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The software production process involves a set of phases where a clear relationship and smooth transitions between them should be introduced. In this paper, a requirements engineering-based conceptual modeling approach is introduced as a way to improve the quality of the software production process. The aim of this approach is to provide a set of techniques and methods to capture software requirements and to provide a way to move from requirements to a conceptual schema in a traceable way. The approach combines a framework for requirements engineering (TRADE) and a graphical object-oriented method for conceptual modeling and code generation (OO-Method). The intended improvement of the software production process is accomplished by providing a precise methodological guidance to go from the user requirements (represented through the use of the appropriate TRADE techniques) to the conceptual schema that properly represents them (according to the conceptual constructs provided by the OO-Method). Additionally, as the OO-Method provides full model-based code generation features, this combination minimizes the time dedicated to obtaining the nal software product.

Modeling is a fundamental activity within the requirements engineering process and concerns the construction of abstract descriptions of software requirements that are amenable to interpretation and validation. The choice of a modeling technique is a critical issue whenever it is necessary to discuss the interpretation and validation of software requirements. This is particularly true in the case of stakeholders with divergent goals and different backgrounds and experience. This paper presents the results of a family of experiments conducted with students and professionals to investigate whether the comprehension of software requirements is influenced by the use of dynamic models. The family contains five experiments performed in different locations and with 112 subjects of different abilities and levels of experience with UML. The results show that dynamic models improve the comprehension of software requirements in the case of high ability and more experienced subjects.

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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 date 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 98 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.

OO-Method is an OO Methodology that blends the use of formal specification systems with conventional OO methodologies based on practice. In contrast to other approaches in this field ([Jun95,Esd93]), a set of graphical models provided by the methodology allows analysts to introduce the relevant system information to obtain the conceptual model through a requirements collection phase, so that an OO formal specification in Oasis ([Pas92, Pas95-1]), can be generated at any time. This formal specification acts as a high-level system repository. Furthermore, a software prototype which is functionally equivalent to the Oasis specification is also generated in an automated way. This is achieved by defining an execution model which gives the pattern for obtaining a concrete implementation in a declarative or an imperative software development environment (depending on the user choice). The methodology is supported by a CASE workbench.

Software developers require effective effort estimation models to facilitate project planning. Although Usman et al. systematically reviewed and synthesized the effort estimation models and practices for Agile Software Development (ASD) in 2014, new evidence may provide new perspectives for researchers and practitioners. This paper presents a systematic literature review that updates the Usman et al. study from 2014 to 2020 by analyzing the data extracted from 73 new papers. This analysis allowed us to identify six agile methods: Scrum, Xtreme Programming and four others, in all of which expert-based estimation methods continue to play an important role. This is particularly the case of Planning Poker, which is very closely related to the most frequently used size metric (story points) and the way in which software requirements are specified in ASD. There is also a remarkable trend toward studying techniques based on the intensive use of data. In this respect, although most of the data originate from single-company datasets, there is a significant increase in the use of cross-company data. With regard to cost factors, we applied the thematic analysis method. The use of team and project factors appears to be more frequent than the consideration of more technical factors, in accordance with agile principles. Finally, although accuracy is still a challenge, we identified that improvements have been made. On the one hand, an increasing number of papers showed acceptable accuracy values, although many continued to report inadequate results. On the other, almost 29% of the papers that reported the accuracy metric used reflected aspects concerning the validation of the models and 18% reported the effect size when comparing models.