Mohammad R. Basirati, Henning Femmer, S. Eder, Martin Fritzsche, Alexander Widera
Requirements change and so (should) do requirements artifacts, such as use cases. However, we have little knowledge about which changes requirements engineers actually perform on use cases. We do not know what is changing, at which locations use cases change and need a deeper understanding of which changes are problematic in terms of difficult or risky. To explore these challenges from an industrial point of view, we conducted a mixed methods case study in which we analyze 15 month of changes in use cases in an industrial software project. The study provided interesting observations for both practitioners and researchers involved: First, the most frequently changing use cases had an issue in their structuring. Second, alternative flows (i.e., variations or extensions of the main flow) were especially prone to changes. Third, changes in content (semantic changes) and in presentation of the content (syntactic changes) happen similarly frequently. Last, a qualitative and quantitative analysis aiming at a deeper understanding of problematic changes identified taxonomy changes, as well as locally or temporally dispersed changes as particularly difficult and risky. In this paper, we contribute a first empirical inquiry for understanding the maintainability of use cases: The presented study provides empirical evidence that there are particular maintenance risks and suggests to continuously analyze local and temporal dispersion.
{"title":"Understanding changes in use cases: A case study","authors":"Mohammad R. Basirati, Henning Femmer, S. Eder, Martin Fritzsche, Alexander Widera","doi":"10.1109/RE.2015.7320452","DOIUrl":"https://doi.org/10.1109/RE.2015.7320452","url":null,"abstract":"Requirements change and so (should) do requirements artifacts, such as use cases. However, we have little knowledge about which changes requirements engineers actually perform on use cases. We do not know what is changing, at which locations use cases change and need a deeper understanding of which changes are problematic in terms of difficult or risky. To explore these challenges from an industrial point of view, we conducted a mixed methods case study in which we analyze 15 month of changes in use cases in an industrial software project. The study provided interesting observations for both practitioners and researchers involved: First, the most frequently changing use cases had an issue in their structuring. Second, alternative flows (i.e., variations or extensions of the main flow) were especially prone to changes. Third, changes in content (semantic changes) and in presentation of the content (syntactic changes) happen similarly frequently. Last, a qualitative and quantitative analysis aiming at a deeper understanding of problematic changes identified taxonomy changes, as well as locally or temporally dispersed changes as particularly difficult and risky. In this paper, we contribute a first empirical inquiry for understanding the maintainability of use cases: The presented study provides empirical evidence that there are particular maintenance risks and suggests to continuously analyze local and temporal dispersion.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"68 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":"130665839","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 engineers are faced with multiple sources of uncertainty. In particular, the extent to which the identified software requirements and environment assumptions are adequate and sufficiently complete is uncertain; the extent to which they will be satisfied in the system-to-be is uncertain; and the extent to which obstacles to their satisfaction will occur is uncertain. The resolution of such domain-level uncertainty requires estimations of the likelihood that those different types of situations may or may not occur. However, the extent to which the resulting estimates are accurate is uncertain as well. This meta-level uncertainty limits current risk-based methods for requirements engineering. The paper introduces a quantitative approach for managing it. An earlier formal framework for probabilistic goals and obstacles is extended to explicitly cope with uncertainties about estimates of likelihoods of fine-grained obstacles to goal satisfaction. Such estimates are elicited from multiple sources and combined in order to reduce their uncertainty margins. The combined estimates and their uncertainties are up-propagated through obstacle refinement trees and then through the system's goal model. Two metrics are introduced for measuring problematic uncertainties. When applied to the probability distributions obtained by up-propagation to the top-level goals, the metrics allow critical leaf obstacles with most problematic uncertainty margins to be highlighted. The proposed approach is evaluated on excerpts from a real ambulance dispatching system.
