Comparative Study on Agile software development methodologies

Today-s business environment is very much dynamic, and organisations are constantly changing their software requirements to adjust with new environment. They also demand for fast delivery of software products as well as for accepting changing requirements. In this aspect, traditional plan-driven developments fail to meet up these requirements. Though traditional software development methodologies, such as life cycle-based structured and object oriented approaches, continue to dominate the systems development few decades and much research has done in traditional methodologies, Agile software development brings its own set of novel challenges that must be addressed to satisfy the customer through early and continuous delivery of the valuable software. It is a set of software development methods based on iterative and incremental development process, where requirements and development evolve through collaboration between self-organizing, cross-functional teams that allows rapid delivery of high quality software to meet customer needs and also accommodate changes in the requirements. In this paper, we significantly identify and describe the major factors, that Agile development approach improves software development process to meet the rapid changing business environments. We also provide a brief comparison of agile development methodologies with traditional systems development methodologies, and discuss current state of adopting agile methodologies. We speculate that from the need to satisfy the customer through early and continuous delivery of the valuable software, Agile software development is emerged as an alternative to traditional plan-based software development methods. The purpose of this paper, is to provide an in-depth understanding, the major benefits of agile development approach to software development industry, as well as provide a comparison study report of ASDM over TSDM.Comment: 25 pages, 25 images, 86 references used, with authors biographie

Partition strategies for incremental Mini-Bucket

Los modelos en grafo probabilísticos, tales como los campos aleatorios de Markov y las redes bayesianas, ofrecen poderosos marcos de trabajo para la representación de conocimiento y el razonamiento en modelos con gran número de variables. Sin embargo, los problemas de inferencia exacta en modelos de grafos son NP-hard en general, lo que ha causado que se produzca bastante interés en métodos de inferencia aproximados. El mini-bucket incremental es un marco de trabajo para inferencia aproximada que produce como resultado límites aproximados inferior y superior de la función de partición exacta, a base de -empezando a partir de un modelo con todos los constraints relajados, es decir, con las regiones más pequeñas posibleincrementalmente añadir regiones más grandes a la aproximación. Los métodos de inferencia aproximada que existen actualmente producen límites superiores ajustados de la función de partición, pero los límites inferiores suelen ser demasiado imprecisos o incluso triviales. El objetivo de este proyecto es investigar estrategias de partición que mejoren los límites inferiores obtenidos con el algoritmo de mini-bucket, trabajando dentro del marco de trabajo de mini-bucket incremental. Empezamos a partir de la idea de que creemos que debería ser beneficioso razonar conjuntamente con las variables de un modelo que tienen una alta correlación, y desarrollamos una estrategia para la selección de regiones basada en esa idea. Posteriormente, implementamos nuestra estrategia y exploramos formas de mejorarla, y finalmente medimos los resultados obtenidos usando nuestra estrategia y los comparamos con varios métodos de referencia. Nuestros resultados indican que nuestra estrategia obtiene límites inferiores más ajustados que nuestros dos métodos de referencia. También consideramos y descartamos dos posibles hipótesis que podrían explicar esta mejora.Els models en graf probabilístics, com bé els camps aleatoris de Markov i les xarxes bayesianes, ofereixen poderosos marcs de treball per la representació del coneixement i el raonament en models amb grans quantitats de variables. Tanmateix, els problemes d’inferència exacta en models de grafs son NP-hard en general, el qual ha provocat que es produeixi bastant d’interès en mètodes d’inferència aproximats. El mini-bucket incremental es un marc de treball per a l’inferència aproximada que produeix com a resultat límits aproximats inferior i superior de la funció de partició exacta que funciona començant a partir d’un model al qual se li han relaxat tots els constraints -és a dir, un model amb les regions més petites possibles- i anar afegint a l’aproximació regions incrementalment més grans. Els mètodes d’inferència aproximada que existeixen actualment produeixen límits superiors ajustats de la funció de partició. Tanmateix, els límits inferiors acostumen a ser massa imprecisos o fins aviat trivials. El objectiu d’aquest projecte es recercar estratègies de partició que millorin els límits inferiors obtinguts amb l’algorisme de mini-bucket, treballant dins del marc de treball del mini-bucket incremental. La nostra idea de partida pel projecte es que creiem que hauria de ser beneficiós per la qualitat de l’aproximació raonar conjuntament amb les variables del model que tenen una alta correlació entre elles, i desenvolupem una estratègia per a la selecció de regions basada en aquesta idea. Posteriorment, implementem la nostra estratègia i explorem formes de millorar-la, i finalment mesurem els resultats obtinguts amb la nostra estratègia i els comparem a diversos mètodes de referència. Els nostres resultats indiquen que la nostra estratègia obté límits inferiors més ajustats que els nostres dos mètodes de referència. També considerem i descartem dues possibles hipòtesis que podrien explicar aquesta millora.Probabilistic graphical models such as Markov random fields and Bayesian networks provide powerful frameworks for knowledge representation and reasoning over models with large numbers of variables. Unfortunately, exact inference problems on graphical models are generally NP-hard, which has led to signifi- cant interest in approximate inference algorithms. Incremental mini-bucket is a framework for approximate inference that provides upper and lower bounds on the exact partition function by, starting from a model with completely relaxed constraints, i.e. with the smallest possible regions, incrementally adding larger regions to the approximation. Current approximate inference algorithms provide tight upper bounds on the exact partition function but loose or trivial lower bounds. This project focuses on researching partitioning strategies that improve the lower bounds obtained with mini-bucket elimination, working within the framework of incremental mini-bucket. We start from the idea that variables that are highly correlated should be reasoned about together, and we develop a strategy for region selection based on that idea. We implement the strategy and explore ways to improve it, and finally we measure the results obtained using the strategy and compare them to several baselines. We find that our strategy performs better than both of our baselines. We also rule out several possible explanations for the improvement

