Context: User stories have been widely accepted as artifacts to capture the user requirements in agile software development. They are short pieces of texts in a semi-structured format that express requirements. Natural language processing (NLP) techniques offer a potential advantage in user story applications. Objective: Conduct a systematic literature review to capture the current state-of-the-art of NLP research on user stories. Method: The search strategy is used to obtain relevant papers from SCOPUS, ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar. Inclusion and exclusion criteria are applied to filter the search results. We also use the forward and backward snowballing techniques to obtain more comprehensive results. Results: The search results identified 718 papers published between January 2009 to December 2020. After applying the inclusion/exclusion criteria and the snowballing technique, we identified 38 primary studies that discuss NLP techniques in user stories. Most studies used NLP techniques to extract aspects of who, what, and why from user stories. The purpose of NLP studies in user stories is broad, ranging from discovering defects, generating software artifacts, identifying the key abstraction of user stories, and tracing links between model and user stories. Conclusion: NLP can help system analysts manage user stories. Implementing NLP in user stories has many opportunities and challenges. Considering the exploration of NLP techniques and rigorous evaluation methods is required to obtain quality research. As with NLP research in general, the ability to understand a sentence’s context continues to be a challenge.

/pdf/user-stories-and-natural-language-processing-a-systematic-2atf5mds3e.pdf

User Stories and Natural Language Processing: A Systematic Literature Review

User stories are a widely used artifact in Agile software development. Currently, only a limited number of secondary studies have reviewed the research on the user story technique. These research reviews focused on specific research topics related to ambiguity of requirements, effort estimation, and the application of Natural Language Processing. To our knowledge, a systematic mapping of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">all</i> user story research has not been performed. To this end, we study the academic literature to investigate what user stories research has been performed, what types of problems have been identified, what sort of solutions or other types of research outcomes have been achieved, how mature the research is, and what research gaps exist. We followed Systematic Mapping Study guidelines to synthesize the currently available academic research on user stories. In total, we found 186 unique peer-reviewed studies, published in the period 2001-2021. We observed that research on the user story technique and its use had grown exponentially over the last seven years. Further, using a five-dimensional classification framework– requirements engineering activity, problem class, outcome class, type of research, type of publication– we observed several patterns in the classification of these studies across the different framework dimensions, which provided insights into the state-of-the-art and maturity of the research. We also identified four research gaps: the paucity of focused literature reviews; a lack of research on the role that user stories play in human cognition and interaction; a lack of comprehensive and mature solutions for resolving ambiguity issues with user stories early in the project; and a lack of validation and evaluation of proposed solutions. Several research opportunities are suggested, making our paper a useful reference for future research on user stories allowing researchers to clearly position their contributions. 

/pdf/systematic-literature-mapping-of-user-story-research-2r104lj0.pdf

Systematic Literature Mapping of User Story Research

User stories are a widely used artifact in Agile software development. Currently, only a limited number of secondary studies have reviewed the research on the user story technique. These research reviews focused on specific research topics related to ambiguity of requirements, effort estimation, and the application of Natural Language Processing. To our knowledge, a systematic mapping of all user story research has not been performed. To this end, we study the academic literature to investigate what user stories research has been performed, what types of problems have been identified, what sort of solutions or other types of research outcomes have been achieved, how mature the research is, and what research gaps exist. We followed Systematic Mapping Study guidelines to synthesize the currently available academic research on user stories. In total, we found 186 unique peer-reviewed studies, published in the period 2001-2021. We observed that research on the user story technique and its use had grown exponentially over the last seven years. Further, using a five-dimensional classification framework– requirements engineering activity, problem class, outcome class, type of research, type of publication– we observed several patterns in the classification of these studies across the different framework dimensions, which provided insights into the state-of-the-art and maturity of the research. We also identified four research gaps: the paucity of focused literature reviews; a lack of research on the role that user stories play in human cognition and interaction; a lack of comprehensive and mature solutions for resolving ambiguity issues with user stories early in the project; and a lack of validation and evaluation of proposed solutions. Several research opportunities are suggested, making our paper a useful reference for future research on user stories allowing researchers to clearly position their contributions.

