Evaluating Maintainability Prejudices with a Large-Scale Study of Open-Source Projects

Exaggeration or context changes can render maintainability experience into prejudice. For example, JavaScript is often seen as least elegant language and hence of lowest maintainability. Such prejudice should not guide decisions without prior empirical validation. We formulated 10 hypotheses about maintainability based on prejudices and test them in a large set of open-source projects (6,897 GitHub repositories, 402 million lines, 5 programming languages). We operationalize maintainability with five static analysis metrics. We found that JavaScript code is not worse than other code, Java code shows higher maintainability than C# code and C code has longer methods than other code. The quality of interface documentation is better in Java code than in other code. Code developed by teams is not of higher and large code bases not of lower maintainability. Projects with high maintainability are not more popular or more often forked. Overall, most hypotheses are not supported by open-source data.Comment: 20 page

Should I Bug You? Identifying Domain Experts in Software Projects Using Code Complexity Metrics

In any sufficiently complex software system there are experts, having a deeper understanding of parts of the system than others. However, it is not always clear who these experts are and which particular parts of the system they can provide help with. We propose a framework to elicit the expertise of developers and recommend experts by analyzing complexity measures over time. Furthermore, teams can detect those parts of the software for which currently no, or only few experts exist and take preventive actions to keep the collective code knowledge and ownership high. We employed the developed approach at a medium-sized company. The results were evaluated with a survey, comparing the perceived and the computed expertise of developers. We show that aggregated code metrics can be used to identify experts for different software components. The identified experts were rated as acceptable candidates by developers in over 90% of all cases

A research review of quality assessment for software

Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness

Aspect-Oriented Modularization of Assertion Crosscutting Objects

Software Engineering Conference, 2005. APSEC '05. 12th Asia-PacificDate of Conference:15-17 Dec. 200

Evaluating Ethereum development environments

Abstract. Blockchain technology has been one of the hottest buzzwords in the early 2020s and one of the main reasons for that is the interest towards decentralized applications, which use the smart contracts located in the blockchain to serve the application’s business logic. Ethereum is the biggest platform for decentralized applications, and this study focuses on exploring what kind of support developers need for developing Ethereum based products. This is done by first examining the state of the art by conducting a semi-systematic literature review, followed by using a customized DESMET evaluation method, in which the requirements are mapped as features along with the evaluation criteria, to see how well the currently popular Ethereum development environments provide support for the developers. A total of three development environments by the names of Hardhat, Truffle, and Brownie are evaluated, and the achieved results are analysed to find the differences in the level of support they offer for the developers. At the end the findings of the study are summarized, the experiences from the customized DESMET evaluation method are reported, the validity towards the achieved results are inspected, and the possible directions to continue the work is discussed

A Reasoning Framework for Dependability in Software Architectures

The degree to which a software system possesses specified levels of software quality attributes, such as performance and modifiability, often have more influence on the success and failure of those systems than the functional requirements. One method of improving the level of a software quality that a product possesses is to reason about the structure of the software architecture in terms of how well the structure supports the quality. This is accomplished by reasoning through software quality attribute scenarios while designing the software architecture of the system. As society relies more heavily on software systems, the dependability of those systems becomes critical. In this study, a framework for reasoning about the dependability of a software system is presented. Dependability is a multi-faceted software quality attribute that encompasses reliability, availability, confidentiality, integrity, maintainability and safety. This makes dependability more complex to reason about than other quality attributes. The goal of this reasoning framework is to help software architects build dependable software systems by using quantitative and qualitative techniques to reason about dependability in software architectures

Unified radio and network control across heterogeneous hardware platforms

Experimentation is an important step in the investigation of techniques for handling spectrum scarcity or the development of new waveforms in future wireless networks. However, it is impractical and not cost effective to construct custom platforms for each future network scenario to be investigated. This problem is addressed by defining Unified Programming Interfaces that allow common access to several platforms for experimentation-based prototyping, research, and development purposes. The design of these interfaces is driven by a diverse set of scenarios that capture the functionality relevant to future network implementations while trying to keep them as generic as possible. Herein, the definition of this set of scenarios is presented as well as the architecture for supporting experimentation-based wireless research over multiple hardware platforms. The proposed architecture for experimentation incorporates both local and global unified interfaces to control any aspect of a wireless system while being completely agnostic to the actual technology incorporated. Control is feasible from the low-level features of individual radios to the entire network stack, including hierarchical control combinations. A testbed to enable the use of the above architecture is utilized that uses a backbone network in order to be able to extract measurements and observe the overall behaviour of the system under test without imposing further communication overhead to the actual experiment. Based on the aforementioned architecture, a system is proposed that is able to support the advancement of intelligent techniques for future networks through experimentation while decoupling promising algorithms and techniques from the capabilities of a specific hardware platform