{"title":"Handling knowledge uncertainty in risk-based requirements engineering","authors":"Antoine Cailliau, A. V. Lamsweerde","doi":"10.1109/RE.2015.7320413","DOIUrl":"https://doi.org/10.1109/RE.2015.7320413","url":null,"abstract":"Requirements engineers are faced with multiple sources of uncertainty. In particular, the extent to which the identified software requirements and environment assumptions are adequate and sufficiently complete is uncertain; the extent to which they will be satisfied in the system-to-be is uncertain; and the extent to which obstacles to their satisfaction will occur is uncertain. The resolution of such domain-level uncertainty requires estimations of the likelihood that those different types of situations may or may not occur. However, the extent to which the resulting estimates are accurate is uncertain as well. This meta-level uncertainty limits current risk-based methods for requirements engineering. The paper introduces a quantitative approach for managing it. An earlier formal framework for probabilistic goals and obstacles is extended to explicitly cope with uncertainties about estimates of likelihoods of fine-grained obstacles to goal satisfaction. Such estimates are elicited from multiple sources and combined in order to reduce their uncertainty margins. The combined estimates and their uncertainties are up-propagated through obstacle refinement trees and then through the system's goal model. Two metrics are introduced for measuring problematic uncertainties. When applied to the probability distributions obtained by up-propagation to the top-level goals, the metrics allow critical leaf obstacles with most problematic uncertainty margins to be highlighted. The proposed approach is evaluated on excerpts from a real ambulance dispatching system.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"22 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":"134061799","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}
A relevant activity in the requirements engineering process consists in the identification, assessment and management of potential risks, which can prevent the system-to-be from meeting stakeholder needs. However, risk analysis techniques are often time- and resource- consuming activities, which may introduce in the requirements engineering process a significant overhead. To overcome this problem, we aim at supporting risk management activity in a semi-automated way, merging the capability to exploit existing risk-related information potentially present in a given organisation, with an automated ranking of the goals with respect to the level of risk the decision-maker estimates for them. In particular, this paper proposes an approach to address the general problem of risk decision-making, which combines knowledge about risks assessment techniques and Machine Learning to enable an active intervention of human evaluators in the decision process, learning from their feedback and integrating it with the organisational knowledge. The long term objective is that of improving the capacity of an organisation to be aware and to manage risks, by introducing new techniques in the field of risk management that are able to interactively and continuously extract useful knowledge from the organisation domain and from the decision-maker expertise.
{"title":"Goals at risk? Machine learning at support of early assessment","authors":"P. Avesani, A. Perini, A. Siena, A. Susi","doi":"10.1109/RE.2015.7320432","DOIUrl":"https://doi.org/10.1109/RE.2015.7320432","url":null,"abstract":"A relevant activity in the requirements engineering process consists in the identification, assessment and management of potential risks, which can prevent the system-to-be from meeting stakeholder needs. However, risk analysis techniques are often time- and resource- consuming activities, which may introduce in the requirements engineering process a significant overhead. To overcome this problem, we aim at supporting risk management activity in a semi-automated way, merging the capability to exploit existing risk-related information potentially present in a given organisation, with an automated ranking of the goals with respect to the level of risk the decision-maker estimates for them. In particular, this paper proposes an approach to address the general problem of risk decision-making, which combines knowledge about risks assessment techniques and Machine Learning to enable an active intervention of human evaluators in the decision process, learning from their feedback and integrating it with the organisational knowledge. The long term objective is that of improving the capacity of an organisation to be aware and to manage risks, by introducing new techniques in the field of risk management that are able to interactively and continuously extract useful knowledge from the organisation domain and from the decision-maker expertise.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"62 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":"121704790","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}
Goal-Orientation provides a rich framework for reasoning about systems during the Requirements Engineering (RE) phase. While critical properties like safety or security can require formal semantics, performing quantitative reasoning on semi-formal models in a much more lightweight approach reveals to be sufficient in many projects. Most of the time, existing RE tools only target specific quantification scenarios or do not provide easy mechanisms for implementing them. In order to demonstrate the ability to provide mechanisms that are both generic and powerful, we developed an extension of the Objectiver tool in three directions: (1) internal reasoning capabilities on AND-OR goal/obstacles structures, (2) close integration with an external spreadsheet application and (3) model export for building assessment tools using model-driven engineering techniques. We also demonstrate how our approach can cope with a variety of industrial scenarios requiring some form of quantification such as risk analysis, selection of design alternatives, effort estimation, and assessment of customer satisfaction.
