Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch031
Priyanka Chandani, Chetna Gupta
Accurate time and budget is an essential estimate for planning software projects correctly. Quite often, the software projects fall into unrealistic estimates and the core reason generally owes to problems with the requirement analysis. For investigating such problems, risk has to identified and assessed at the requirement engineering phase only so that defects do not seep down to other software development phases. This article proposes a multi-criteria risk assessment model to compute risk at a requirement level by computing cumulative risk score based on a weighted score assigned to each criterion. The result of comparison with other approaches and experimentation shows that using this model it is possible to predict the risk at the early phase of software development life cycle with high accuracy.
{"title":"An Early Multi-Criteria Risk Assessment Model","authors":"Priyanka Chandani, Chetna Gupta","doi":"10.4018/978-1-6684-3702-5.ch031","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch031","url":null,"abstract":"Accurate time and budget is an essential estimate for planning software projects correctly. Quite often, the software projects fall into unrealistic estimates and the core reason generally owes to problems with the requirement analysis. For investigating such problems, risk has to identified and assessed at the requirement engineering phase only so that defects do not seep down to other software development phases. This article proposes a multi-criteria risk assessment model to compute risk at a requirement level by computing cumulative risk score based on a weighted score assigned to each criterion. The result of comparison with other approaches and experimentation shows that using this model it is possible to predict the risk at the early phase of software development life cycle with high accuracy.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129728943","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch061
Sonali Pradhan, M. Ray, S. Patnaik
State-based testing (SBT) is known as deriving test cases from state machines and examining the dynamic behaviour of the system. It helps to identify various types of state-based faults within a system under test (SUT). For SBT, test cases are generated from state chart diagrams based on various coverage criteria such as All Transition, Round Trip Path, All Transition Pair, All Transition Pair with length 2, All Transition Pair with length 3, All Transition Pair of length 4 and Full Predicate. This article discuses a number of coverage criteria at the design level to find out various types of state-based faults in SBT. First, the intermediate graph is generated from a state chart diagram using an XML parser. The graph is traversed based on the given coverage criteria to generate a sequence of test cases. Then, mutation testing and sneak-path testing are applied on the generated test cases to check the effectiveness of the generated test suite. These two are common methods for checking the effectiveness of test cases. Mutation testing helps in the number of seeded errors covered whereas sneak-path testing basically helps to examine the unspecified behavior of the system. In round trip path (RTP), it is not possible to cover all paths. All transition is not an adequate level of fault detection with more execution time compared to all transition pair (ATP) with length 4 (LN4). In the discussion, ATP with LN4 is the best among all coverage criteria. SBT can able to detect various state-based faults-incorrect transition, missing transition, missing or incorrect event, missing or incorrect action, extra missing or corrupt state, which are difficult to detect in code-based testing. Most of these state-based faults can be avoided, if the testing is conducted at the early phase of design.
{"title":"Coverage Criteria for State-Based Testing","authors":"Sonali Pradhan, M. Ray, S. Patnaik","doi":"10.4018/978-1-6684-3702-5.ch061","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch061","url":null,"abstract":"State-based testing (SBT) is known as deriving test cases from state machines and examining the dynamic behaviour of the system. It helps to identify various types of state-based faults within a system under test (SUT). For SBT, test cases are generated from state chart diagrams based on various coverage criteria such as All Transition, Round Trip Path, All Transition Pair, All Transition Pair with length 2, All Transition Pair with length 3, All Transition Pair of length 4 and Full Predicate. This article discuses a number of coverage criteria at the design level to find out various types of state-based faults in SBT. First, the intermediate graph is generated from a state chart diagram using an XML parser. The graph is traversed based on the given coverage criteria to generate a sequence of test cases. Then, mutation testing and sneak-path testing are applied on the generated test cases to check the effectiveness of the generated test suite. These two are common methods for checking the effectiveness of test cases. Mutation testing helps in the number of seeded errors covered whereas sneak-path testing basically helps to examine the unspecified behavior of the system. In round trip path (RTP), it is not possible to cover all paths. All transition is not an adequate level of fault detection with more execution time compared to all transition pair (ATP) with length 4 (LN4). In the discussion, ATP with LN4 is the best among all coverage criteria. SBT can able to detect various state-based faults-incorrect transition, missing transition, missing or incorrect event, missing or incorrect action, extra missing or corrupt state, which are difficult to detect in code-based testing. Most of these state-based faults can be avoided, if the testing is conducted at the early phase of design.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127985273","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch101
Narendranath Shanbhag, E. Pardede
Software startups are increasingly under high pressure to deliver successful products to survive and thrive in the modern highly competitive technology market. Larger organizations with deep pockets can replicate the same business ideas used by startups with relative ease. So how does the average startup stand a chance at succeeding at this seemingly David vs. Goliath contest? This article looks at the available literature and identifies such factors that can affect the success of software development startups. Using causal loop constructs from the field of system dynamics, the interactions among the various identified factors are visualised to reveal the dynamics of the system. The result is as a three-dimensional view of success factors in form of time, capital and (product) differentiation. The modelled system is then simulated, and the resultant trend is reviewed and interpreted. This research acts as ground work for analysing the workings of software development startups and sets the stage for a more holistic study of the area, upon which further research can be carried out.
