Building lean thinking in a telecom software development organization: strengths and challenges.

The potential shown by Lean in different domains has aroused interest in the software industry. However, it remains unclear how Lean can be effectively applied in a domain such as software development that is fundamentally different from manufacturing. This study explores how Lean principles are implemented in software development companies and the challenges that arise when applying Lean Software Development. For that, a case study was conducted at Ericsson R&D Finland, which successfully adopted Scrum in 2009 and subsequently started a comprehensible transition to Lean in 2010. Focus groups were conducted with company representatives to help devise a questionnaire supporting the creation of a Lean mindset in the company (Team Amplifier). Afterwards, the questionnaire was used in 16 teams based in Finland, Hungary and China to evaluate the status of the transformation. By using Lean thinking, Ericsson R&D Finland has made important improvements to the quality of its products, customer satisfaction and transparency within the organization. Moreover, build times have been reduced over ten times and the number of commits per day has increased roughly five times.The study makes two main contributions to research. First, the main factors that have enabled Ericsson R&D?s achievements are analysed. Elements such as ?network of product owners?, ?continuous integration?, ?work in progress limits? and ?communities of practice? have been identified as being of fundamental importance. Second, three categories of challenges in using Lean Software Development were identified: ?achieving flow?, ?transparency? and ?creating a learning culture?

Software tool for simulation of aircraft trajectories

New concepts in air navigation have been introduced recently. Among others, are the concepts of trajectory optimization, 4D trajectories, RBT (Reference Business Trajectory), TBO (trajectory based operations), CDA (Continuous Descent Approach) and ACDA (Advanced CDA), conflict resolution, arrival time (AMAN), introduction of new aircraft (UAVs, UASs) in air space, etc. Although some of these concepts are new, the future Air Traffic Management will maintain the four ATM key performance areas such as Safety, Capacity, Efficiency, and Environmental impact. So much, the performance of the ATM system is directly related to the accuracy with which the future evolution of the traffic can be predicted. In this sense, future air traffic management will require a variety of support tools to provide suitable help to users and engineers involved in the air space management. Most of these tools are based on an appropriate trajectory prediction module as main component. Therefore, the purposes of these tools are related with testing and evaluation of any air navigation concept before they become fully operative. The aim of this paper is to provide an overview to the design of a software tool useful to estimate aircraft trajectories adapted to air navigation concepts. Other usage of the tool, like controller design, vertical navigation assessment, procedures validation and hardware and software in the loop are available in the software tool. The paper will show the process followed to design the tool, the software modules needed to perform accurately and the process followed to validate the output data.

Definition of a support infrastructure for replicating and aggregating families of software engineering experiments

Experimental software engineering includes several processes, the most representative being run experiments, run replications and synthesize the results of multiple replications. Of these processes, only the first is relatively well established in software engineering. Problems of information management and communication among researchers are one of the obstacles to progress in the replication and synthesis processes. Software engineering experimentation has expanded considerably over the last few years. This has brought with it the invention of experimental process support proposals. However, few of these proposals provide integral support, including replication and synthesis processes. Most of the proposals focus on experiment execution. This paper proposes an infrastructure providing integral support for the experimental research process, specializing in the replication and synthesis of a family of experiments. The research has been divided into stages or phases, whose transition milestones are marked by the attainment of their goals. Each goal exactly matches an artifact or product. Within each stage, we will adopt cycles of successive approximations (generateand- test cycles), where each approximation includes a diferent viewpoint or input. Each cycle will end with the product approval.

Gestión de configuración y línea de productos para mejorar el proceso experimental en ingeniería del software