{"title":"Supporting quantitative assessment of requirements in Goal Orientation","authors":"Robert Darimont, C. Ponsard","doi":"10.1109/RE.2015.7320443","DOIUrl":"https://doi.org/10.1109/RE.2015.7320443","url":null,"abstract":"Goal-Orientation provides a rich framework for reasoning about systems during the Requirements Engineering (RE) phase. While critical properties like safety or security can require formal semantics, performing quantitative reasoning on semi-formal models in a much more lightweight approach reveals to be sufficient in many projects. Most of the time, existing RE tools only target specific quantification scenarios or do not provide easy mechanisms for implementing them. In order to demonstrate the ability to provide mechanisms that are both generic and powerful, we developed an extension of the Objectiver tool in three directions: (1) internal reasoning capabilities on AND-OR goal/obstacles structures, (2) close integration with an external spreadsheet application and (3) model export for building assessment tools using model-driven engineering techniques. We also demonstrate how our approach can cope with a variety of industrial scenarios requiring some form of quantification such as risk analysis, selection of design alternatives, effort estimation, and assessment of customer satisfaction.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"18 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":"133722071","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}
We apply an existing formal framework for practical reasoning with arguments and evidence to the Goal-oriented Requirements Language (GRL), which is part of the User Requirements Notation (URN). This formal framework serves as a rationalization for elements in a GRL model: using attack relations between arguments we can automatically compute the acceptability status of elements in a GRL model, based on the acceptability status of their underlying arguments and the evidence. We integrate the formal framework into the GRL metamodel and we set out a research to further develop this framework.
{"title":"Rationalization of goal models in GRL using formal argumentation","authors":"Marc van Zee, Floris Bex, S. Ghanavati","doi":"10.1109/RE.2015.7320426","DOIUrl":"https://doi.org/10.1109/RE.2015.7320426","url":null,"abstract":"We apply an existing formal framework for practical reasoning with arguments and evidence to the Goal-oriented Requirements Language (GRL), which is part of the User Requirements Notation (URN). This formal framework serves as a rationalization for elements in a GRL model: using attack relations between arguments we can automatically compute the acceptability status of elements in a GRL model, based on the acceptability status of their underlying arguments and the evidence. We integrate the formal framework into the GRL metamodel and we set out a research to further develop this framework.","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":"132875948","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}
Jiale Zhou, Kaj Hänninen, K. Lundqvist, Yue Lu, Luciana Provenzano, K. Forsberg
The environment, where a safety critical system (SCS) operates, is an important source from which safety requirements of the SCS can originate. By treating the system under construction as a black box, the environment is typically documented as a number of assumptions, based on which a set of environmental safety requirements will be elicited. However, it is not a trivial task in practice to capture the environmental assumptions to elicit safety requirements. The lack of certain assumptions or too strict assumptions will either result in incomplete environmental safety requirements or waste many efforts on eliciting incorrect requirements. Moreover, the variety of operating environment for an SCS will further complicate the task, since the captured assumptions are at risk of invalidity, and consequently the elicited requirements need to be revisited to ensure safety has not been compromised by the change. This short paper presents an on-going work aiming to 1) systematically organize the knowledge of system operating environment and, 2) facilitate the elicitation of environmental safety requirements. We propose an ontological approach to achieve the objectives. In particular, we utilize conceptual ontologies to organize the environment knowledge in terms of relevant environment concepts, relations among them and axioms. Environmental assumptions are captured by instantiating the environment ontology. An ontological reasoning mechanism is also provided to support elicitation of safety requirements from the captured assumptions.
