Formal Specification Driven Development

This paper researches a quantitative metric of investigating Formal Specification-Driven Development (FSDD). Formal specification is needed at the beginning of the development process to prevent ambiguity and to improve the quality through corrections of errors found in the late phases of a traditional design process, Software Development Life Cycle (SDLC). The research is conducted with capstone students using both the FSDD and the SDLC (traditional) models and a quantitative analysis is presented to evaluate the internal quality of the software. The tool used to measure the internal quality is the .NET 2013 analysis tool. Formal Specification-Driven Development (FSDD) is a new approach in which formal specification is used and functional units of code are incrementally written and tested prior to the code implementation. In the research, there is a comparative study of Formal Specification-Driven Development with the traditional model. This research realized the promising attributes of Formal Specification Driven Development. It promotes the incorporation of FSDD in the software development process. FSDD is radically different from the traditional ways of developing software. In the traditional software development model (SDLC), the tests are written after code implementation. In FSDD the test occurs during development. This model is more of a programmer’s process. This study is the first complete evaluation of how FSDD affects software development and internal design quality. The study was carried out with students in a Software Engineering Capstone class. The research included a semester-long project to develop a ticketing system. This research demonstrated that software developers applying Formal Specification-Driven Development (FSDD) approach are likely to improve some software quality aspects compared to Software Development Life Cycle (FSDD) approach. In particular this research has shown significant differences in the areas of code complexity and size statistically. The differences in internal quality can considerably improve the external software quality, software maintainability, software understandability, and software re-usability. The research establishes a standard for future studies. It focused mainly on the software process. This research is going to raise awareness of FSDD as a new software development approach to explore further

A systematic review of quality attributes and measures for software product lines

[EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. 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Perceived Quality of Cars. A Novel Framework and Evaluation Methodology.

The supremacy of the automotive manufacturers today is no longer driven by them achieving a superior manufacturing quality but increasingly depends on the customer’s quality perception. Average car consumers see a car’s quality as a fancy mixture of design, aesthetics, their own previous experiences and performance characteristics of the vehicle, unlike a combination of mechanical parts, software pieces, advanced materials, cutting-edge manufacturing processes, with technical knowledge, skills and high production volumes – all ingredients involved in the modern car creation. Perceived quality is one of the most critical aspects for product development that defines successful car design.Speaking of perceived quality, we are dealing with a complex, multifaceted adaptive system; a system where a human is the main agent. “Which product characteristics require the most attention for successful car design?”\ua0 This is the question engineers and designers need to answer under the pressure of shrinking product development time, available technologies, and financial limitations, not to mention that the answer is expected to be given in numbers to sustain the fierce competition in today’s automotive industry. For this reason, the perceived quality must be understood and controlled during all stages of product development. The research presented in this thesis justifies the engineering viewpoint on perceived quality as an inevitable part of new product development. The core of this research is the Perceived Quality Framework (PQF), a taxonomy structure of perceived quality attributes and the Perceived Quality Attributes Importance Ranking (PQAIR) method, a novel method for perceived quality evaluation that can be applied to a variety of products, including cars. The PQF communicates the attribute-centric engineering viewpoint on quality perception, developed through cumulative studies in the premium and luxury market segment of the automotive industry. The PQAIR method equips engineers with practical tools for perceived quality evaluation. The proposed method helps to reach the equilibrium of the product’s quality equation from the perspective of design effort, time, and costs estimations.Altogether this introduces a new paradigm of perceived quality as the inevitable element integrated into the process of engineering endeavor regarding product attributes that communicates quality to the customer