La Ingeniería del Software (IS) Empírica adopta el método científico a la IS para facilitar la generación de conocimiento. Una de las técnicas empleadas, es la realización de experimentos. Para que el conocimiento obtenido experimentalmente adquiera el nivel de madurez necesario para su posterior uso, es necesario que los experimentos sean replicados. La existencia de múltiples replicaciones de un mismo experimento conlleva la existencia de numerosas versiones de los distintos productos generados durante la realización de cada replicación. Actualmente existe un gran descontrol sobre estos productos, ya que la administración se realiza de manera informal. Esto causa problemas a la hora de planificar nuevas replicaciones, o intentar obtener información sobre las replicaciones ya realizadas. Para conocer con detalle la dimensión del problema a resolver, se estudia el estado actual de la gestión de materiales experimentales y su uso en replicaciones, así como de las herramientas de gestión de materiales experimentales. El estudio concluye que ninguno de los enfoques estudiados proporciona una solución al problema planteado. Este trabajo persigue como objetivo mejorar la administración de los materiales experimentales y replicaciones de experimentos en IS para dar soporte a la replicación de experimentos. Para satisfacer este objetivo, se propone la adopción en experimentación de los paradigmas de Gestión de Configuración del Software (GCS) y Línea de Producto Software (LPS). Para desarrollar la propuesta se decide utilizar el método de investigación acción (en inglés action research). Para adoptar la GCS a experimentación, se comienza realizando un estudio del proceso experimental como transformación de productos; a continuación, se realiza una adopción de conceptos fundamentada en los procesos del desarrollo software y de experimentación; finalmente, se desarrollan un conjunto de instrumentos, que se incorporan a un Plan de Gestión de Configuración de Experimentos (PGCE). Para adoptar la LPS a experimentación, se comienza realizando un estudio de los conceptos, actividades y fases que fundamentan la LPS; a continuación, se realiza una adopción de los conceptos; finalmente, se desarrollan o adoptan las técnicas, simbología y modelos para dar soporte a las fases de la Línea de Producto para Experimentación (LPE). La propuesta se valida mediante la evaluación de su: viabilidad, flexibilidad, usabilidad y satisfacción. La viabilidad y flexibilidad se evalúan mediante la instanciación del PGCE y de la LPE en experimentos concretos en IS. La usabilidad se evalúa mediante el uso de la propuesta para la generación de las instancias del PGCE y de LPE. La satisfacción evalúa la información sobre el experimento que contiene el PGCE y la LPE. Los resultados de la validación de la propuesta muestran mejores resultados en los aspectos de usabilidad y satisfacción a los experimentadores. ABSTRACT Empirical software engineering adapts the scientific method to software engineering (SE) in order to facilitate knowledge generation. Experimentation is one of the techniques used. For the knowledge generated experimentally to acquire the level of maturity necessary for later use, the experiments have to be replicated. As the same experiment is replicated more than once, there are numerous versions of all the products generated during a replication. These products are generally administered informally without control. This is troublesome when it comes to planning new replications or trying to gather information on replications conducted in the past. In order to grasp the size of the problem to be solved, this research examines the current state of the art of the management and use of experimental materials in replications, as well as the tools managing experimental materials. The study concludes that none of the analysed approaches provides a solution to the stated problem. The aim of this research is to improve the administration of SE experimental materials and experimental replications in support of experiment replication. To do this, we propose the adaptation of software configuration management (SCM) and software product line (SPL) paradigms to experimentation. The action research method was selected in order to develop this proposal. The first step in the adaptation of the SCM to experimentation was to analyse the experimental process from the viewpoint of the transformation of products. The concepts were then adapted based on software development and experimentation processes. Finally, a set of instruments were developed and added to an experiment configuration management plan (ECMP). The first step in the adaptation of the SPL to experimentation is to analyse the concepts, activities and phases underlying the SPL. The concepts are then adapted. Finally, techniques, symbols and models are developed or adapted in support of the experimentation product line (EPL) phases. The proposal is validated by evaluating its feasibility, flexibility, usability and satisfaction. Feasibility and flexibility are evaluated by instantiating the ECMP and the EPL in specific SE experiments. Usability is evaluated by using the proposal to generate the instances of the ECMP and EPL. The results of the validation of the proposal show that the proposal performs better with respect to usability issues and experimenter satisfaction.

Conceptualización e Infraestructura para la Investigación Experimental en Ingeniería del Software