the agile software development process has a set of standard agile ceremonies, which are must for an agile team to conduct in order to preserve its agility. However, there is always a challenge for agile teams to decide how much agile sprint time should be spent on hosting agile ceremonies and agile product build tasks. This is due to the fact that if most of the agile sprint time is spent on hosting agile ceremonies then the time for agile product build tasks will be reduced significantly impacting the velocity of the agile team. Hence, there is a need to find a solution with the help of which agile team can strike a right balance among various agile ceremonies and agile product build tasks during a sprint. To overcome this gap, this research paper analyses the data for 14 agile sprints to understand the agile time distribution across agile sprint ceremonies and agile product build tasks under current approach. Because of which, this research paper proposes the values for two newly introduced agile co-efficient namely coefficient of agile ceremony time and co-efficient of agile product build time to suggest the ideal time to be spent on agile ceremonies during a sprint. From the research results, it was evident that the velocity of the agile team following the proposed approach reported an increase in velocity by 13.96% for sprints when compared to the velocity of the agile team following the existing approach. The research work also highlighted that the duration chosen for agile ceremony by agile teams is independent of sprint lengths.

An Impact Assessment of Agile Ceremonies on Sprint Velocity Under Agile Software Development

Product backlog optimization technique in agile software development using clustering algorithm

once the requirement is gathered in agile, it is broken down into smaller pre-defined format called user stories. These user stories are then scoped in various sprint releases and delivered accordingly. Release planning in Agile becomes challenging when the number of user stories goes up in hundreds. In such scenarios it is very difficult to manually identify similar user stories and package them together into a release. Hence, this paper suggests application of natural language processing algorithms for identifying similar user stories and then scoping them into a release This paper takes the approach to build a word corpus for every project release identified in the project and then to convert the provided user stories into a vector of string using Java utility for calculating top 3 most occurring words from the given project corpus in a user story. Once all the user stories are represented as vector array then by using RV coefficient NLP algorithm the user stories are clustered into various releases of the software project. Using the proposed approach, the release planning for large and complex software engineering projects can be simplified resulting into efficient planning in less time. The automated commercial tools like JIRA and Rally can be enhanced to include suggested algorithms for managing release planning in Agile.

Agile Release Planning Using Natural Language Processing Algorithm

AGILE methodology is widely used throughout the information technology industry for software development In AGILE methodology, the delivery cycle is broken down into sprints or iterations Many iteration-based AGILE teams use a time-boxed 1-hour discussion midway through a 2-week iteration (the team selects an iteration duration that provides them frequent enough feedback) (Cohn in AGILE Estimating and Planning, 2005 [1]) A sprint or iteration is expected to deliver a piece of functionality within a fixed period of time The length of AGILE sprint is measured in number of days Hence, it can be concluded that the unit of sprint is time, measured in numbers of days But since AGILE is feature-driven, the unit of sprint should not be limited to time There is a need to explore other measures that can be used to define or determine the length of the AGILE sprint The purpose of this paper is to find out any other unit to define or derive the length of sprint The paper also explores the various ways in which the AGILE developer(s), AGILE tester(s), and AGILE end user(s) can be benefited by changing the unit of sprint length from time to something else This paper particularly talks about the possibility of using the “feature” as unit of sprint and lists down the advantages and disadvantages of using “feature” over “time” as unit of sprint The term “sprint” or “iteration” is used as synonyms throughout the discussion

On the Development of Feature-Based Sprint in AGILE

every software development project is unique but still shares some similarities with other projects in terms of domain, database used, programming language employed, etc. Based upon which a lot of work has been done so far to predict project size, efforts required, budget required to build the software project using historical data. But, a very less attention has been given in modeling world to analyze the skills of agile team responsible for software project development. Hence, this paper suggests a simplified agile software project selection model using natural language processing based upon the agile team skills named as "Stair-case Model". After all it is the capability of agile team to deliver the project on time within budget. A strong skilled agile team having relevant experience has brighter chances to deliver the quality project on time and vice-versa.

Sarika Sharma

Papers

Agile Release Planning Using Natural Language Processing Algorithm

On the Development of Feature-Based Sprint in AGILE

Simplified Agile Software Project Selection Model Using Natural Language Processing Based Upon Agile Team Skills