{"title":"The Dynamics of Product Development in Software Startups","authors":"Narendranath Shanbhag, E. Pardede","doi":"10.4018/978-1-6684-3702-5.ch101","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch101","url":null,"abstract":"Software startups are increasingly under high pressure to deliver successful products to survive and thrive in the modern highly competitive technology market. Larger organizations with deep pockets can replicate the same business ideas used by startups with relative ease. So how does the average startup stand a chance at succeeding at this seemingly David vs. Goliath contest? This article looks at the available literature and identifies such factors that can affect the success of software development startups. Using causal loop constructs from the field of system dynamics, the interactions among the various identified factors are visualised to reveal the dynamics of the system. The result is as a three-dimensional view of success factors in form of time, capital and (product) differentiation. The modelled system is then simulated, and the resultant trend is reviewed and interpreted. This research acts as ground work for analysing the workings of software development startups and sets the stage for a more holistic study of the area, upon which further research can be carried out.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127285305","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch054
Pekka Mäkiaho, Katriina Vartiainen, T. Poranen
This paper presents the Metrics Monitoring Tool (MMT) that was developed in university graduate and undergraduate courses on software project work in 2014-2016. The tool aims to support project members, project managers and upper management in reporting and monitoring software and project metrics for their easier and more effective utilization. The paper covers the development process of the tool, evaluation assessment, its current composition and features. The paradigm applied in this study is Design Science Research and the methods for evaluation include prototype, expert evaluation, case study and technical experiment. Data was collected from the tool users by two questionnaires. As a result, MMT was evaluated to ease the metrics handling, while several aspects related to the richness of functionalities and usability still require further development.
{"title":"MMT","authors":"Pekka Mäkiaho, Katriina Vartiainen, T. Poranen","doi":"10.4018/978-1-6684-3702-5.ch054","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch054","url":null,"abstract":"This paper presents the Metrics Monitoring Tool (MMT) that was developed in university graduate and undergraduate courses on software project work in 2014-2016. The tool aims to support project members, project managers and upper management in reporting and monitoring software and project metrics for their easier and more effective utilization. The paper covers the development process of the tool, evaluation assessment, its current composition and features. The paradigm applied in this study is Design Science Research and the methods for evaluation include prototype, expert evaluation, case study and technical experiment. Data was collected from the tool users by two questionnaires. As a result, MMT was evaluated to ease the metrics handling, while several aspects related to the richness of functionalities and usability still require further development.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117353944","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch074
Rafael A. Gonzalez, Marisela Vargas, Florentino Malaver, Efraín Ortiz
This case study presents the evolution of a software firm from startup into early internationalization. Building on a structuration theory, the case is framed within a conceptual model that illustrates the way skills and routines co-evolve both at the level of the founding entrepreneur (agency) and of the firm (structure). As such, this article contributes to an emergent structurational view of technology-based entrepreneurship. Such views places emphasis on learning both at the individual and collective level, in terms of software engineering, commercial, managerial and strategic capabilities. In addition, it supports a dynamic perspective of entrepreneurship in the software industry by covering not only the startup phase but also early growth and consolidation of the firm.
