Organizing the Technical Debt Landscape

To date, several methods and tools for detecting source code and design anomalies have been developed. While each method focuses on identifying certain classes of source code anomalies that potentially relate to technical debt (TD), the overlaps and gaps among these classes and TD have not been rigorously demonstrated. We propose to construct a seminal technical debt landscape as a way to visualize and organize research on the subjec

Scaling Flow Path Processes to Fluvial Landscapes: An Integrated Field and Model Assessment of Temperature and Dissolved Oxygen Dynamics in a River-Floodplain-Aquifer System

Biogeochemical cycling within river ecosystems is strongly influenced by geomorphic and hydrologic dynamics. To scale point observations of temperature and dissolved oxygen (DO) to a hydrologically complex and dynamic three-dimensional river-floodplain-aquifer system, we integrated empirical models of temperature and biotic oxygen utilization with a recently published hydrogeomorphic model. The hydrogeomorphic model simulates channel flow, floodplain inundation, and surface-subsurface water exchange on the 16 km(2) Nyack Floodplain, Middle Fork Flathead River, Montana, USA. Model results were compared to observed data sets of DO to test the hypothesis that complexity in spatiotemporal patterns of biogeochemistry emerges from a comparatively simple representation of biogeochemical processes operating within a multidimensional hydrologic system. The model explained 58% of the variance in 820 DO measurements that spanned the study site longitudinally, laterally, vertically, and across river discharge conditions and seasons. We also used model results to illustrate spatial and temporal trends of temperature and DO dynamics within the shallow alluvial aquifer, which is an extensive hyporheic zone because subsurface alluvial flow paths are recharged primarily by channel water. Our results underscore the importance of geomorphic, hydrologic, and temperature dynamics in driving river ecosystem processes, and they demonstrate how a realistic representation of a river\u27s physical template, combined with simple biogeochemical models, can explain complex patterns of solute availability

Comparing Four Approaches for Technical Debt Identification

Background: Software systems accumulate technical debt (TD) when short-term goals in software development are traded for long term goals (e.g., quick-and-dirty implementation to reach a release date vs. a well-refactored implementation that supports the long term health of the project). Some forms of TD accumulate over time in the form of source code that is difficult to work with and exhibits a variety of anomalies. A number of source code analysis techniques and tools have been proposed to potentially identify the code-level debt accumulated in a system. What has not yet been studied is if using multiple tools to detect TD can lead to benefits, i.e. if different tools will flag the same or different source code components. Further, these techniques also lack investigation into the symptoms of TD "interest" that they lead to. To address this latter question, we also investigated whether TD, as identified by the source code analysis techniques, correlates with interest payments in the form of increased defect- and change-proneness. Aims: Comparing the results of different TD identification approaches to understand their commonalities and differences and to evaluate their relationship to indicators of future TD "interest". Method: We selected four different TD identification techniques (code smells, automatic static analysis (ASA) issues, grime buildup, and modularity violations) and applied them to 13 versions of the Apache Hadoop open source software project. We collected and aggregated statistical measures to investigate whether the different techniques identified TD indicators in the same or different classes and whether those classes in turn exhibited high interest (in the form of a large number of defects and higher change proneness). Results: The outputs of the four approaches have very little overlap and are therefore pointing to different problems in the source code. Dispersed coupling and modularity violations were co-located in classes with higher defect proneness. We also observed a strong relationship between modularity violations and change proneness. Conclusions: Our main contribution is an initial overview of the TD landscape, showing that different TD techniques are loosely coupled and therefore indicate problems in different locations of the source code. Moreover, our proxy interest indicators (change- and defect-proneness) correlate with only a small subset of TD indicator

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

How Software Designs Decay: A Pilot Study of Pattern Evolution

A common belief is that software designs decay as systems evolve. This research examines the extent to which software designs actually decay by studying the aging of design patterns in successful object oriented systems. Aging of design patterns is measured using various types of decay indices developed for this research. Decay indices track the internal structural changes of a design pattern realization and the code that surrounds the realization. Hypotheses for each kind of decay are tested. We found that the original design pattern functionality remains, and pattern decay is due to the “grime”, non-pattern code, that grows around the pattern realization. Categories and Subject Descriptors D.2.8 [Software Engineering]: Metrics – software evolution, software decay, software grime

The evolution of FreeBSD and linux

Is the nature of Open Source Software (OSS) evolution fundamentally different from that of the traditional and commercially available software systems? Lehman and others conducted a series of empirical studies that found that traditional systems grow at a linear or sub-linear rate. A prior case study of the Linux OSS system suggests that OSS may evolve in a unique manner. Godfrey and Tu found that some aspects of Linux are growing at a super-linear rate rather than a sub-linear rate. Additional studies are necessary before drawing conclusions. Thus, we examine the evolution of FreeBSD and re-analyze the evolution of Linux, and find evidence that the growth of both systems has a linear upper bound, and thus appear to grow at similar rates to that of commercial systems. These results do not support the hypothesis that OSS systems grow at rates that exceed that of traditional systems

How Software Designs Decay: A Pilot Study of Pattern Evolution

A common belief is that software designs decay as systems evolve. This research examines the extent to which software designs actually decay by studying the aging of design patterns in successful object oriented systems. Aging of design patterns is measured using various types of decay indices developed for this research. Decay indices track the internal structural changes of a design pattern realization and the code that surrounds the realization. Hypotheses for each kind of decay are tested. We found that the original design pattern functionality remains, and pattern decay is due to the “grime”, non-pattern code, that grows around the pattern realization

Ontology-guided knowledge discovery of event sequences in maintenance data

Abstract—We created an application that facilitates improved knowledge discovery from aircraft maintenance data by trans-forming transactional database records into ontology-based event graphs, and then providing a filterable visualization of event sequences through time. We developed OWL ontologies based on formally defined IEEE standards, and use these ontologies to guide the data mining and data transformation processes. Our application removes much of the users burden for data look-up and greatly increases the potential for knowledge discovery from data (KDD) in this field. We provide an easy-to-use interface that generates relevant sequences of data in a meaningful context in a fraction of the time it would take domain experts to retrieve and display similar information. I

Graphbased ontology-guided data mining for d-matrix model maturation,” Aerospace

Abstract—In model-based diagnostic algorithms, it is assumed that the model is correct. If the model is incorrect, the diagnostic algorithm may diagnose the wrong fault, which can be costly and time consuming. Using past maintenance events, one should be able to make corrections to the model in order for diagnostic algorithm to correctly diagnosis faults. In this paper, a maturation approach is proposed which uses the graph-theoretic representations of Timed Failure Propagation Graph (TFPG) models and diagnostic sessions based on recently standardized diagnostic ontologies to determine statistical discrepancies between that which is expected by the models and that which has been encountered in practice. These discrepancies are then analyzed to generate recommendations for maturing the diagnostic models. Maturation recommendations includ