The specific purpose of this doctoral research is to improve the writing of requirements at the French Space Agency (CNES) by proposing a set of linguistic rules - referred to as a Controlled Natural Language (CNL) - that engineers should follow when writing out specifications in French. CNLs for technical writing do already exist, but if they are reviewed from a linguistic point of view, they are found unsatisfactory and too constraining, because some of the rules they impose lack relevance or are not compatible with the way engineers actually specify large-scale systems. In this research abstract, we will present a methodology based on corpus analysis aimed at improving existing rules and suggesting new ones that are inspired by existing data. We will also consider requirements extracted from specifications written at CNES to demonstrate its feasibility.
{"title":"How can corpus linguistics help improve requirements writing? Specifications of a space project as a case study","authors":"Maxime Warnier","doi":"10.1109/RE.2015.7320456","DOIUrl":"https://doi.org/10.1109/RE.2015.7320456","url":null,"abstract":"The specific purpose of this doctoral research is to improve the writing of requirements at the French Space Agency (CNES) by proposing a set of linguistic rules - referred to as a Controlled Natural Language (CNL) - that engineers should follow when writing out specifications in French. CNLs for technical writing do already exist, but if they are reviewed from a linguistic point of view, they are found unsatisfactory and too constraining, because some of the rules they impose lack relevance or are not compatible with the way engineers actually specify large-scale systems. In this research abstract, we will present a methodology based on corpus analysis aimed at improving existing rules and suggesting new ones that are inspired by existing data. We will also consider requirements extracted from specifications written at CNES to demonstrate its feasibility.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128379264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Preethu Rose Anish, M. Daneva, J. Cleland-Huang, R. Wieringa, S. Ghaisas
Software architects are responsible for designing an architectural solution that satisfies the functional and non-functional requirements of the system to the fullest extent possible. However, the details they need to make informed architectural decisions are often missing from the requirements specification. An earlier study we conducted indicated that architects intuitively recognize architecturally significant requirements in a project, and often seek out relevant stakeholders in order to ask Probing Questions (PQs) that help them acquire the information they need. This paper presents results from a qualitative interview study aimed at identifying architecturally significant functional requirements' categories from various business domains, exploring relevant PQs for each category, and then grouping PQs by type. Using interview data from 14 software architects in three countries, we identified 15 categories of architecturally significant functional requirements and 6 types of PQs. We found that the domain knowledge of the architect and her experience influence the choice of PQs significantly. A preliminary quantitative evaluation of the results against real-life software requirements specification documents indicated that software specifications in our sample largely do not contain the crucial architectural differentiators that may impact architectural choices and that PQs are a necessary mechanism to unearth them. Further, our findings provide the initial list of PQs which could be used to prompt business analysts to elicit architecturally significant functional requirements that the architects need.
{"title":"What you ask is what you get: Understanding architecturally significant functional requirements","authors":"Preethu Rose Anish, M. Daneva, J. Cleland-Huang, R. Wieringa, S. Ghaisas","doi":"10.1109/RE.2015.7320411","DOIUrl":"https://doi.org/10.1109/RE.2015.7320411","url":null,"abstract":"Software architects are responsible for designing an architectural solution that satisfies the functional and non-functional requirements of the system to the fullest extent possible. However, the details they need to make informed architectural decisions are often missing from the requirements specification. An earlier study we conducted indicated that architects intuitively recognize architecturally significant requirements in a project, and often seek out relevant stakeholders in order to ask Probing Questions (PQs) that help them acquire the information they need. This paper presents results from a qualitative interview study aimed at identifying architecturally significant functional requirements' categories from various business domains, exploring relevant PQs for each category, and then grouping PQs by type. Using interview data from 14 software architects in three countries, we identified 15 categories of architecturally significant functional requirements and 6 types of PQs. We found that the domain knowledge of the architect and her experience influence the choice of PQs significantly. A preliminary quantitative evaluation of the results against real-life software requirements specification documents indicated that software specifications in our sample largely do not contain the crucial architectural differentiators that may impact architectural choices and that PQs are a necessary mechanism to unearth them. Further, our findings provide the initial list of PQs which could be used to prompt business analysts to elicit architecturally significant functional requirements that the architects need.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127657702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Requirements reuse promises to reduce product development cost and improve product quality. Applying a standard set of requirements to multiple products configured into the same system can ensure all the products take advantage of the system's architectural features and do not adversely interact with each other. While existing literature provides guidance for developing requirements suitable for reuse, little has been written on the practical realities an organization faces in attempting to reuse requirements. This paper addresses that gap by describing a commercial engineering company's deployment of a requirements reuse process, the problems encountered, the results obtained, and the plans for future improvement of the process.