{"title":"An environment-driven ontological approach to requirements elicitation for safety-critical systems","authors":"Jiale Zhou, Kaj Hänninen, K. Lundqvist, Yue Lu, Luciana Provenzano, K. Forsberg","doi":"10.1109/RE.2015.7320431","DOIUrl":"https://doi.org/10.1109/RE.2015.7320431","url":null,"abstract":"The environment, where a safety critical system (SCS) operates, is an important source from which safety requirements of the SCS can originate. By treating the system under construction as a black box, the environment is typically documented as a number of assumptions, based on which a set of environmental safety requirements will be elicited. However, it is not a trivial task in practice to capture the environmental assumptions to elicit safety requirements. The lack of certain assumptions or too strict assumptions will either result in incomplete environmental safety requirements or waste many efforts on eliciting incorrect requirements. Moreover, the variety of operating environment for an SCS will further complicate the task, since the captured assumptions are at risk of invalidity, and consequently the elicited requirements need to be revisited to ensure safety has not been compromised by the change. This short paper presents an on-going work aiming to 1) systematically organize the knowledge of system operating environment and, 2) facilitate the elicitation of environmental safety requirements. We propose an ontological approach to achieve the objectives. In particular, we utilize conceptual ontologies to organize the environment knowledge in terms of relevant environment concepts, relations among them and axioms. Environmental assumptions are captured by instantiating the environment ontology. An ontological reasoning mechanism is also provided to support elicitation of safety requirements from the captured assumptions.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"165 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":"133183000","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}
We investigate a method to infer the implicit test status of requirements and thus increase the number of requirements for which the test status is known. The general idea is to improve the data set for measuring the maturity of the system in the current release. The inference is based on the structuring mechanisms (hierarchy, types) which are typically used to document the (natural language) requirements specification. We present a case study in the context of the development process for Mercedes-Benz passenger cars at Daimler AG. The results of the case study indicate the usefulness of the structuring mechanisms in the requirements specification as the basis for the inference. In particular, the number of requirements for which the status is known could be increased by almost a third.
{"title":"Using the requirements specification to infer the implicit test status of requirements","authors":"Tobias Morciniec, A. Podelski","doi":"10.1109/RE.2015.7320453","DOIUrl":"https://doi.org/10.1109/RE.2015.7320453","url":null,"abstract":"We investigate a method to infer the implicit test status of requirements and thus increase the number of requirements for which the test status is known. The general idea is to improve the data set for measuring the maturity of the system in the current release. The inference is based on the structuring mechanisms (hierarchy, types) which are typically used to document the (natural language) requirements specification. We present a case study in the context of the development process for Mercedes-Benz passenger cars at Daimler AG. The results of the case study indicate the usefulness of the structuring mechanisms in the requirements specification as the basis for the inference. In particular, the number of requirements for which the status is known could be increased by almost a third.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"3 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":"122163803","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}
Tong Li, E. Paja, J. Mylopoulos, Jennifer Horkoff, Kristian Beckers
The ever-growing complexity of systems makes their protection more challenging, as a single vulnerability or exposure of any component of the system can lead to serious security breaches. This problem is exacerbated by the fact that the system development community has not kept up with advances in attack knowledge. In this demo paper, we propose a holistic attack analysis approach to identify and tackle both atomic and multistage attacks, taking into account not only software attacks but also attacks that are targeted at people and hardware. To bridge the knowledge gap between attackers and defenders, we systematically analyze and refine the malicious desires of attackers (i.e., anti-goals), and leverage a comprehensive attack pattern repository (CAPEC) to operationalize attacker goals into concrete attack actions. Based on the results of our attack analysis, appropriate security controls can be selected to effectively tackle potential attacks.
{"title":"Holistic security requirements analysis: An attacker's perspective","authors":"Tong Li, E. Paja, J. Mylopoulos, Jennifer Horkoff, Kristian Beckers","doi":"10.1109/RE.2015.7320439","DOIUrl":"https://doi.org/10.1109/RE.2015.7320439","url":null,"abstract":"The ever-growing complexity of systems makes their protection more challenging, as a single vulnerability or exposure of any component of the system can lead to serious security breaches. This problem is exacerbated by the fact that the system development community has not kept up with advances in attack knowledge. In this demo paper, we propose a holistic attack analysis approach to identify and tackle both atomic and multistage attacks, taking into account not only software attacks but also attacks that are targeted at people and hardware. To bridge the knowledge gap between attackers and defenders, we systematically analyze and refine the malicious desires of attackers (i.e., anti-goals), and leverage a comprehensive attack pattern repository (CAPEC) to operationalize attacker goals into concrete attack actions. Based on the results of our attack analysis, appropriate security controls can be selected to effectively tackle potential attacks.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"87 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":"128957949","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}
Technology and knowledge have been recognized as main sources of competitive advantage of corporations, industries and nations, particularly in the software domain. They have led to the creation of local ecosystems devoted to development and transfer activities, which ensure not only personal and institutional motivation/recognition, but also social and economic gains. An open (ended) debate panel is proposed in order to develop greater awareness and seek deeper understanding of such activities from Requirements Engineering research to industrial practice. The panel involves researchers and practitioners with the perspective of eliciting: (i) experiences in knowledge and technology development and transfer; (ii) awareness and effectiveness of models and patterns; and (iii) factors for having successful collaboration between research institutions and industry. The organizers also plan to run a survey during and after the conference, summarizing their conclusions in specific post-conference reports.
