Systematic Literature Review of Lean Tools Applied to Software Development

Currently, the predominance of Agile frameworks in software development means that Lean applications in the IT sector are incipient or very little known. However, several authors argue that the application of Lean in software has more advantages than Agile could have, due to the scalability of the procedures. The objective of this research is to know the state of the art of the application of Lean in software development through a systematic literature review. After reviewing 19 articles, it was found that the most common Lean waste with the greatest impact on software development is waiting. The main barriers that hinder the application of Lean correspond to attitudinal components of people such as low understanding of Lean concepts. The most applied Lean tool is Kanban and the main advantage of applying Lean in software development is the improvement of team performance

Assessing the Impact of Empirical Process Control Metrics in Agile Software Development - A Framework based on Improvement Capability

Empirical process control is an integral part of agile software development. A multitude of development metrics has been proposed to implement it. However, the efficacy of control metrics has remained unclear and empirical evidence of their impact is scarce. Methods for assessing whether and how a proposed metric stimulates the improvement of a development process are not yet available. We conduct a design science approach to develop an artifact that assesses the impact of development metrics and we identify their contribution for process improvement at a global software vendor. We draw on the theoretical construct of improvement capability to outline design principles of a measurement framework. Our evaluation of five large-scale agile development projects demonstrates that our framework facilitates to implement development metrics more effectively. The framework has the potential to improve large-scale agile software development and it serves as a useful basis for future empirical research on development metrics

Enhancement of software project performance by overcoming waste, volatility and constraints simultaneously

There have been many projects and researches conducted to identify software projects’ failure and success factors. The success factors were always remained as best practices as it favours desired results while the failure factors are always avoided as it yields undesired factors. However, it is least understood that focusing on avoiding a failure factor could actually influence other forms of failure risk(s). In this study, it has been understood through literature review that most of the findings on software projects failure factors have been repetitive for more than two decades. These failure factors commonality was then understood and categorized by bridging few studies and experts’ opinions based on three well-known theories; Lean, Requirement Volatility and Theory of Constraints. There are nine types of wastes, three types errors that leads to requirement volatility and eight types of constraints in relevance to software projects. Through literature and discussion with 15 experts it was apparent that there could be interdependency and interrelationship amongst these 20 variables. The relationship amongst the variables were studied by employing the DEMATEL methodology. DEMATEL was opted to show the Impact Relation Map which could serve as a good source of reference to help decision makers formulate their decisions pertaining these 20 variables. A Software Project Success Framework was then developed to assist the foundation for planning and prioritizing relevant mitigations and corrective measures about software projects failure factors. Requirement volatility has been emphasized as the main cause of software project failure. It does not only cause direct impact towards software projects failure but also influences other identified factors to affect the sotware project performance adversely

A literature review and Research Agenda of Value Stream Mapping addressing Study Population and Sample Design

The Purpose of this literature review is to provide a taxonomy of value stream mapping research and, based on that, to develop a research agenda for this field of study in relation to study population and research design. The proposed value stream mapping research classification framework is based on a comprehensive literature review, which concentrates on peer-reviewed journal papers published within the period 2002-2020. A total of 83 academic sources have been retrieved and analyzed interms of research purpose and nature, methodology employed, theoretical approach and level of analysis. The review reveals that value stream mapping research is empirical-descriptive in nature and that it generally lacks a sampling design foundation and a tin study population. It identifies certain knowledge gaps and develops sixe propositions for future research. It suggests that focus should be directed towards more conceptual model, mathematical model, interviews, empirical triangulation (mixed methods) and simulation based studies. It also argues that further empirical research in relation to value stream mapping in relation to study population and sample design needed. This paper fulfils an identified need for a comprehensive classification framework of value stream mapping studies. It essentially provides both academics and practitioners with a conceptual map of existing value stream mapping research and also points out opportunities for future research

Process analysis and optimization

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FLOW-assisted value stream mapping in the early phases of large-scale software development