Antecedentes: Esta investigación se enmarca principalmente en la replicación y secundariamente en la síntesis de experimentos en Ingeniería de Software (IS). Para poder replicar, es necesario disponer de todos los detalles del experimento original. Sin embargo, la descripción de los experimentos es habitualmente incompleta debido a la existencia de conocimiento tácito y a la existencia de otros problemas tales como: La carencia de un formato estándar de reporte, la inexistencia de herramientas que den soporte a la generación de reportes experimentales, etc. Esto provoca que no se pueda reproducir fielmente el experimento original. Esta problemática limita considerablemente la capacidad de los experimentadores para llevar a cabo replicaciones y por ende síntesis de experimentos. Objetivo: La investigación tiene como objetivo formalizar el proceso experimental en IS, de modo que facilite la comunicación de información entre experimentadores. Contexto: El presente trabajo de tesis doctoral ha sido desarrollado en el seno del Grupo de Investigación en Ingeniería del Software Empírica (GrISE) perteneciente a la Escuela Técnica Superior de Ingenieros Informáticos (ETSIINF) de la Universidad Politécnica de Madrid (UPM), como parte del proyecto TIN2011-23216 denominado “Tecnologías para la Replicación y Síntesis de Experimentos en Ingeniería de Software”, el cual es financiado por el Gobierno de España. El grupo GrISE cumple a la perfección con los requisitos necesarios (familia de experimentos establecida, con al menos tres líneas experimentales y una amplia experiencia en replicaciones (16 replicaciones hasta 2011 en la línea de técnicas de pruebas de software)) y ofrece las condiciones para que la investigación se lleve a cabo de la mejor manera, como por ejemplo, el acceso total a su información. Método de Investigación: Para cumplir este objetivo se opta por Action Research (AR) como el método de investigación más adecuado a las características de la investigación, para obtener resultados a través de aproximaciones sucesivas que abordan los problemas concretos de comunicación entre experimentadores. Resultados: Se formalizó el modelo conceptual del ciclo experimental desde la perspectiva de los 3 roles principales que representan los experimentadores en el proceso experimental, siendo estos: Gestor de la Investigación (GI), Gestor del Experimento (GE) y Experimentador Senior (ES). Por otra parte, se formalizó el modelo del ciclo experimental, a través de: Un workflow del ciclo y un diagrama de procesos. Paralelamente a la formalización del proceso experimental en IS, se desarrolló ISRE (de las siglas en inglés Infrastructure for Sharing and Replicating Experiments), una prueba de concepto de entorno de soporte a la experimentación en IS. Finalmente, se plantearon guías para el desarrollo de entornos de soporte a la experimentación en IS, en base al estudio de las características principales y comunes de los modelos de las herramientas de soporte a la experimentación en distintas disciplinas experimentales. Conclusiones: La principal contribución de la investigación esta representada por la formalización del proceso experimental en IS. Los modelos que representan la formalización del ciclo experimental, así como la herramienta ISRE, construida a modo de evaluación de los modelos, fueron encontrados satisfactorios por los experimentadores del GrISE. Para consolidar la validez de la formalización, consideramos que este estudio debería ser replicado en otros grupos de investigación representativos en la comunidad de la IS experimental. Futuras Líneas de Investigación: El cumplimiento de los objetivos, de la mano con los hallazgos alcanzados, han dado paso a nuevas líneas de investigación, las cuales son las siguientes: (1) Considerar la construcción de un mecanismo para facilitar el proceso de hacer explícito el conocimiento tácito de los experimentadores por si mismos de forma colaborativa y basados en el debate y el consenso , (2) Continuar la investigación empírica en el mismo grupo de investigación hasta cubrir completamente el ciclo experimental (por ejemplo: experimentos nuevos, síntesis de resultados, etc.), (3) Replicar el proceso de investigación en otros grupos de investigación en ISE, y (4) Renovar la tecnología de la prueba de concepto, tal que responda a las restricciones y necesidades de un entorno real de investigación. ABSTRACT Background: This research addresses first and foremost the replication and also the synthesis of software engineering (SE) experiments. Replication is impossible without access to all the details of the original experiment. But the description of experiments is usually incomplete because knowledge is tacit, there is no standard reporting format or there are hardly any tools to support the generation of experimental reports, etc. This means that the original experiment cannot be reproduced exactly. These issues place considerable constraints on experimenters’ options for carrying out replications and ultimately synthesizing experiments. Aim: The aim of the research is to formalize the SE experimental process in order to facilitate information communication among experimenters. Context: This PhD research was developed within the empirical software engineering research group (GrISE) at the Universidad Politécnica de Madrid (UPM)’s School of Computer Engineering (ETSIINF) as part of project TIN2011-23216 entitled “Technologies for Software Engineering Experiment Replication and Synthesis”, which was funded by the Spanish Government. The GrISE research group fulfils all the requirements (established family of experiments with at least three experimental lines and lengthy replication experience (16 replications prior to 2011 in the software testing techniques line)) and provides favourable conditions for the research to be conducted in the best possible way, like, for example, full access to information. Research Method: We opted for action research (AR) as the research method best suited to the characteristics of the investigation. Results were generated successive rounds of AR addressing specific communication problems among experimenters. Results: The conceptual model of the experimental cycle was formalized from the viewpoint of three key roles representing experimenters in the experimental process. They were: research manager, experiment manager and senior experimenter. The model of the experimental cycle was formalized by means of a workflow and a process diagram. In tandem with the formalization of the SE experimental process, infrastructure for sharing and replicating experiments (ISRE) was developed. ISRE is a proof of concept of a SE experimentation support environment. Finally, guidelines for developing SE experimentation support environments were designed based on the study of the key features that the models of experimentation support tools for different experimental disciplines had in common. Conclusions: The key contribution of this research is the formalization of the SE experimental process. GrISE experimenters were satisfied with both the models representing the formalization of the experimental cycle and the ISRE tool built in order to evaluate the models. In order to further validate the formalization, this study should be replicated at other research groups representative of the experimental SE community. Future Research Lines: The achievement of the aims and the resulting findings have led to new research lines, which are as follows: (1) assess the feasibility of building a mechanism to help experimenters collaboratively specify tacit knowledge based on debate and consensus, (2) continue empirical research at the same research group in order to cover the remainder of the experimental cycle (for example, new experiments, results synthesis, etc.), (3) replicate the research process at other ESE research groups, and (4) update the tools of the proof of concept in order to meet the constraints and needs of a real research environment.