{"title":"Structuration and Learning in a Software Firm","authors":"Rafael A. Gonzalez, Marisela Vargas, Florentino Malaver, Efraín Ortiz","doi":"10.4018/978-1-6684-3702-5.ch074","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch074","url":null,"abstract":"This case study presents the evolution of a software firm from startup into early internationalization. Building on a structuration theory, the case is framed within a conceptual model that illustrates the way skills and routines co-evolve both at the level of the founding entrepreneur (agency) and of the firm (structure). As such, this article contributes to an emergent structurational view of technology-based entrepreneurship. Such views places emphasis on learning both at the individual and collective level, in terms of software engineering, commercial, managerial and strategic capabilities. In addition, it supports a dynamic perspective of entrepreneurship in the software industry by covering not only the startup phase but also early growth and consolidation of the firm.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"496 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120864433","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch017
Venugopal Balijepally, Gerald DeHondt, V. Sugumaran, S. Nerur
Agile Development Methods, considered as an alternative to the traditional plan-based methods, have received much attention since their inception. These practices have evolved and developed over time, culminating in 2001 with the Agile Manifesto. Since that time, preferred methodologies, implementations, and best practices have continued to evolve with a focus on doing what works best for the individual company or project. However, the concept of agility in software development has remained quite nebulous, lacking in clarity particularly about its underlying dimensions. In this research the authors conceive agility in terms of four distinct dimensions. Drawing from the theoretical perspective of holographic organization, they develop a model explaining how each of these underlying dimensions of agility contributes to project value in software teams. The authors test the model using survey data collected from industry practitioners and discuss findings.
{"title":"Agility in Software Development and Project Value","authors":"Venugopal Balijepally, Gerald DeHondt, V. Sugumaran, S. Nerur","doi":"10.4018/978-1-6684-3702-5.ch017","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch017","url":null,"abstract":"Agile Development Methods, considered as an alternative to the traditional plan-based methods, have received much attention since their inception. These practices have evolved and developed over time, culminating in 2001 with the Agile Manifesto. Since that time, preferred methodologies, implementations, and best practices have continued to evolve with a focus on doing what works best for the individual company or project. However, the concept of agility in software development has remained quite nebulous, lacking in clarity particularly about its underlying dimensions. In this research the authors conceive agility in terms of four distinct dimensions. Drawing from the theoretical perspective of holographic organization, they develop a model explaining how each of these underlying dimensions of agility contributes to project value in software teams. The authors test the model using survey data collected from industry practitioners and discuss findings.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"52 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114326373","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch049
Charles B. Tichenor
Using the lines of code (LOC) metric in software project management can be a financial moral hazard to an organization. This is especially true for upper management who handles an organizational budget and strategic plan. Software project managers have their own budgets. However, if they fail to meet the budget, the organization's cash flow, rather than the project manager's personal cash flow, will suffer. This chapter will discuss the practice of software project management, the field of software metrics, game theory, and the game theory issue of moral hazard. It will demonstrate why using LOC as a metric can present a moral hazard to senior management and an organization.
{"title":"The Mythical Lines of Code Metric","authors":"Charles B. Tichenor","doi":"10.4018/978-1-6684-3702-5.ch049","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch049","url":null,"abstract":"Using the lines of code (LOC) metric in software project management can be a financial moral hazard to an organization. This is especially true for upper management who handles an organizational budget and strategic plan. Software project managers have their own budgets. However, if they fail to meet the budget, the organization's cash flow, rather than the project manager's personal cash flow, will suffer. This chapter will discuss the practice of software project management, the field of software metrics, game theory, and the game theory issue of moral hazard. It will demonstrate why using LOC as a metric can present a moral hazard to senior management and an organization.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120923522","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-5225-6029-6.CH002
Rimsy Dua, Samiksha Sharma, Rohit Kumar
This chapter describes how risk management deals with the detection, the evaluation and the precedence of the risks in the process of project management. There is always an uncertainty factor related to the decisions of an investment while managing a project. Risk management is a proactive approach to deal with such future events that can lead to slow performance of the software project management. For successful risk management; there are different metrics that have been used in the past and are being getting used in the present for inspecting the progress of a project at specific points in a timeline that help in reducing the amount of risk. For the adoption of effective metrics for risk management, data is required. All of the metrics can be applied to the different domains of project, process and product. The chapter also covers strategies to advance, distinguish, estimate, and forecast the risk management process. A review of the key point indicators (KPIs) are also integrated along with the project metrics to signify the future and the present renderings.