Component Integration Metrics and Their Evaluation

Software Engineering (SE) has been described as the discipline devoted to the design, development, and use of computer software, covering not only the technical aspects of building software systems, but also management issues develops highly complex software. The crisis in SE, due to the lack of well-defined formal processes, has led to poorly designed products with high maintenance costs and whose behavior becomes unpredictable. Component Based Software Engineering (CBSE) is currently a preferred approach to system design to overcome the crisis of SE, since it promotes software re-use, facilitates adaptability and faster system development. A component provides a function or a set of related functions, which forms a reusable program building block that can be combined with other components to form an application. A component with qualities such as, reusability, testability, modularity, complexity, proper to communicate and stability reduces maintenance costs. The components thus integrated, should be able to interoperate so that an operational application that results in reduced maintenance costs can be composed with minimal effort. Metrics are used to measure a component\u27s quality factor and there are no good metrics available to validate their effectiveness, when components are integrated. Currently, the success of projects based on the CBSE methodology relies on experts who assess software components; however, their evaluation process involves parameters that may not be measured in practice. Existing traditional metrics are inappropriate since CBSE is aimed at improving interoperability and re-usability. Size metrics based on lines of code are not applicable as component sizes may not be known a priori. Furthermore, complexities that arise due to varying nature of facets and interfaces are not addressed by traditional metrics. This thesis addresses the evaluation of a series of metrics based on complexity, criticality and dynamic behavior, in order that component integration performance can be assessed. Three suites of metrics defined by various authors have been considered for evaluation so that one could choose the best metrics to measure an integrated environment. A suite of metrics proposed by Narasimhan and Hendradjaya are classified based on the attributes of: complexity, criticality and dynamic aspects. These metrics use graph-based connectivity to represent a system of integrated components. While the complexity metrics consider the packing density of integrated components and the interaction density among the components, criticality metrics reveal the extent of binding within each component in the system. Dynamic metrics have also been collected during the execution of an application and aid the process involved in testing and maintenance. Metric related data sets have been from several benchmark programs using instrumentation programs and key inferences have been obtained; these inferences include a systematic evaluation of quality of the various metrics. Two new metrics have also been provided towards assessing the stability of the application: one metric, namely CRIT instability, calculates the instability of each component, while the second new metric, namely CRIT inheritance,counts the number of components whose children exceeds a threshold value. Both these metrics are useful to assess the stability of the application and, in addition, to determine the components in a given application that needs to be redesigned. Future work will focus on the development of a metric evaluation suite to assess the system\u27s stability as a whole, considering the role of each component in an application

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

Systematic evaluation of software product line architectures

The architecture of a software product line is one of its most important artifacts as it represents an abstraction of the products that can be generated. It is crucial to evaluate the quality attributes of a product line architecture in order to: increase the productivity of the product line process and the quality of the products; provide a means to understand the potential behavior of the products and, consequently, decrease their time to market; and, improve the handling of the product line variability. The evaluation of product line architecture can serve as a basis to analyze the managerial and economical values of a product line for software managers and architects. Most of the current research on the evaluation of product line architecture does not take into account metrics directly obtained from UML models and their variabilities; the metrics used instead are difficult to be applied in general and to be used for quantitative analysis. This paper presents a Systematic Evaluation Method for UML-based Software Product Line Architecture, the SystEM-PLA. SystEM-PLA differs from current research as it provides stakeholders with a means to: (i) estimate and analyze potential products; (ii) use predefined basic UML-based metrics to compose quality attribute metrics; (iii) perform feasibility and trade-off analysis of a product line architecture with respect to its quality attributes; and, (iv) make the evaluation of product line architecture more flexible. An example using the SEI’s Arcade Game Maker (AGM) product line is presented as a proof of concept, illustrating SystEM-PLA activities. Metrics for complexity and extensibility quality attributes are defined and used to perform a trade-off analysis

Evaluating Software Architectures: Development Stability and Evolution

We survey seminal work on software architecture evaluationmethods. We then look at an emerging class of methodsthat explicates evaluating software architectures forstability and evolution. We define architectural stabilityand formulate the problem of evaluating software architecturesfor stability and evolution. We draw the attention onthe use of Architectures Description Languages (ADLs) forsupporting the evaluation of software architectures in generaland for architectural stability in specific