Análisis del software ImageJ para el análisis científico de imágenes

ImageJ es un programa informático de tratamiento digital de imagen orientado principalmente hacia el ámbito de las ciencias de la salud. Se trata de un software de dominio público y de código abierto desarrollado en lenguaje Java en las instituciones del National Institutes of Health de Estados Unidos. Incluye por defecto potentes herramientas para editar, procesar y analizar imágenes de casi cualquier tipo y formato. Sin embargo, su mayor virtud reside en su extensibilidad: las funcionalidades de ImageJ pueden ampliarse hasta resolver casi cualquier problema de tratamiento digital de imagen mediante macros, scripts y, especialmente, plugins programables en lenguaje Java gracias a la API que ofrece. Además, ImageJ cuenta con repositorios oficiales en los que es posible obtener de forma gratuita macros, scripts y plugins aplicables en multitud de entornos gracias a la labor de la extensa comunidad de desarrolladores de ImageJ, que los depura, mejora y amplia frecuentemente. Este documento es la memoria de un proyecto que consiste en el análisis detallado de las herramientas de tratamiento digital de imagen que ofrece ImageJ. Tiene por objetivo determinar si ImageJ, a pesar de estar más enfocado a las ciencias de la salud, puede resultar útil en el entorno de la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid, y en tal caso, resaltar las características que pudieran resultar más beneficiosas en este ámbito y servir además como guía introductoria. En las siguientes páginas se examinan una a una las herramientas de ImageJ (versión 1.48q), su funcionamiento y los mecanismos subyacentes. Se sigue el orden marcado por los menús de la interfaz de usuario: el primer capítulo abarca las herramientas destinadas a la manipulación de imágenes en general (menú Image); el segundo, las herramientas de procesado (menú Process); el tercero, las herramientas de análisis (menú Analyze); y el cuarto y último, las herramientas relacionadas con la extensibilidad de ImageJ (menú Plugins). ABSTRACT. ImageJ is a digital image processing computer program which is mainly focused at the health sciences field. It is a public domain, open source software developed in Java language at the National Institutes of Health of the United States of America. It includes powerful built-in tools to edit, process and analyze almost every type of image in nearly every format. However, its main virtue is its extensibility: ImageJ functionalities can be widened to solve nearly every situation found in digital image processing through macros, scripts and, specially, plugins programmed in Java language thanks to the ImageJ API. In addition, ImageJ has official repositories where it is possible to freely get many different macros, scripts and plugins thanks to the work carried out by the ImageJ developers community, which continuously debug, improve and widen them. This document is a report which explains a detailed analysis of all the digital image processing tools offered by ImageJ. Its final goal is to determine if ImageJ can be useful to the environment of Escuela Tecnica Superior de Ingenierfa y Sistemas de Telecomunicacion of Universidad Politecnica de Madrid, in spite of being focused at the health sciences field. In such a case, it also aims to highlight the characteristics which could be more beneficial in this field, and serve as an introductory guide too. In the following pages, all of the ImageJ tools (version 1.48q) are examined one by one, as well as their work and the underlying mechanics. The document follows the order established by the menus in ImageJ: the first chapter covers all the tools destined to manipulate images in general (menu Image); the second one covers all the processing tools (menu Process); the third one includes analyzing tools (menu Analyze); and finally, the fourth one contains all those tools related to ImageJ extensibility (menu Plugins).

