Structured Review of the Evidence for Effects of Code Duplication on Software Quality

This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)

Assessing the effect of source code characteristics on changeability

Maintenance is the phase of the software lifecycle that comprises any modification after the delivery of an application. Modifications during this phase include correcting faults, improving internal attributes, as well as adapting the application to different environments. As application knowledge and architectural integrity degrade over time, so does the facility with which changes to the application are introduced. Thus, eliminating source code that presents characteristics that hamper maintenance becomes necessary if the application is to evolve. We group these characteristics under the term Source Code Issues. Even though there is support for detecting Source Code Issues, the extent of their harmfulness for maintenance remains unknown. One of the most studied Source Code Issue is cloning. Clones are duplicated code, usually created as programmers copy, paste, and customize existing source code. However, there is no agreement on the harmfulness of clones. This thesis proposes and follows a novel methodology to assess the effect of clones on the changeability of methods. Changeability is the ease with which a source code entity is modified. It is assessed through metrics calculated from the history of changes of the methods. The impact of clones on the changeability of methods is measured by comparing the metrics of methods that contain clones to those that do not. Source code characteristics are then tested to establish whether they are endemic of methods whose changeability decay increase when cloned. In addition to findings on the harmfulness of cloning, this thesis contributes a methodology that can be applied to assess the harmfulness of other Source Code Issues. The contributions of this thesis are twofold. First, the findings answer the question about the harmfulness of clones on changeability by showing that cloned methods are more likely to change, and that some cloned methods have significantly higher changeability decay when cloned. Furthermore, it offers a characterization of such harmful clones. Second, the methodology provides a guide to analyze the effect of Source Code Characteristics in changeability; and therefore, can be adapted for other Source Code Issues

Technical Debt Decision-Making Framework

Software development companies strive to produce high-quality software. In commercial software development environments, due to resource and time constraints, software is often developed hastily which gives rise to technical debt. Technical debt refers to the consequences of taking shortcuts when developing software. These consequences include making the system difficult to maintain and defect prone. Technical debt can have financial consequences and impede feature enhancements. Identifying technical debt and deciding which debt to address is challenging given resource constraints. Project managers must decide which debt has the highest priority and is most critical to the project. This decision-making process is not standardized and sometimes differs from project to project. My research goal is to develop a framework that project managers can use in their decision-making process to prioritize technical debt based on its potential impact. To achieve this goal, we survey software practitioners, conduct literature reviews, and mine software repositories for historical data to build a framework to model the technical debt decision-making process and inform practitioners of the most critical debt items

Technical Debt Decision-Making Framework

Software development companies strive to produce high-quality software. In commercial software development environments, due to resource and time constraints, software is often developed hastily which gives rise to technical debt. Technical debt refers to the consequences of taking shortcuts when developing software. These consequences include making the system difficult to maintain and defect prone. Technical debt can have financial consequences and impede feature enhancements. Identifying technical debt and deciding which debt to address is challenging given resource constraints. Project managers must decide which debt has the highest priority and is most critical to the project. This decision-making process is not standardized and sometimes differs from project to project. My research goal is to develop a framework that project managers can use in their decision-making process to prioritize technical debt based on its potential impact. To achieve this goal, we survey software practitioners, conduct literature reviews, and mine software repositories for historical data to build a framework to model the technical debt decision-making process and inform practitioners of the most critical debt items

Software languages engineering: experimental evaluation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia InformáticaDomain-Specific Languages (DSLs) are programming languages that offer, through appropriate notation and abstraction, still enough an expressive control over a particular problem domain for more restricted use. They are expected to contribute with an enhancement of productivity, reliability, maintainability and portability, when compared with General Purpose Programming Languages (GPLs). However, like in any Software Product without passing by all development stages namely Domain Analysis, Design, Implementation and Evaluation, some of the DSLs’ alleged advantages may be impossible to be achieved with a significant level of satisfaction. This may lead to the production of inadequate or inefficient languages. This dissertation is focused on the Evaluation phase. To characterize DSL community commitment concerning Evaluation, we conducted a systematic review. The review covered publications in the main fora dedicated to DSLs from 2001 to 2008, and allowed to analyse and classify papers with respect to the validation efforts conducted by DSLs’ producers, where have been observed a reduced concern to this matter. Another important outcome that has been identified is the absence of a concrete approach to the evaluation of DSLs, which would allow a sound assessment of the actual improvements brought by the usage of DSLs. Therefore, the main goal of this dissertation concerns the production of a Systematic Evaluation Methodology for DSLs. To achieve this objective, has been carried out the major techniques used in Experimental Software Engineering and Usability Engineering context. The proposed methodology was validated with its use in several case studies, whereupon DSLs evaluation has been made in accordance with this methodology

A Multi-Level Framework for the Detection, Prioritization and Testing of Software Design Defects

Large-scale software systems exhibit high complexity and become difficult to maintain. In fact, it has been reported that software cost dedicated to maintenance and evolution activities is more than 80% of the total software costs. In particular, object-oriented software systems need to follow some traditional design principles such as data abstraction, encapsulation, and modularity. However, some of these non-functional requirements can be violated by developers for many reasons such as inexperience with object-oriented design principles, deadline stress. This high cost of maintenance activities could potentially be greatly reduced by providing automatic or semi-automatic solutions to increase system‟s comprehensibility, adaptability and extensibility to avoid bad-practices. The detection of refactoring opportunities focuses on the detection of bad smells, also called antipatterns, which have been recognized as the design situations that may cause software failures indirectly. The correction of one bad smell may influence other bad smells. Thus, the order of fixing bad smells is important to reduce the effort and maximize the refactoring benefits. However, very few studies addressed the problem of finding the optimal sequence in which the refactoring opportunities, such as bad smells, should be ordered. Few other studies tried to prioritize refactoring opportunities based on the types of bad smells to determine their severity. However, the correction of severe bad smells may require a high effort which should be optimized and the relationships between the different bad smells are not considered during the prioritization process. The main goal of this research is to help software engineers to refactor large-scale systems with a minimum effort and few interactions including the detection, management and testing of refactoring opportunities. We report the results of an empirical study with an implementation of our bi-level approach. The obtained results provide evidence to support the claim that our proposal is more efficient, on average, than existing techniques based on a benchmark of 9 open source systems and 1 industrial project. We have also evaluated the relevance and usefulness of the proposed bi-level framework for software engineers to improve the quality of their systems and support the detection of transformation errors by generating efficient test cases.Ph.D.Information Systems Engineering, College of Engineering and Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/136075/1/Dilan_Sahin_Final Dissertation.pdfDescription of Dilan_Sahin_Final Dissertation.pdf : Dissertatio

Architectural stability of self-adaptive software systems

This thesis studies the notion of stability in software engineering with the aim of understanding its dimensions, facets and aspects, as well as characterising it. The thesis further investigates the aspect of behavioural stability at the architectural level, as a property concerned with the architecture's capability in maintaining the achievement of expected quality of service and accommodating runtime changes, in order to delay the architecture drifting and phasing-out as a consequence of the continuous unsuccessful provision of quality requirements. The research aims to provide a systematic and methodological support for analysing, modelling, designing and evaluating architectural stability. The novelty of this research is the consideration of stability during runtime operation, by focusing on the stable provision of quality of service without violations. As the runtime dimension is associated with adaptations, the research investigates stability in the context of self-adaptive software architectures, where runtime stability is challenged by the quality of adaptation, which in turn affects the quality of service. The research evaluation focuses on the effectiveness, scale and accuracy in handling runtime dynamics, using the self-adaptive cloud architectures