Functional Size Measurement Tool-based Approach for Mobile Game

Nowadays, software effort estimation plays an important role in software project management due to its extensive use in industry to monitor progress, and performance, determine overall productivity and assist in project planning. After the success of methods such as IFPUG Function Point Analysis, MarkII Function Point Analysis, and COSMIC Full Function Points, several other extension methods have been introduced to be adopted in software projects. Despite the efficiency in measuring the software cost, software effort estimation, unfortunately, is facing several issues; it requires some knowledge, effort, and a significant amount of time to conduct the measurement, thus slightly ruining the advantages of this approach. This paper demonstrates a functional size measurement tool, named UML Point tool, that utilizes the concept of IFPUG Function Point Analysis directly to Unified Modeling Language (UML) model. The tool allows the UML eXchange Format (UXF) file to decode the UML model of mobile game requirement and extract the diagrams into component complexity, object interface complexity, and sequence diagram complexity, according to the defined measurement rules. UML Point tool then automatically compute the functional size, effort, time, human resources, and total development cost of mobile game. Besides, this paper also provides a simple case study to validate the tool. The initial results proved that the tool could be useful to improve estimation accuracy for mobile game application development and found to be reliable to be applied in the mobile game industry

Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach

Historically, software production methods and tools have a unique goal: to produce high quality software. Since the goal of Model-Driven Development (MDD) methods is no different, MDD methods have emerged to take advantage of the benefits of using conceptual models to produce high quality software. In such MDD contexts, conceptual models are used as input to automatically generate final applications. Thus, we advocate that there is a relation between the quality of the final software product and the quality of the models used to generate it. The quality of conceptual models can be influenced by many factors. In this thesis, we focus on the accuracy of the techniques used to predict the characteristics of the development process and the generated products. In terms of the prediction techniques for software development processes, it is widely accepted that knowing the functional size of applications in order to successfully apply effort models and budget models is essential. In order to evaluate the quality of generated applications, defect detection is considered to be the most suitable technique. The research goal of this thesis is to provide an accurate measurement procedure based on COSMIC for the automatic sizing of object-oriented OO-Method MDD applications. To achieve this research goal, it is necessary to accurately measure the conceptual models used in the generation of object-oriented applications. It is also very important for these models not to have defects so that the applications to be measured are correctly represented. In this thesis, we present the OOmCFP (OO-Method COSMIC Function Points) measurement procedure. This procedure makes a twofold contribution: the accurate measurement of objectoriented applications generated in MDD environments from the conceptual models involved, and the verification of conceptual models to allow the complete generation of correct final applications from the conceptual models involved. The OOmCFP procedure has been systematically designed, applied, and automated. This measurement procedure has been validated to conform to the ISO 14143 standard, the metrology concepts defined in the ISO VIM, and the accuracy of the measurements obtained according to ISO 5725. This procedure has also been validated by performing empirical studies. The results of the empirical studies demonstrate that OOmCFP can obtain accurate measures of the functional size of applications generated in MDD environments from the corresponding conceptual models.Marín Campusano, BM. (2011). Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11237Palanci

Linguistic Approaches for Early Measurement of Functional Size from Software Requirements

The importance of early effort estimation, resource allocation and overall quality control in a software project has led the industry to formulate several functional size measurement (FSM) methods that are based on the knowledge gathered from software requirements documents. The main objective of this research is to develop a comprehensive methodology to facilitate and automate early measurement of a software's functional size from its requirements document written in unrestricted natural language. For the purpose of this research, we have chosen to use the FSM method developed by the Common Software Measurement International Consortium (COSMIC) and adopted as an international standard by the International Standardization Organization (ISO). This thesis presents a methodology to measure the COSMIC size objectively from various textual forms of functional requirements and also builds conceptual measurement models to establish traceability links between the output measurements and the input requirements. Our research investigates the feasibility of automating every major phase of this methodology with natural language processing and machine learning approaches. The thesis provides a step-by-step validation and demonstration of the implementation of this innovative methodology. It describes the details of empirical experiments conducted to validate the methodology with practical samples of textual requirements collected from both the industry and academia. Analysis of the results show that each phase of our methodology can successfully be automated and, in most cases, leads to an accurate measurement of functional size

Towards making functional size measurement easily usable in practice

Functional Size Measurement methods \u2013like the IFPUG Function Point Analysis and COSMIC methods\u2013 are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications\u2018 sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results

Towards making functional size measurement easily usable in practice

Functional Size Measurement methods –like the IFPUG Function Point Analysis and COSMIC methods– are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications‘ sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results

Formal and quantitative approach to non-functional requirements modeling and assessment in software engineering