UML 1.4 versus UML 2.0 as Languages to Describe Software Architectures.

ML 1.4 is widely accepted as the standard for representing the various software artifacts generated by a development process. For this reason, there have been attempts to use this language to represent the software architec- ture of systems as well. Unfortunately, these attempts have ended in representa- tions (boxes and lines) already criticized by the software architecture commu- nity. Recently, OMG has published a draft that will constitute the future UML 2.0 specification. In this paper we compare the capacities of UML 1.4 and UML 2.0 to describe software architectures. In particular, we study extensions of both UML versions to describe the static view of the C3 architectural style (a simplification of the C2 style). One of the results of this study is the difficulties found when using the UML 2.0 metamodel to describe the concept of connector in a software architecture.

Diseño de una metodología CASE de desarrollo de software

En la actualidad existe una gran expectación ante la introducción de nuevas herramientas y métodos para el desarrollo de productos software, que permitirán en un futuro próximo un planteamiento de ingeniería del proceso de producción software. Las nuevas metodologías que empiezan a esbozarse suponen un enfoque integral del problema abarcando todas las fases del esquema productivo. Sin embargo el grado de automatización conseguido en el proceso de construcción de sistemas es muy bajo y éste está centrado en las últimas fases del ciclo de vida del software, consiguiéndose así una reducción poco significativa de sus costes y, lo que es aún más importante, sin garantizar la calidad de los productos software obtenidos. Esta tesis define una metodología de desarrollo software estructurada que se puede automatizar, es decir una metodología CASE. La metodología que se presenta se ajusta al modelo de ciclo de desarrollo CASE, que consta de las fases de análisis, diseño y pruebas; siendo su ámbito de aplicación los sistemas de información. Se establecen inicialmente los principios básicos sobre los que la metodología CASE se asienta. Posteriormente, y puesto que la metodología se inicia con la fijación de los objetivos de la empresa que demanda un sistema informático, se emplean técnicas que sirvan de recogida y validación de la información, que proporcionan a la vez un lenguaje de comunicación fácil entre usuarios finales e informáticos. Además, estas mismas técnicas detallarán de una manera completa, consistente y sin ambigüedad todos los requisitos del sistema. Asimismo, se presentan un conjunto de técnicas y algoritmos para conseguir que desde la especificación de requisitos del sistema se logre una automatización tanto del diseño lógico del Modelo de Procesos como del Modelo de Datos, validados ambos conforme a la especificación de requisitos previa. Por último se definen unos procedimientos formales que indican el conjunto de actividades a realizar en el proceso de construcción y cómo llevarlas a cabo, consiguiendo de esta manera una integridad en las distintas etapas del proceso de desarrollo.---ABSTRACT---Nowdays there is a great expectation with regard to the introduction of new tools and methods for the software products development that, in the very near future will allow, an engineering approach in the software development process. New methodologies, just emerging, imply an integral approach to the problem, including all the productive scheme stages. However, the automatization degree obtained in the systems construction process is very low and focused on the last phases of the software lifecycle, which means that the costs reduction obtained is irrelevant and, which is more important, the quality of the software products is not guaranteed. This thesis defines an structured software development methodology that can be automated, that is a CASE methodology. Such a methodology is adapted to the CASE development cycle-model, which consists in analysis, design and testing phases, being the information systems its field of application. Firstly, we present the basic principies on which CASE methodology is based. Secondly, since the methodology starts from fixing the objectives of the company demanding the automatization system, we use some techniques that are useful for gathering and validating the information, being at the same time an easy communication language between end-users and developers. Indeed, these same techniques will detail completely, consistently and non ambiguously all the system requirements. Likewise, a set of techniques and algorithms are shown in order to obtain, from the system requirements specification, an automatization of the Process Model logical design, and of the Data Model logical design. Those two models are validated according to the previous requirement specification. Finally, we define several formal procedures that suggest which set of activities to be accomplished in the construction process, and how to carry them out, getting in this way integrity and completness for the different stages of the development process.