Value stream mapping (VSM) has been successfully applied in the context of software process improvement. However, its current adaptations from Lean manufacturing focus mostly on the flow of artifacts and have taken no account of the essential information flows in software development. A solution specifically targeted toward information flow elicitation and modeling is FLOW. This paper aims to propose and evaluate the combination of VSM and FLOW to identify and alleviate information and communication related challenges in large-scale software development. Using case study research, FLOW-assisted VSM was used for a large product at Ericsson AB, Sweden. Both the process and the outcome of FLOW-assisted VSM have been evaluated from the practitioners’ perspective. It was noted that FLOW helped to systematically identify challenges and improvements related to information flow. Practitioners responded favorably to the use of VSM and FLOW, acknowledged the realistic nature and impact on the improvement on software quality, and found the overview of the entire process using the FLOW notation very useful. The combination of FLOW and VSM presented in this study was successful in systematically uncovering issues and characterizing their solutions, indicating their practical usefulness for waste removal with a focus on information flow related issues

A Framework for Evaluating Technology-Mediated Collaborative Workflow

The adoption of new technology into collaborative workflows has permeated every aspect of our personal and professional lives with the promise of performing work processes more efficiently and with greater capability. The continued rise of ubiquitous computing and heightened need for collaborative features suggest that a view of enabling technologies in a workflow should include the physical computing infrastructure, the collaborative interaction between humans and computers, and the informatics (i.e., collection and representation of data within the workflow). The development and integration of technology for collaborative workflows introduces many variables that are of great concern to companies, organization, and individuals. These variables include the costs of development, the switching cost associated with migrating from the current workflow to the technology-enhanced workflow, and details of how the technology-mediated workflow functions compare to the current workflow functions. There is, however, no consistent, generalizable approach to evaluate and compare an existing workflow with the enhanced technology-mediated workflow in a manner that identifies improvements and barriers in replicable qualitative and quantitative measures. In order to develop such a consistent, generalizable approach, this research investigates what necessary set of cross-disciplinary metrics and methodology is required to effectively evaluate technology-mediated collaborative workflow through an analysis of related works from four disciplines (Social Sciences, Organization and Behavioral Management, Industrial Engineering, and Human-Computer Interaction). The research introduces the Collaborative Space – Analysis Framework (CS-AF), a cross-disciplinary model and methodology designed to evaluate and compare collaborative workflows. The research includes testing the CS-AF model using two diverse empirical studies designed to evaluate a current-state workflow, compared to a technology-mediated workflow on five key collaborative areas (Context, Technology, Process, Attitude and Behavior, and Outcomes). The research incorporates the CS-AF model and methodology to test the effectiveness of the approach for capturing and analyzing essential quantitative and qualitative parameters of the collaborative workflows. The second empirical study tested hypertensive patients currently involved in clinical maintenance with regular outpatient monitoring. The test included 50 hypertension patients, selected based on matched-pairs for age and gender to test the workflow model in a 3-week trial. All participants were tested on an existing workflow (current-state), then the population was randomly split within pairs. The matched-pairs were assigned to one of two alternative workflows: 25 patients were introduced to a manual hypertension self-exam workflow (control group), and their matched-pair counterparts were introduced to technology-mediated hypertension self-exam workflow. All participants were tested on the existing workflow (current-state), followed by the introduction of an alternate workflow, and then tested a second time (pre-/ post-) with the same CS-AF procedure. The study incorporated the research findings from these two tests and a comparison between the workflows introduced using the CS-AF metrics. Findings from the two diverse empirical studies using the CS-AF (Graphic Communications sales order process, and Health Information Technology hypertension exam workflow) indicate that technology-mediated workflows do improve collaborative performance; however, adoption is not as pronounced as hypothesized. The research findings indicate that the lack of acceptance is due to non-technology factors, such as attitude and behavior, which play a significant role in adoption and need similar attention as technology innovation to drive true adoption and ultimately better collaborative performance. The research findings also indicate that the effectiveness of the CS-AF may have potential as a generalizable approach for evaluating technology-mediated collaborative workflow in a variety of unique domains