Aspect-oriented model-driven code generation approach for improving code reusability and maintainability

Software development teams always need methods that can help in producing high-quality software with reduced development effort and delivery time. Model-Driven Engineering (MDE) as well as Aspect-Oriented Software Development (AOSD) techniques help in reducing the delivery time, and also positively contribute to quality of the produced software. Through the use of AOSD techniques in combination with MDE, an integration of excellent abstraction mechanisms of MDE and capabilities of AOSD with regards to modularity and composition of concerns can be perceived, which is expected to enhance the positive effects of both techniques. To this end, different integration approaches have appeared in literature, but aspect-oriented code generation has advantages over the other approaches. Consequently, a number of aspect-oriented code generation approaches have been offered, but all such approaches lack several features mandatory to materialize a workable integration of aspect technologies in the context of MDE. To address these issues, this research was conducted to present an approach for aspect-oriented model-driven code generation, which focuses on elaborating the conceptual relationship between design models and the implementation code, and exploits the same to obtain aspect-oriented code that is more reusable and maintainable. The key outcomes of this research are the elaboration of the conceptual mappings between elements of visual design and constructs of the code, mapping of the visual models to implementation-specific text-based models, and a technique for generation of aspect-oriented code. The applicability of the proposed approach is shown by the use of case studies, whereas the quality of the approach is measured using reusability and maintainability metrics. A comparison of the proposed approach with existing approaches substantiates its efficacy in terms of reusability and maintainability of code, showing an outperformance of other approaches by the proposed approach against 78% of the employed quality metrics

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

A Quality Model for Actionable Analytics in Rapid Software Development

Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by IEEE in the 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018. The final authenticated version will be available onlin

Impact of Aspect Oriented Programming on Software Development Quality Metrics

The aspect-oriented programming (AOP) is a new paradigm for improving the system’s features such as modularity, readability and maintainability. Owing to a better modularisation of cross-cutting concerns, the developed system implementation would be less complex, and more readable.Thus, software development efficiency would increase, so the system would be created faster than its object-oriented programming (OOP) equivalent. In this paper, we provide some insight into the OO software development quality metrics were significantly associated with using AOP.The method that we are currently studying is based on a popular C & K metrics suite that extends the metrics traditionally used with the OO paradigm and also extend to AO paradigm. We argue that a shift similar to the one leading to the Chidamber and Kemerer’s metrics is necessary when moving from OO to AOP software

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

What to Fix? Distinguishing between design and non-design rules in automated tools

Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality tool vendors have responded to this need by positioning their tools to detect and manage technical debt. While these tools bundle a number of rules, it is hard for users to understand which rules identify design issues, as opposed to syntactic quality. This is important, since previous studies have revealed the most significant technical debt is related to design issues. Other research has focused on comparing these tools on open source projects, but these comparisons have not looked at whether the rules were relevant to design. We conducted an empirical study using a structured categorization approach, and manually classify 466 software quality rules from three industry tools---CAST, SonarQube, and NDepend. We found that most of these rules were easily labeled as either not design (55%) or design (19%). The remainder (26%) resulted in disagreements among the labelers. Our results are a first step in formalizing a definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on Software Architecture 2017 (Gothenburg, SE

LIFECYCLE BASED AUDIT PROCESS FOR DISTRIBUTED APPLICATIONS

The paper wishes to present the audit process as part of a distributed framework in which a new set of metrics are built. The requirements for an audit process are described and on each of the lifecycle stages, the audit process is emphasized. The existing quality characteristics models from the literature are analyzed based on which a new set of metrics are built for sustaining the overall audit process.audit process, distributed applications, metrics and lifecycle