Testing in the incremental design and development of complex products

Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested

Contingent Information Systems Development

Situated approaches based on project contingencies are becoming more and more an important research topic for information systems development organizations. The Information Services Organization, which was investigated, has recognized that it should tune its systems development approaches to the specific situation. A model has been developed, dealing with the matching between prevailing contingency factors and the preconditions of already existing situated approaches. Furthermore, a generic process model for systems development, including the information systems operations stage, is proposed. This model makes it possible to derive from it specific systems development strategies. A number of basic development strategies, specific for the Information Services Organization, are described. Preconditions, specific for this organization, are added to the standard situated approaches

Is agile project management applicable to construction?

This paper briefly summarises the evolution of Agile Project Management (APM) and differentiates it from lean and agile production and ‘leagile’ construction. The significant benefits being realized through employment of APM within the information systems industry are stated. The characteristics of APM are explored, including: philosophy, organizational attitudes and practices, planning, execution and control and learning. Finally, APM is subjectively assessed as to its potential contribution to the pre-design, design and construction phases. In conclusion, it is assessed that APM offers considerable potential for application in predesign and design but that there are significant hurdles to its adoption in the actual construction phase. Should these be overcome, APM offers benefits well beyond any individual project

Adapting to informality: multistory housing driven by a co-productive process and the People’s Plans in Metro Manila, Philippines

Faced with an ever-increasing demand for land in Metro Manila, as well as with the domination of standardised low-income housing models, the local civil society and the urban-poor sector embarked on the development of an alternative shelter approach in-city multistorey housing delivered through the People’s Plan. The article documents the emergence of the approach, interrogates its main assumptions and takes a closer look at the implementation process through two case studies, in Pasig and San Jose Del Monte. The article analyses the modality as an attempt to create a hybrid approach between formal and informal delivery systems within the built form conventionally associated with the imaginaries of the ‘formal’ city. The findings underscore the role of co-production in enabling the urban-poor sector to leverage their approach, while documenting the need to move beyond a formal–informal dichotomy in both theory and urban development practice

DATABASE DEVELOPMENT LIFE CYCLE

A software development life cycle model (SDLC) consists of a set of processes (planning, requirements, design, development, testing, installation and maintenance) defined to accomplish the task of developing a software application that is functionally correct and satisfies the user’s needs. These set of processes, when arranged in different orders, characterize different types of life cycles. When developing a database, the order of these tasks is very important to efficiently and correctly transform the user’s requirements into an operational database. These SDLCs are generally defined very broadly and are not specific for a particular type of application. In this paper the authors emphasize that there should be a SDLC that is specific to database applications. Database applications do not have the same characteristics as other software applications and thus a specific database development life cycle (DBDLC) is needed. A DBDLC should accommodate properties like scope restriction, progressive enhancement, incremental planning and pre-defined structure.Software Development, Database, DBMS, lifecycle model, traditional lifecycles