Modelling spatial decisión support systems focused on the development of a data warehouse: applying software engineering

Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.

Replications of software engineering experiments

There are many open issues that must be addressed before the replication process can be successfully formalized in empirical software engineering research. We define replication as the deliberate repetition of the same empirical study for the purpose of determining whether the results of the first experiment can be reproduced. This definition would appear at first glance to be good. However, it needs several clarifications that have not yet been forthcoming in software engineering: – What is the exact meaning of the same empirical study? Namely how similar should an experiment be to the baseline study for it to be considered a replication? What is the exact meaning of a result being reproduced? Namely how similar does a result have to be to the result of the baseline study for it to be considered reproduced? These and other methodological questions need to be researched and tailored for empirical software engineering.

ITIL in Small to Medium-Sized Enterprises: toward a proposal based on an ITIL processes implementation sequence and a pofile scheme strategy for implementing the first process in the sequence

The backdrop of actual problematic about the implementation of Information Technology (IT) services management in Small and Medium Enterprises (SMEs) will be described. It will be exposed the reasons why reaching a maturity/capability level through well-known standards or the implementation of good software engineering practices by means of IT infrastructure Library are really difficult to achieve by SMEs. Also, the solutions to the exposed problems will be explained. Also master thesis goals are presented in terms of: purpose, research questions, research goals, objectives and scope. Finally, thesis structure is described.

Software architecture implementation based on OpenSim

One of the objectives of the European Higher Education Area is the promotion of collaborative and informal learning through the implementation of educational practices. 3D virtual environments become an ideal space for such activities. On the other hand, the problem of financing in Spanish universities has led to the search for new ways to optimize available resources. The Technical University of Madrid requires the use of laboratories which due to their dangerousness, duration or control of the developed processes are difficult to perform in real life. For this reason, we have developed several 3D laboratories in virtual environment. The laboratories are built on open source platform OpenSim. In this paper it is exposed the use of the OpenSim platform for these new teaching experiences and the new design of the software architecture. This architecture requires the adaptation of the platform to the needs of the users and the different laboratories of our University. We will explain the structure of the implemented architecture and the process of creating and configuring it. The proposed architecture is decentralized, each laboratory is housed in different an educational center. The architecture adds several services, among others, the creation and management of users automated, communication between external services and platforms in different program languages. Therefore, we achieve improving the user experience and rising the functionalities of laboratories.

Análisis de la calidad y productividad en el desarrollo de un proyecto software en una microempresa con TSPi

Este artículo presenta el análisis de los resultados obtenidos al aplicar TSPi en el desarrollo de un proyecto software en una microempresa desde el punto de vista de la calidad y la productividad. La organización en estudio necesitaba mejorar la calidad de sus procesos pero no contaba con los recursos económicos que requieren modelos como CMMI-DEV. Por esta razón, se decidió utilizar un proceso adaptado a la organización basado en TSPi, observándose una reducción en la desviación de las estimaciones, un incremento en la productividad, y una mejora en la calidad.---ABSTRACT---This article shows the benefits of developing a software project using TSPi in a “Very Small Enterprise” based in quality and productivity measures. An adapted process from the current process based on the TSPi was defined and the team was trained in it. The workaround began by gathering historical data from previous projects in order to get a measurement repository, and then the project metrics were collected. Finally, the process, product and quality improvements were verified.

A small settings case study using TSPi in a software project

This article introduces a small setting case study about the benefits of using TSPi in a software project. An adapted process from the current process based on the TSPi was defined. The pilot project had schedule and budget constraints. The process began by gathering historical data from previous projects in order to get a measurement repository. The project was launched with the following goals: increase the productivity, reduce the test time and improve the product quality. Finally, the results were analysed and the goals were verified

Benefits of TSPi in a software project under a small settings enviroment

This article presents a case study about the TSPi benefits in a software project under a Small Settings environment. An adapted process based on the TSPi was defined. The pilot project had a schedule and budget restricted. The process began collecting historical projects data in order to get a measure repository. The project was launched defining the following goals: increase the productivity, reduce the test time and improve the product quality. Finally, the results were analysed and the goals were verified.