{"title":"Reuse of architecturally derived Standards Requirements","authors":"Michael C. Panis","doi":"10.1109/RE.2015.7320446","DOIUrl":"https://doi.org/10.1109/RE.2015.7320446","url":null,"abstract":"Requirements reuse promises to reduce product development cost and improve product quality. Applying a standard set of requirements to multiple products configured into the same system can ensure all the products take advantage of the system's architectural features and do not adversely interact with each other. While existing literature provides guidance for developing requirements suitable for reuse, little has been written on the practical realities an organization faces in attempting to reuse requirements. This paper addresses that gap by describing a commercial engineering company's deployment of a requirements reuse process, the problems encountered, the results obtained, and the plans for future improvement of the process.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128976653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.
{"title":"QuantUn: Quantification of uncertainty for the reassessment of requirements","authors":"N. Bencomo","doi":"10.1109/RE.2015.7320429","DOIUrl":"https://doi.org/10.1109/RE.2015.7320429","url":null,"abstract":"Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129465113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The growing complexity and dynamics of the execution environment have been major motivation for designing self-adaptive systems. Although significant work can be found in the field of formalizing or modeling the requirements of adaptive system, not enough attention has been paid towards the requirements elicitation techniques for the same. It is still an open challenge to elicit the users' requirements in the light of various contexts and introduce the required flexibility in the system's behavior at an early phase of requirements engineering. We explore the idea of using a cognitive technique, repertory grid, to acquire the knowledge of various stakeholders along multiple dimensions of problem space and design space. We aim at discovering the scope of variations in the features of the system by capturing the intentional and technical variability in the problem space and design space respectively. A stepwise methodology for finding the right set of features in the changing context has also been provided in this work. We evaluate the proposed idea by a preliminary case study using smart home system domain.
{"title":"From requirements elicitation to variability analysis using repertory grid: A cognitive approach","authors":"Sangeeta Dey, Seok-Won Lee","doi":"10.1109/RE.2015.7320407","DOIUrl":"https://doi.org/10.1109/RE.2015.7320407","url":null,"abstract":"The growing complexity and dynamics of the execution environment have been major motivation for designing self-adaptive systems. Although significant work can be found in the field of formalizing or modeling the requirements of adaptive system, not enough attention has been paid towards the requirements elicitation techniques for the same. It is still an open challenge to elicit the users' requirements in the light of various contexts and introduce the required flexibility in the system's behavior at an early phase of requirements engineering. We explore the idea of using a cognitive technique, repertory grid, to acquire the knowledge of various stakeholders along multiple dimensions of problem space and design space. We aim at discovering the scope of variations in the features of the system by capturing the intentional and technical variability in the problem space and design space respectively. A stepwise methodology for finding the right set of features in the changing context has also been provided in this work. We evaluate the proposed idea by a preliminary case study using smart home system domain.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121984802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Lucassen, F. Dalpiaz, J. V. D. Werf, S. Brinkkemper
User stories are a widely used notation for formulating requirements in agile development projects. Despite their popularity in industry, little to no academic work is available on assessing their quality. The few existing approaches are too generic or employ highly qualitative metrics. We propose the Quality User Story Framework, consisting of 14 quality criteria that user story writers should strive to conform to. Additionally, we introduce the conceptual model of a user story, which we rely on to design the AQUSA software tool. AQUSA aids requirements engineers in turning raw user stories into higher-quality ones by exposing defects and deviations from good practice in user stories. We evaluate our work by applying the framework and a prototype implementation to three user story sets from industry.
