Harmonizing CMMI-DEV 1.2 and XP Method to Improve The Software Development Processes in Small Software Development Firms

Most software development organizations are small firms, and they have realized the need to manage and improve their software development and management activities. Traditional Software Process Improvement (SPI) models and standards are not realistic for these firms because of high cost, limited resources and strict project deadlines. Therefore, these firms need a lightweight software development method and an appropriate SPI model to manage and improve their software development and management processes. This study aims to construct a suitable software development process improvement framework for Small Software Development Firms (SSDFs) based on eXtreme Programming (XP) method and Capability Maturity Model Integration for Development Version 1.2 (CMMI-Dev1.2) model. Four stages are involved in developing the framework: (1) aligning XP practices to the specific goals of CMMI-Dev1.2 Key Process Areas (KPAs); (2) developing the proposed software development process improvement framework based on extending XP method by adapting the Extension-Based Approach (EBA), CMMI-Dev1.2, and generic elements of the SPI framework; (3) verifying the compatibility of the proposed framework to the KPAs of CMMI-Dev1.2 by using focus group method coupled with Delphi technique; and (4) validating the modified framework by using CMMI-Dev1.2 questionnaire as a main item to validate the suitability of the modified framework for SSDFs, and conducting two case studies to validate the applicability and effectiveness of this framework for these firms. The result of aligning XP practices to the KPAs of CMMI-Dev1.2 shows that twelve KPAs are largely supported by XP practices, eight KPAs are partially supported by XP practices, and two KPAs are not-supported by XP practices. The main contributions of this study are: software development process improvement framework for SSDFs, elicit better understanding of how to construct the framework, and quality improvement of the software development processes. There are possible avenues for extending this research to fulfil the missing specific practices of several KPAs, examining other agile practices and using CMMI-Dev1.3 to improve the framework, and conducting more case studie

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

Quality measurement in agile and rapid software development: A systematic mapping

Context: In despite of agile and rapid software development (ARSD) being researched and applied extensively, managing quality requirements (QRs) are still challenging. As ARSD processes produce a large amount of data, measurement has become a strategy to facilitate QR management. Objective: This study aims to survey the literature related to QR management through metrics in ARSD, focusing on: bibliometrics, QR metrics, and quality-related indicators used in quality management. Method: The study design includes the definition of research questions, selection criteria, and snowballing as search strategy. Results: We selected 61 primary studies (2001-2019). Despite a large body of knowledge and standards, there is no consensus regarding QR measurement. Terminology is varying as are the measuring models. However, seemingly different measurement models do contain similarities. Conclusion: The industrial relevance of the primary studies shows that practitioners have a need to improve quality measurement. Our collection of measures and data sources can serve as a starting point for practitioners to include quality measurement into their decision-making processes. Researchers could benefit from the identified similarities to start building a common framework for quality measurement. In addition, this could help researchers identify what quality aspects need more focus, e.g., security and usability with few metrics reported.This work has been funded by the European Union’s Horizon 2020 research and innovation program through the Q-Rapids project (grant no. 732253). This research was also partially supported by the Spanish Ministerio de Economía, Industria y Competitividad through the DOGO4ML project (grant PID2020-117191RB-I00). Silverio Martínez-Fernández worked in Fraunhofer IESE before January 2020.Peer ReviewedPostprint (published version

Software Technologies for Embedded Systems: An Industry

Abstract. This paper addresses the ongoing inventory activities within the ITEA MOOSE project. The inventory result will be a complete view on the application of methods, techniques and tools for software production within some of the leading European industrial companies within the embedded system field, such as Philips, Océ, ASML and Nokia. The current results are remarkable, as they confirm the cautiousness of industry to adopt recent state of the art development technologies, even as the production of in-time reliable software products becomes more and more an unreachable target

