Software evolution prediction using seasonal time analysis: a comparative study

Prediction models of software change requests are useful for supporting rational and timely resource allocation to the evolution process. In this paper we use a time series forecasting model to predict software maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse’s change request tracking system since the project’s start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests’ evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data

Assessing architectural evolution: A case study

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach

Agent-based simulation of open source evolution

We present an agent-based simulation model developed to study how size, complexity and effort relate to each other in the development of open source software (OSS). In the model, many developer agents generate, extend, and re-factor code modules independently and in parallel. This accords with empirical observations of OSS development. To our knowledge, this is the first model of OSS evolution that includes the complexity of software modules as a limiting factor in productivity, the fitness of the software to its requirements, and the motivation of developers. Validation of the model was done by comparing the simulated results against four measures of software evolution (system size, proportion of highly complex modules, level of complexity control work, and distribution of changes) for four large OSS systems. The simulated results resembled the observed data, except for system size: three of the OSS systems showed alternating patterns of super-linear and sub-linear growth, while the simulations produced only super-linear growth. However, the fidelity of the model for the other measures suggests that developer motivation and the limiting effect of complexity on productivity have a significant effect on the development of OSS systems and should be considered in any model of OSS development

Empirical studies of open source evolution

Copyright @ 2008 Springer-VerlagThis chapter presents a sample of empirical studies of Open Source Software (OSS) evolution. According to these studies, the classical results from the studies of proprietary software evoltion, such as Lehman’s laws of software evolution, might need to be revised, if not fully, at least in part, to account for the OSS observations. The book chapter also summarises what appears to be the empirical status of each of Lehman’s laws with respect to OSS and highlights the threads to validity that frequently emerge in these empirical studies. The chapter also discusses related topics for further research

Open source ERP for SMEs.

For the last decade or so, the biggest category of the IT investment has unarguably been Enterprise Resource Planning (ERP). Most of the bigger corporations in the developed countries have implemented ERP systems with an aim to achieving competitive edge in their respective business areas. Now that the top end of the ERP market has been saturated, the main interest has moved to non-commercial sectors such as universities and small and medium-sized enterprises (SMEs). These organisations have not been able benefit directly from the ERP revolution because an ERP implementation requires huge resources and entails high risks. Over the same period, the concept of Open Source Software (OSS) has been enthusiastically adopted by the software engineering community. OSS has excelled in many systems software domains, for example, operating systems with Linux and web servers with Apache. Having observed these successes, the software industry has been showing interest in application domains such as enterprise information systems, more specifically ERP systems, as the next OSS candidates. In this paper, we outline the challenges as well as opportunities of OSS ERP development

Functional Data Analysis in Electronic Commerce Research

This paper describes opportunities and challenges of using functional data analysis (FDA) for the exploration and analysis of data originating from electronic commerce (eCommerce). We discuss the special data structures that arise in the online environment and why FDA is a natural approach for representing and analyzing such data. The paper reviews several FDA methods and motivates their usefulness in eCommerce research by providing a glimpse into new domain insights that they allow. We argue that the wedding of eCommerce with FDA leads to innovations both in statistical methodology, due to the challenges and complications that arise in eCommerce data, and in online research, by being able to ask (and subsequently answer) new research questions that classical statistical methods are not able to address, and also by expanding on research questions beyond the ones traditionally asked in the offline environment. We describe several applications originating from online transactions which are new to the statistics literature, and point out statistical challenges accompanied by some solutions. We also discuss some promising future directions for joint research efforts between researchers in eCommerce and statistics.Comment: Published at http://dx.doi.org/10.1214/088342306000000132 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Survey of the Economic Role of Software Platforms in Computer-Based Industries

Software platforms are a critical component of the computer systems underpinning leading– edge products ranging from third– generation mobile phones to video games. After describing some key economic features of computer systems and software platforms, the paper presents case studies of personal computers, video games, personal digital assistants, smart mobile phones, and digital content devices. It then compares several economic aspects of these businesses including their industry evolution, pricing structures, and degrees of integration.software platforms, hardware platforms, network effects, bundling, multi-sided markets