{"title":"Forging high-quality User Stories: Towards a discipline for Agile Requirements","authors":"G. Lucassen, F. Dalpiaz, J. V. D. Werf, S. Brinkkemper","doi":"10.1109/RE.2015.7320415","DOIUrl":"https://doi.org/10.1109/RE.2015.7320415","url":null,"abstract":"User stories are a widely used notation for formulating requirements in agile development projects. Despite their popularity in industry, little to no academic work is available on assessing their quality. The few existing approaches are too generic or employ highly qualitative metrics. We propose the Quality User Story Framework, consisting of 14 quality criteria that user story writers should strive to conform to. Additionally, we introduce the conceptual model of a user story, which we rely on to design the AQUSA software tool. AQUSA aids requirements engineers in turning raw user stories into higher-quality ones by exposing defects and deviations from good practice in user stories. We evaluate our work by applying the framework and a prototype implementation to three user story sets from industry.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Ameller, Xavier Franch, Cristina Gómez, João Araújo, Richard Berntsson-Svensson, S. Biffl, Jordi Cabot, V. Cortellessa, M. Daneva, Daniel Méndez Fernández, A. Moreira, H. Muccini, Antonio Vallecillo, M. Wimmer, Vasco Amaral, H. Brunelière, L. Burgueño, M. Goulão, B. Schätz, Sabine Teufl
Model-Driven Development (MDD) is no longer a novel development paradigm. It has become mature from a research perspective and recent studies show its adoption in industry. Still, some issues remain a challenge. Among them, we are interested in the treatment of non-functional requirements (NFRs) in MDD processes. Very few MDD approaches have been reported to deal with NFRs (and they do it in a limited way). However, it is clear that NFRs need to be considered somehow in the final product of the MDD process. To better understand how NFRs are integrated into the existing MDD approaches, we have initiated the NFR4MDD project, a multi-national empirical study, based on interviews with companies working on MDD projects. Our project aims at surveying the state of the practice for this topic. In this paper, we summarize our research protocol and present the current status of our study. The discussion will focus on the peculiarities of our study's context and organization involving about 20 researchers from 8 European countries.
{"title":"Handling non-functional requirements in Model-Driven Development: An ongoing industrial survey","authors":"David Ameller, Xavier Franch, Cristina Gómez, João Araújo, Richard Berntsson-Svensson, S. Biffl, Jordi Cabot, V. Cortellessa, M. Daneva, Daniel Méndez Fernández, A. Moreira, H. Muccini, Antonio Vallecillo, M. Wimmer, Vasco Amaral, H. Brunelière, L. Burgueño, M. Goulão, B. Schätz, Sabine Teufl","doi":"10.1109/RE.2015.7320424","DOIUrl":"https://doi.org/10.1109/RE.2015.7320424","url":null,"abstract":"Model-Driven Development (MDD) is no longer a novel development paradigm. It has become mature from a research perspective and recent studies show its adoption in industry. Still, some issues remain a challenge. Among them, we are interested in the treatment of non-functional requirements (NFRs) in MDD processes. Very few MDD approaches have been reported to deal with NFRs (and they do it in a limited way). However, it is clear that NFRs need to be considered somehow in the final product of the MDD process. To better understand how NFRs are integrated into the existing MDD approaches, we have initiated the NFR4MDD project, a multi-national empirical study, based on interviews with companies working on MDD projects. Our project aims at surveying the state of the practice for this topic. In this paper, we summarize our research protocol and present the current status of our study. The discussion will focus on the peculiarities of our study's context and organization involving about 20 researchers from 8 European countries.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127395294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Software Traceability is a critical element in all safety critical software systems. Trace links are created across diverse artifacts such as requirements, design, code, test cases, and hazards - either manually or with the help of supporting tools. The links are then used to support a range of software engineering activities including impact analysis, compliance verification, and safety inspections. For traceability to effectively support these activities it is important for the meaning and rationale of each link to be clearly communicated. It is often insuficient to know that one artifact satisfies, realizes, or complies to another. Instead, it is important to know why and how it does so. Terms and phrases used to describe artifacts are connected through composition, synonymic, and generalization relationships which often can only be interpreted by domain experts. In this RE:Next! paper we propose a novel approach for utilizing domain-specific knowledge bases to generate trace link rationales. We illustrate our approach with examples of automatically generated rationales taken from the domain of Communication and Control of a Transportation system, and from a Medical Infusion pump domain.
{"title":"Trace links explained: An automated approach for generating rationales","authors":"Jin Guo, Natawut Monaikul, J. Cleland-Huang","doi":"10.1109/RE.2015.7320423","DOIUrl":"https://doi.org/10.1109/RE.2015.7320423","url":null,"abstract":"Software Traceability is a critical element in all safety critical software systems. Trace links are created across diverse artifacts such as requirements, design, code, test cases, and hazards - either manually or with the help of supporting tools. The links are then used to support a range of software engineering activities including impact analysis, compliance verification, and safety inspections. For traceability to effectively support these activities it is important for the meaning and rationale of each link to be clearly communicated. It is often insuficient to know that one artifact satisfies, realizes, or complies to another. Instead, it is important to know why and how it does so. Terms and phrases used to describe artifacts are connected through composition, synonymic, and generalization relationships which often can only be interpreted by domain experts. In this RE:Next! paper we propose a novel approach for utilizing domain-specific knowledge bases to generate trace link rationales. We illustrate our approach with examples of automatically generated rationales taken from the domain of Communication and Control of a Transportation system, and from a Medical Infusion pump domain.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"10 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114132321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Callele, Philip Dueck, K. Wnuk, Peitsa Hynninen
A properly formed requirement is testable, a necessity for ensuring that design goals are met. While challenging in productivity applications, entertainment applications such as games compound the problem due to their subjective nature. We report here on our efforts to create testable experience requirements, the associated scope challenges and challenges with test design and result interpretation. We further report on issues experienced when performing focus group testing and provide practitioner guidance.