A Family of Experiments on Test-Driven Development

Context: Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.). The particularities of each study make the aggregation of results untenable. Objectives: The goal of this paper is to: increase the accuracy and generalizability of the results achieved in isolated experiments on TDD, provide joint conclusions on the performance of TDD across different industrial and academic settings, and assess the extent to which the characteristics of the experiments affect the quality-related performance of TDD. Method: We conduct a family of 12 experiments on TDD in academia and industry. We aggregate their results by means of meta-analysis. We perform exploratory analyses to identify variables impacting the quality-related performance of TDD. Results: TDD novices achieve a slightly higher code quality with iterative test-last development (i.e., ITL, the reverse approach of TDD) than with TDD. The task being developed largely determines quality. The programming environment, the order in which TDD and ITL are applied, or the learning effects from one development approach to another do not appear to affect quality. The quality-related performance of professionals using TDD drops more than for students. We hypothesize that this may be due to their being more resistant to change and potentially less motivated than students. Conclusion: Previous studies seem to provide conflicting results on TDD performance (i.e., positive vs. negative, respectively). We hypothesize that these conflicting results may be due to different study durations, experiment participants being unfamiliar with the TDD process..

Software Startups -- A Research Agenda

Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct from traditional mature software companies, but also from micro-, small-, and medium-sized enterprises, introducing new challenges relevant for software engineering research. This paper's research agenda focuses on software engineering in startups, identifying, in particular, 70+ research questions in the areas of supporting startup engineering activities, startup evolution models and patterns, ecosystems and innovation hubs, human aspects in software startups, applying startup concepts in non-startup environments, and methodologies and theories for startup research. We connect and motivate this research agenda with past studies in software startup research, while pointing out possible future directions. While all authors of this research agenda have their main background in Software Engineering or Computer Science, their interest in software startups broadens the perspective to the challenges, but also to the opportunities that emerge from multi-disciplinary research. Our audience is therefore primarily software engineering researchers, even though we aim at stimulating collaborations and research that crosses disciplinary boundaries. We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs

Vertically Integrated Projects (VIP) Programs: Multidisciplinary Projects with Homes in Any Discipline

A survey of papers in the ASEE Multidisciplinary Engineering Division over the last three years shows three main areas of emphasis: individual courses; profiles of specific projects; and capstone design courses. However, propagating multidisciplinary education across the vast majority of disciplines offered at educational institutions with varying missions requires models that are independent of the disciplines, programs, and institutions in which they were originally conceived. Further, models that can propagate must be cost effective, scalable, and engage and benefit participating faculty. Since 2015, a consortium of twenty-four institutions has come together around one such model, the Vertically Integrated Projects (VIP) Program. VIP unites undergraduate education and faculty research in a team-based context, with students earning academic credits toward their degrees, and faculty and graduate students benefitting from the design/discovery efforts of their multidisciplinary teams. VIP integrates rich student learning experiences with faculty research, transforming both contexts for undergraduate learning and concepts of faculty research as isolated from undergraduate teaching. It provides a rich, cost-effective, scalable, and sustainable model for multidisciplinary project-based learning. (1) It is rich because students participate multiple years as they progress through their curriculum; (2) It is cost-effective since students earn academic credit instead of stipends; (3) It is scalable because faculty can work with teams of students instead of individual undergraduate research fellows, and typical teams consist of fifteen or more students from different disciplines; (4) It is sustainable because faculty benefit from the research and design efforts of their teams, with teams becoming integral parts of their research. While VIP programs share key elements, approaches and implementations vary by institution. This paper shows how the VIP model works across sixteen different institutions with different missions, sizes, and student profiles. The sixteen institutions represent new and long-established VIP programs, varying levels of research activity, two Historically Black Colleges and Universities (HBCUs), a Hispanic-Serving Institution (HSI), and two international universities1. Theses sixteen profiles illustrate adaptability of the VIP model across different academic settings

A Feasibility Study of Automated Support for Similarity Analysis of Natural Language Requirements in Market-Driven Development

In market-driven software development there is a strong need for support to handle congestion in the requirements engineering process, which may occur as the demand for short time-to-market is combined with a rapid arrival of new requirements from many different sources. Automated analysis of the continuous flow of incoming requirements provides an opportunity to increase the efficiency of the requirements engineering process. This paper presents empirical evaluations of the benefit of automated similarity analysis of textual requirements, where existing information retrieval techniques are used to statistically measure requirements similarity. The results show that automated analysis of similarity among textual requirements is a promising technique that may provide effective support in identifying relationships between requirements