48 research outputs found

    Observations on patterns of development in open source software projects

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    What is the Connection Between Issues, Bugs, and Enhancements? (Lessons Learned from 800+ Software Projects)

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    Agile teams juggle multiple tasks so professionals are often assigned to multiple projects, especially in service organizations that monitor and maintain a large suite of software for a large user base. If we could predict changes in project conditions changes, then managers could better adjust the staff allocated to those projects.This paper builds such a predictor using data from 832 open source and proprietary applications. Using a time series analysis of the last 4 months of issues, we can forecast how many bug reports and enhancement requests will be generated next month. The forecasts made in this way only require a frequency count of this issue reports (and do not require an historical record of bugs found in the project). That is, this kind of predictive model is very easy to deploy within a project. We hence strongly recommend this method for forecasting future issues, enhancements, and bugs in a project.Comment: Accepted to 2018 International Conference on Software Engineering, at the software engineering in practice track. 10 pages, 10 figure

    Exploring the eradication of code smells: An empirical and theoretical perspective

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    This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2010 Hindawi Publishing CorporationCode smells reflect code decay, and, as such, developers should seek to eradicate such smells through application of “deodorant” in the form of one or more refactorings. However, a relative lack of studies exploring code smells either theoretically or empirically when compared with literature on refactoring suggests that there are reasons why smell eradication is neither being applied in anger, nor the subject of significant research. In this paper, we present three studies as supporting evidence for this stance. The first is an analysis of a set of five, open-source Java systems in which we show very little tendency for smells to be eradicated by developers; the second is an empirical study of a subsystem of a proprietary, C# web-based application where practical problems arise in smell identification and the third, a theoretical enumeration of smell-related refactorings to suggest why smells may be left alone from an effort perspective. Key findings of the study were that first, smells requiring application of simple refactorings were eradicated in favour of smells requiring more complex refactorings; second, a wide range of conflicts and anomalies soon emerged when trying to identify smelly code; an interesting result with respect to comment lines was also observed. Finally, perceived (estimated) effort to eradicate a smell may be a key factor in explaining why smell eradication is avoided by developers. The study thus highlights the need for a clearer research strategy on the issue of code smells and all aspects of their identification and measurement.The research in this paper was supported by a grant from the UK Engineering and Physical Sciences Research Council (EPSRC) (Grant no: EP/G031126/1

    Evolvability as a Quality Attribute of Software Architectures

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    We review the definition of evolvability as it appears on the literature. In particular, the concept of software evolvability is compared with other system quality attributes, such as adaptability, maintainability and modifiability

    Class movement and re-location: An empirical study of Java inheritance evolution

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    This is the post-print version of the final paper published in Journal of Systems and Software. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.Inheritance is a fundamental feature of the Object-Oriented (OO) paradigm. It is used to promote extensibility and reuse in OO systems. Understanding how systems evolve, and specifically, trends in the movement and re-location of classes in OO hierarchies can help us understand and predict future maintenance effort. In this paper, we explore how and where new classes were added as well as where existing classes were deleted or moved across inheritance hierarchies from multiple versions of four Java systems. We observed first, that in one of the studied systems the same set of classes was continuously moved across the inheritance hierarchy. Second, in the same system, the most frequent changes were restricted to just one sub-part of the overall system. Third, that a maximum of three levels may be a threshold when using inheritance in a system; beyond this level very little activity was observed, supporting earlier theories that, beyond three levels, complexity becomes overwhelming. We also found evidence of ‘collapsing’ hierarchies to bring classes up to shallower levels. Finally, we found that larger classes and highly coupled classes were more frequently moved than smaller and less coupled classes. Statistical evidence supported the view that larger classes and highly coupled classes were less cohesive than smaller classes and lowly coupled classes and were thus more suitable candidates for being moved (within an hierarchy)

    A framework for the simulation of structural software evolution

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    This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 ACM.As functionality is added to an aging piece of software, its original design and structure will tend to erode. This can lead to high coupling, low cohesion and other undesirable effects associated with spaghetti architectures. The underlying forces that cause such degradation have been the subject of much research. However, progress in this field is slow, as its complexity makes it difficult to isolate the causal flows leading to these effects. This is further complicated by the difficulty of generating enough empirical data, in sufficient quantity, and attributing such data to specific points in the causal chain. This article describes a framework for simulating the structural evolution of software. A complete simulation model is built by incrementally adding modules to the framework, each of which contributes an individual evolutionary effect. These effects are then combined to form a multifaceted simulation that evolves a fictitious code base in a manner approximating real-world behavior. We describe the underlying principles and structures of our framework from a theoretical and user perspective; a validation of a simple set of evolutionary parameters is then provided and three empirical software studies generated from open-source software (OSS) are used to support claims and generated results. The research illustrates how simulation can be used to investigate a complex and under-researched area of the development cycle. It also shows the value of incorporating certain human traits into a simulation—factors that, in real-world system development, can significantly influence evolutionary structures

    Identifying Effort Estimation Factors for Corrective Maintenance in Object-Oriented Systems

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    This research explores the decision-making process of expert estimators of corrective maintenance projects by usingqualitative methods to identify the factors that they use in deriving estimates. We implement a technique called causalmapping, which allows us to identify the cognitive links between the information that estimators use, and the estimates thatthey produce based on that information. Results suggest that a total of 17 factors may be relevant for corrective maintenanceeffort estimation, covering constructs related to developers, code, defects, and environment. This line of research aims ataddressing the limitations of existing maintenance estimation models that do not incorporate a number of soft factors, thus,achieving less accurate estimates than human experts

    Software-as-a Service Model: Elaborating Client-Side Adoption Factors

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    Software-as-a-Service (SaaS) is emerging as a viable outsourcing option for clients interested in paying for the right to access through the network a standardized set of business software functions. SaaS model largely replaced the Application Service Providers (ASPs)-based model, by creating an architecture that that provides no mechanisms for customizing the software on the vendor side; all customization is done on the client side through standardized interfaces. The fact that vendors are not making any client-specific investments makes this outsourcing model quite intriguing. In this paper we investigate client’s side determinants of adopting the SaaS model. We draw on economic, strategic management, and IS theories to develop a theoretical framework. In it, we develop a more elaborate view of uncertainty as some types uncertainty increase the propensity to adopt SaaS, while other types do the opposite. Finally, we integrate the role of the internal enterprise IT architecture into our model
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