In the software market place, in which functionally equivalent products compete for the same customer, Non Functional Requirements (NFRs) become more important in distinguishing between the competing products. However, in practice, NFRs receive little attention relative to Functional Requirements (FRs). This is mainly because of the nature of these requirements which poses a challenge when taking the choice of treating them earlier in the software development. NFRs are subjective, relative and they become scattered among multiple modules when they are mapped from the requirements domain to the solution space. Furthermore, NFRs can often interact, in the sense that attempts to achieve one NFR can help or hinder the achievement of other NFRs at particular software functionality. Such an interaction creates an extensive network of interdependencies and tradeoffs among NFRs which is not easy to trace or estimate. This thesis contributes towards achieving the goal of managing the attainable scope and the changes of NFRs. The thesis proposes and empirically evaluates a formal and quantitative approach to modeling and assessing NFRs. Central to such an approach is the implementation of the proposed NFRs Ontology for capturing and structuring the knowledge on the software requirements (FRs and NFRs), their refinements, and their interdependencies. In this thesis, we also propose a change management mechanism for tracing the impact of NFRs on the other constructs in the ontology and vice-versa. We provide a traceability mechanism using Datalog expressions to implement queries on the relational model-based representation for the ontology. An alternative implementation view using XML and XQuery is provided as well. In addition, we propose a novel approach for the early requirements-based effort estimation, based on NFRs Ontology. The effort estimation approach complementarily uses one standard functional size measurement model, namely COSMIC, and a linear regression techniqu

A reactive architecture for cloud-based system engineering

PhD ThesisSoftware system engineering is increasingly practised over globally distributed locations. Such a practise is termed as Global Software Development (GSD). GSD has become a business necessity mainly because of the scarcity of resources, cost, and the need to locate development closer to the customers. GSD is highly dependent on requirements management, but system requirements continuously change. Poorly managed change in requirements affects the overall cost, schedule and quality of GSD projects. It is particularly challenging to manage and trace such changes, and hence we require a rigorous requirement change management (RCM) process. RCM is not trivial in collocated software development; and with the presence of geographical, cultural, social and temporal factors, it makes RCM profoundly difficult for GSD. Existing RCM methods do not take into consideration these issues faced in GSD. Considering the state-of-the-art in RCM, design and analysis of architecture, and cloud accountability, this work contributes: 1. an alternative and novel mechanism for effective information and knowledge-sharing towards RCM and traceability. 2. a novel methodology for the design and analysis of small-to-medium size cloud-based systems, with a particular focus on the trade-off of quality attributes. 3. a dependable framework that facilitates the RCM and traceability method for cloud-based system engineering. 4. a novel methodology for assuring cloud accountability in terms of dependability. 5. a cloud-based framework to facilitate the cloud accountability methodology. The results show a traceable RCM linkage between system engineering processes and stakeholder requirements for cloud-based GSD projects, which is better than existing approaches. Also, the results show an improved dependability assurance of systems interfacing with the unpredictable cloud environment. We reach the conclusion that RCM with a clear focus on traceability, which is then facilitated by a dependable framework, improves the chance of developing a cloud-based GSD project successfully

Formalisation et automatisation de la mesure des points de fonction

La méthode des points de fonction, proposée par Albrecht, permet de mesurer la taille fonctionnelle d'un logiciel durant la phase de spécification des besoins. Elle a été améliorée par l'IFPUG (International Function Points User Group). Cette méthode des points de fonction a été étendue par le groupe COSMIC (Common Software Measurement International Consortium) pour la mesure des systèmes temps réels, appelée COSMIC-FFP. Cependant, les définitions de ces deux méthodes sont ambiguës, ce qui les rend difficiles à automatiser. Dans cette thèse, nous avons formalisé la définition des points de fonction selon la méthode d'IFPUG pour mesurer des spécifications écrites en langage B. Nous avons également formalisé la définition de COSMIC-FFP pour des spécifications écrites avec la notation de Rational Rose RealTime (RRRT). De plus, nous avons développé un outil, [Special characters omitted.], qui permet de mesurer automatiquement COSMIC-FFP pour des spécifications RRRT. Nos définitions formelles permettent de lever plusieurs ambiguïtés et de rendre ces mesures objectives, ce qui permettra d'éliminer la variance dans le processus de mesure.La formalisation permet également l'automatisation de la mesure

ICSEA 2021: the sixteenth international conference on software engineering advances

The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. The conference had the following tracks: Advances in fundamentals for software development Advanced mechanisms for software development Advanced design tools for developing software Software engineering for service computing (SOA and Cloud) Advanced facilities for accessing software Software performance Software security, privacy, safeness Advances in software testing Specialized software advanced applications Web Accessibility Open source software Agile and Lean approaches in software engineering Software deployment and maintenance Software engineering techniques, metrics, and formalisms Software economics, adoption, and education Business technology Improving productivity in research on software engineering Trends and achievements Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions. We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions. This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success. We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research