{"title":"Risk Management Metrics","authors":"Rimsy Dua, Samiksha Sharma, Rohit Kumar","doi":"10.4018/978-1-5225-6029-6.CH002","DOIUrl":"https://doi.org/10.4018/978-1-5225-6029-6.CH002","url":null,"abstract":"This chapter describes how risk management deals with the detection, the evaluation and the precedence of the risks in the process of project management. There is always an uncertainty factor related to the decisions of an investment while managing a project. Risk management is a proactive approach to deal with such future events that can lead to slow performance of the software project management. For successful risk management; there are different metrics that have been used in the past and are being getting used in the present for inspecting the progress of a project at specific points in a timeline that help in reducing the amount of risk. For the adoption of effective metrics for risk management, data is required. All of the metrics can be applied to the different domains of project, process and product. The chapter also covers strategies to advance, distinguish, estimate, and forecast the risk management process. A review of the key point indicators (KPIs) are also integrated along with the project metrics to signify the future and the present renderings.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115572516","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch064
Venugopal Balijepally, S. Nerur
Software development is a problem-solving activity, where ideas are combined in complex ways to create a software product that embodies new knowledge. In this endeavor, software developers constantly look for actionable knowledge to help solve the problem at hand. While knowledge management efforts in the software development domain traditionally involved technical initiatives such as knowledge repositories, experience factories, and lessons-to-learn databases, there is a growing appreciation in the software community of the role of developers' personal knowledge networks in software development. However, research is scarce on the nature of these networks, the knowledge resources accessed from these networks, and the differences, if any, between developers of different experience levels. This research seeks to fill this void. Based on a case study in a software development organization, this research explores the nature of knowledge networks of developers from a social capital perspective. Specifically, it examines the structural and relational dimensions of developers' knowledge networks, identifies the specific actionable knowledge resources accessed from these networks, and explores how entry-level and more experienced developers differ along these dimensions. The findings from the qualitative analysis, backed by limited quantitative analysis of the case study data underpin the discussion, implications for practice and future research directions.
{"title":"Social Capital and Knowledge Networks of Software Developers","authors":"Venugopal Balijepally, S. Nerur","doi":"10.4018/978-1-6684-3702-5.ch064","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch064","url":null,"abstract":"Software development is a problem-solving activity, where ideas are combined in complex ways to create a software product that embodies new knowledge. In this endeavor, software developers constantly look for actionable knowledge to help solve the problem at hand. While knowledge management efforts in the software development domain traditionally involved technical initiatives such as knowledge repositories, experience factories, and lessons-to-learn databases, there is a growing appreciation in the software community of the role of developers' personal knowledge networks in software development. However, research is scarce on the nature of these networks, the knowledge resources accessed from these networks, and the differences, if any, between developers of different experience levels. This research seeks to fill this void. Based on a case study in a software development organization, this research explores the nature of knowledge networks of developers from a social capital perspective. Specifically, it examines the structural and relational dimensions of developers' knowledge networks, identifies the specific actionable knowledge resources accessed from these networks, and explores how entry-level and more experienced developers differ along these dimensions. The findings from the qualitative analysis, backed by limited quantitative analysis of the case study data underpin the discussion, implications for practice and future research directions.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"21 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726672","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}
Pub Date : 1900-01-01DOI: 10.4018/978-1-6684-3702-5.ch082
Idongesit Williams, Albert Gyamfi
Software programming is a task with high analyzability. However, knowledge sharing is an intricate part of the software programming process. Today, new media platforms have been adopted to enable knowledge sharing between virtual teams. Taking into consideration the high task analyzability and the task characteristics involved in software development, the question is if the media richness of the current media platform is effective in enabling knowledge sharing among these virtual teams? An exploratory research was conducted on a software company in Denmark. The data was gathered was analyzed qualitatively using narrative analysis. This paper concludes, based on the case being investigated, that rich media does not fit the task characteristics of a software programmer. It further concludes that Media richness does affect knowledge sharing in these virtual teams. This is because the current lean media actually enables knowledge sharing as it fits the core characteristics of the software programming process.
{"title":"Media Richness, Knowledge Sharing, and Computer Programming by Virtual Software Teams","authors":"Idongesit Williams, Albert Gyamfi","doi":"10.4018/978-1-6684-3702-5.ch082","DOIUrl":"https://doi.org/10.4018/978-1-6684-3702-5.ch082","url":null,"abstract":"Software programming is a task with high analyzability. However, knowledge sharing is an intricate part of the software programming process. Today, new media platforms have been adopted to enable knowledge sharing between virtual teams. Taking into consideration the high task analyzability and the task characteristics involved in software development, the question is if the media richness of the current media platform is effective in enabling knowledge sharing among these virtual teams? An exploratory research was conducted on a software company in Denmark. The data was gathered was analyzed qualitatively using narrative analysis. This paper concludes, based on the case being investigated, that rich media does not fit the task characteristics of a software programmer. It further concludes that Media richness does affect knowledge sharing in these virtual teams. This is because the current lean media actually enables knowledge sharing as it fits the core characteristics of the software programming process.","PeriodicalId":429458,"journal":{"name":"Research Anthology on Agile Software, Software Development, and Testing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121927561","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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