Managing requirements in market-driven software project: Agile methods view

Vrijeme do plasiranja na tržište i nedovoljno početno saznanje o potrebama dva su značajna problema po kojima se organiziranje potreba kod projekata razvijanja softvera za tržište razlikuje od projekata za softver po narudžbi. Ti se problemi mogu riješiti primjenom agilnih metodologija razvoja softvera kad se radi o tržišno orijentiranom softveru budući da Agilne metode naglašavaju dinamički pristup organiziranju potreba usko povezan s iterativnim ciklusom isporuke. U ovom radu, dinamički pristup Agilnih metoda definiranju potreba koristi se za uspješnu implementaciju složenog tržišno orijentiranog softverskog projekta.Time-to-market and insufficient initial requirements are two significant challenges that make managing requirements for market-driven software projects different from custom-made software projects. These challenges can be resolved by using agile software development methodologies for market-driven software development as agile methods put emphasis on a dynamic approach for requirement engineering which works closely with an iterative release cycle. In this study, dynamic requirement engineering approach of Agile methods was used for the successful implementation of market-driven complex software project

A Study of Designer Familiarity with Product and User During Requirement Elicitation

It is important to recognise the effects of a designer\u27s source of information and decision making during requirements elicitation. Requirements are widely recognised as an important step in the design process. Designers may have perspective based on their experience which results in a level of familiarity with the design. This paper reports on a study that explores the effects of designer familiarity with a project and its user on their ability to elicit requirement specifications. Two familiarity constructs, product and user, are measured as low or high and used to study requirement elicitation with varying familiarity. A high familiarity study using five graduate students and a low familiarity study using a team of five students during senior capstone design are compared for their requirements elicitation. The results of this study include an analysis of the requirements developed and participant survey results from the elicitation process. The results revealed familiarity does in fact have an effect on the ability of elicit requirements. Participants in the low familiarity study expressed difficulty and eliciting requirements while those in the high familiarity study were able to generate more requirements at a faster rate

Computational Representation And Reasoning Support For Requirements Change Management In Complex System Design

Requirements play a critical role within any design process and the activity of identifying and maintaining a system\u27s requirements is essential to. However, design is a complex and iterative process, where requirements are continuously evolving and are volatile. This change, if not managed, may result in undesired uncertainty within the design process leading to monetary losses and time delays, as the changing of requirements has been recognized as a major cause of project failure. In order to mitigate issues that arise due to requirement change propagation, this research presents a computational reasoning tool to help designers and engineers predict change propagation in the requirements domain. The developed tool makes use of requirements syntactical elements to build relationships between requirements. Two heterogeneous industry case studies, spanning four engineering change propagations, are used to both explore the use of requirements in predicting change propagation and generalize an automated prediction tool. Using design structure matrices and graph theoretic based metrics a predictive model is generalized from 491,520 relationship and metric permutation combinations. The developed tool makes use of an RMS scoring algorithm to rank requirements in order of most likely to change due to previous requirement changes. The developed tool is tested against a third industry case study where five engineering changes are predicted. Results indicate the tool can predict sixty percent of change propagation within the top four percent requirements scoring and predict all change propagation within the top thirteen percent scoring