{"title":"Technology transfer - Requirements Engineering research to industrial practice an open (ended) debate","authors":"C. H. C. Duarte, T. Gorschek","doi":"10.1109/RE.2015.7320462","DOIUrl":"https://doi.org/10.1109/RE.2015.7320462","url":null,"abstract":"Technology and knowledge have been recognized as main sources of competitive advantage of corporations, industries and nations, particularly in the software domain. They have led to the creation of local ecosystems devoted to development and transfer activities, which ensure not only personal and institutional motivation/recognition, but also social and economic gains. An open (ended) debate panel is proposed in order to develop greater awareness and seek deeper understanding of such activities from Requirements Engineering research to industrial practice. The panel involves researchers and practitioners with the perspective of eliciting: (i) experiences in knowledge and technology development and transfer; (ii) awareness and effectiveness of models and patterns; and (iii) factors for having successful collaboration between research institutions and industry. The organizers also plan to run a survey during and after the conference, summarizing their conclusions in specific post-conference reports.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"40 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":"121170725","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}
In requirements engineering literature dealing with natural language specifications, we usually find writing rules like `avoid passive voice' or `do not use weak words'. Adhering to such rules should result in understandable and unambiguous requirements. Passive voice, especially when used without an explicit actor, is considered to result in incomplete requirements. The usage of weak words is considered to result in imprecise requirements that are hardly testable. But is the inversion of the claim correct, i.e. does the violation of the writing rules result in problematic specifications? At least in our environment (the passenger car development of Mercedes-Benz) we observe that authors often use passive voice, and there are many requirements containing weak words. To answer this question, we conducted an empirical investigation whose results we report in this paper. The results of this investigation are quite surprising: The use of passive voice, even when the actor is missing, is almost never problematic, as the missing information (the actor) can in most cases easily derived from the context (i.e. surrounding requirements or the general project context). The usage of weak words may be considered problematic in approximately 12% of all occurrences. For an automatic analysis on weak words linguistic patterns can be defined to detect these problematic occurences.
{"title":"The myth of bad passive voice and weak words an empirical investigation in the automotive industry","authors":"J. Krisch, F. Houdek","doi":"10.1109/RE.2015.7320451","DOIUrl":"https://doi.org/10.1109/RE.2015.7320451","url":null,"abstract":"In requirements engineering literature dealing with natural language specifications, we usually find writing rules like `avoid passive voice' or `do not use weak words'. Adhering to such rules should result in understandable and unambiguous requirements. Passive voice, especially when used without an explicit actor, is considered to result in incomplete requirements. The usage of weak words is considered to result in imprecise requirements that are hardly testable. But is the inversion of the claim correct, i.e. does the violation of the writing rules result in problematic specifications? At least in our environment (the passenger car development of Mercedes-Benz) we observe that authors often use passive voice, and there are many requirements containing weak words. To answer this question, we conducted an empirical investigation whose results we report in this paper. The results of this investigation are quite surprising: The use of passive voice, even when the actor is missing, is almost never problematic, as the missing information (the actor) can in most cases easily derived from the context (i.e. surrounding requirements or the general project context). The usage of weak words may be considered problematic in approximately 12% of all occurrences. For an automatic analysis on weak words linguistic patterns can be defined to detect these problematic occurences.","PeriodicalId":132568,"journal":{"name":"2015 IEEE 23rd International Requirements Engineering Conference (RE)","volume":"13 11 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":"132925189","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}
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