{"title":"Experience requirements in video games definition and testability","authors":"David Callele, Philip Dueck, K. Wnuk, Peitsa Hynninen","doi":"10.1109/RE.2015.7320449","DOIUrl":"https://doi.org/10.1109/RE.2015.7320449","url":null,"abstract":"A properly formed requirement is testable, a necessity for ensuring that design goals are met. While challenging in productivity applications, entertainment applications such as games compound the problem due to their subjective nature. We report here on our efforts to create testable experience requirements, the associated scope challenges and challenges with test design and result interpretation. We further report on issues experienced when performing focus group testing and provide practitioner guidance.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"8 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125754857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
App stores like Google Play and Apple AppStore have over 3 Million apps covering nearly every kind of software and service. Billions of users regularly download, use, and review these apps. Recent studies have shown that reviews written by the users represent a rich source of information for the app vendors and the developers, as they include information about bugs, ideas for new features, or documentation of released features. This paper introduces several probabilistic techniques to classify app reviews into four types: bug reports, feature requests, user experiences, and ratings. For this we use review metadata such as the star rating and the tense, as well as, text classification, natural language processing, and sentiment analysis techniques. We conducted a series of experiments to compare the accuracy of the techniques and compared them with simple string matching. We found that metadata alone results in a poor classification accuracy. When combined with natural language processing, the classification precision got between 70-95% while the recall between 80-90%. Multiple binary classifiers outperformed single multiclass classifiers. Our results impact the design of review analytics tools which help app vendors, developers, and users to deal with the large amount of reviews, filter critical reviews, and assign them to the appropriate stakeholders.
Google Play和苹果AppStore等应用商店拥有超过300万款应用，涵盖了几乎所有类型的软件和服务。数十亿用户定期下载、使用和审查这些应用程序。最近的研究表明，用户的评论为应用供应商和开发者提供了丰富的信息来源，因为它们包含了有关漏洞、新功能想法或已发布功能文档的信息。本文介绍了几种概率技术，将应用评论分为四种类型:bug报告、功能请求、用户体验和评级。为此，我们使用评论元数据，如星级和时态，以及文本分类，自然语言处理和情感分析技术。我们进行了一系列的实验来比较这些技术的准确性，并将它们与简单的字符串匹配进行了比较。我们发现单独使用元数据会导致较差的分类准确性。结合自然语言处理，分类精度在70-95%之间，查全率在80-90%之间。多个二元分类器优于单个多类分类器。我们的研究结果影响了评论分析工具的设计，这些工具可以帮助应用程序供应商、开发者和用户处理大量的评论，过滤关键的评论，并将它们分配给适当的利益相关者。
{"title":"Bug report, feature request, or simply praise? On automatically classifying app reviews","authors":"W. Maalej, H. Nabil","doi":"10.1109/RE.2015.7320414","DOIUrl":"https://doi.org/10.1109/RE.2015.7320414","url":null,"abstract":"App stores like Google Play and Apple AppStore have over 3 Million apps covering nearly every kind of software and service. Billions of users regularly download, use, and review these apps. Recent studies have shown that reviews written by the users represent a rich source of information for the app vendors and the developers, as they include information about bugs, ideas for new features, or documentation of released features. This paper introduces several probabilistic techniques to classify app reviews into four types: bug reports, feature requests, user experiences, and ratings. For this we use review metadata such as the star rating and the tense, as well as, text classification, natural language processing, and sentiment analysis techniques. We conducted a series of experiments to compare the accuracy of the techniques and compared them with simple string matching. We found that metadata alone results in a poor classification accuracy. When combined with natural language processing, the classification precision got between 70-95% while the recall between 80-90%. Multiple binary classifiers outperformed single multiclass classifiers. Our results impact the design of review analytics tools which help app vendors, developers, and users to deal with the large amount of reviews, filter critical reviews, and assign them to the appropriate stakeholders.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121320037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：