The Squale Model - A Practice-based Industrial Quality Model

ISO 9126 promotes a three-level model of quality (fac- tors, criteria, and metrics) which allows one to assess qual- ity at the top level of factors and criteria. However, it is dif- ficult to use this model as a tool to increase software quality. In the Squale model, we propose the adjunction of prac- tices as an intermediate level between metrics and crite- ria. Practices abstract from raw information at the source (metrics, tool reports, audits) to provide the developer with technical guidelines to respect. Moreover, practice marks can be adjusted using formulae to suit company develop- ment habits or exigences: for example bad marks can be stressed to point to places which need the most attention. Dashboards allow one to spot faulty practices and find the source elements responsible for the bad marks. The Squale model has been developed and validated over the last cou- ple of years in an industrial setting with Air France-KML and PSA Peugeot-Citroën. Over 100 projects with a total of more than seven millions lines of code have been assessed and steered using Squale

The Squale Model - A Practice-based Industrial Quality Model

International audienceISO 9126 promotes a three-level model of quality (fac- tors, criteria, and metrics) which allows one to assess qual- ity at the top level of factors and criteria. However, it is dif- ficult to use this model as a tool to increase software quality. In the Squale model, we add practices as an intermediate level between metrics and criteria. Practices abstract away from raw information (metrics, tool reports, audits) and provide technical guidelines to respect. Moreover, practice marks are adjusted using formulae to suit company development habits or exigences: for example bad marks are stressed to point to places which need more attention. The Squale model has been developed and validated over the last couple of years in an industrial setting with Air France-KLM and PSA Peugeot-Citroën

A Source-Code Maintainability Evaluation Model for Software Products

The maintainability index (MI) has been proposed to calculate a single number which expresses the maintainability of a system. This article presents a model for evaluating the maintainability of software products. The model improves the shortcomings observed in the maintainability assessment approaches in the quality assessment models SQuaRE (ISO25000), ISO 9126, Squale and the FCM standard. Its main innovation is to take into account the importance of entities in the system when calculating the maintainability score. This implies that the same type of defect will have a different score depending on the entity presenting it. Seven experts with several years of experience evaluated the model. They confirmed the effectiveness and usability of the model. Then, we compared our model with the Squale maintainability index and the classical maintainability index. The results show no correlation between these models. The implications are that each method gives a slightly different view of maintainability

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

An empirical model for continuous and weighted metric aggregation

International audienceIt is now understood that software metrics alone are not enough to characterize software quality. To cope with this problem, most of advanced and/or industrially validated quality models aggregate software metrics: for example, cy- clomatic complexity is combined with test coverage to stress the fact that it is more important to cover complex methods than accessors. Yet, aggregating and weighting metrics to produce quality indexes is a difficult task. Indeed certain weighting approaches may lead to abnormal situations where a developer increasing the quality of a software component sees the overall quality degrade. Finally, mapping combinations of metric values to quality indexes may be a problem when using thresholds. In this paper, we present the problems we faced when designing the Squale quality model, then we present an empirical solution based on weighted aggregations and on continuous functions. The solution has been termed the Squale quality model and validated over 4 years with two large multinational companies: Air France-KLM and PSA Peugeot- Citroen

Quality Properties of Execution Tracing, an Empirical Study

The authors are grateful to all the professionals who participated in the focus groups; moreover, they also express special thanks to the management of the companies involved for making the organisation of the focus groups possible.Data are made available in the appendix including the results of the data coding process.The quality of execution tracing impacts the time to a great extent to locate errors in software components; moreover, execution tracing is the most suitable tool, in the majority of the cases, for doing postmortem analysis of failures in the field. Nevertheless, software product quality models do not adequately consider execution tracing quality at present neither do they define the quality properties of this important entity in an acceptable manner. Defining these quality properties would be the first step towards creating a quality model for execution tracing. The current research fills this gap by identifying and defining the variables, i.e., the quality properties, on the basis of which the quality of execution tracing can be judged. The present study analyses the experiences of software professionals in focus groups at multinational companies, and also scrutinises the literature to elicit the mentioned quality properties. Moreover, the present study also contributes to knowledge with the combination of methods while computing the saturation point for determining the number of the necessary focus groups. Furthermore, to pay special attention to validity, in addition to the the indicators of qualitative research: credibility, transferability, dependability, and confirmability, the authors also considered content, construct, internal and external validity

Project-Team RMoD (Analyses and Language Constructs for Object-Oriented Application Evolution) 2009 Activity Report

This is the yearly report of the RMOD team. A good way to understand what we are doing