts and investigate approaches to score texts readability manually. Then investigate existing automated readability approaches for texts with their working theories. Next, evaluate the effectiveness of measuring the readability of SRS documents by using these automated readability approaches. Finally, rank these automated approaches by their effectiveness. Methods. In order to find out the way how human score the readability of texts manually and investigate existing automated readability approaches for texts, systematic literature review is chosen as the research methodology. Experiment is chosen to explore the effectiveness of automated readability approaches. Results. We find 67 articles after performing systematic literature review. According to systematic literature review, human judging the readability of texts through reading is the most common way of scoring texts readability manually. Additionally, we find four available automated readability assessments tools and seven available automated readability assessments formulas. After executing the experiment, we find the actual value of effectiveness of all selected approaches are not high and Coh-Metrix presents the highest actual value of effectiveness of automated readability approach among the selected approaches. Conclusions. Coh-Metrix is the most effective automated readability approach, but the feasibility in directly applying Coh-Metrix in SRS documents readability assessments cannot be permitted. Since the actual value of evaluated effectiveness is not high enough. In addition, all selected approaches are based on metrics of readability measures, but no semantic factors are blended in readability assessments. Hence studying more on human perception quantifying and adding semantic analysis in SRS documents readability assessment could be two research directions in future.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-14816
Date January 2017
CreatorsChen, Mingda, He, Yao
PublisherBlekinge Tekniska Högskola, Institutionen för programvaruteknik, Blekinge Tekniska Högskola, Institutionen för programvaruteknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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