2026
Conference article
Restricted
Critical Analysis of ASPICE® 4.0 Machine Learning Engineering Process Requirements
Lami Giuseppe, Falcini Fabio
The introduction of machine learning development paradigm into the automotive software industry has made necessary to update the applicable qual- ity evaluation standards such as Automotive SPICE®. As a result the Automotive SPICE® community timely tackled this challenge with the introduction of the ver- sion 4.0 containing a first baseline of process requirements for machine learning engineering. The paper provides a succinct critical analysis of related ASPICE® new content with particular reference to the current state of the art of machine learn- ing development practices. The outcome of this paper aims at being an input for the forthcoming improvement initiatives within the Automotive SPICE working groups.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16362, pp. 346-352. Salerno, Italy, 1-3 December 2025
DOI: 10.1007/978-3-032-12092-2_29
Metrics:
Lami Giuseppe, Falcini Fabio
The introduction of machine learning development paradigm into the automotive software industry has made necessary to update the applicable qual- ity evaluation standards such as Automotive SPICE®. As a result the Automotive SPICE® community timely tackled this challenge with the introduction of the ver- sion 4.0 containing a first baseline of process requirements for machine learning engineering. The paper provides a succinct critical analysis of related ASPICE® new content with particular reference to the current state of the art of machine learn- ing development practices. The outcome of this paper aims at being an input for the forthcoming improvement initiatives within the Automotive SPICE working groups.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16362, pp. 346-352. Salerno, Italy, 1-3 December 2025
DOI: 10.1007/978-3-032-12092-2_29
Metrics:
See at:
doi.org 
| CNR IRIS | CNR IRIS | link.springer.com
2025
Conference article
Restricted
A survey of existing standards addressing AI-based technologies
Lami Giuseppe, Merola Francesco
The rapid integration of Artificial Intelligence (AI) into software sys- tems across many domains, including critical ones such as healthcare, transporta- tion, and public administration, has intensified the need for robust, reliable, and transparent quality evaluation methods. While numerous standards and regula- tory initiatives have emerged and many more are being worked on, the current landscape remains fragmented with varying scopes, definitions, and enforcement mechanisms. This paper provides a structured, yet not exhaustive, overview of current international standards, regulatory instruments, and soft-law guidelines relevant to AI-based software quality evaluation. The purpose of this paper is to provide a starting point for practitioners and researchers for understanding the sta- tus, as well as the short-coming evolution, of the standards addressing AI-based technologies and for orienting their efforts to contribute to fill the existing lacks and weaknesses in the standard corpus.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16362, pp. 323-333. Salerno, Italy, 1-3/12/2025
DOI: 10.1007/978-3-032-12092-2_27
Metrics:
Lami Giuseppe, Merola Francesco
The rapid integration of Artificial Intelligence (AI) into software sys- tems across many domains, including critical ones such as healthcare, transporta- tion, and public administration, has intensified the need for robust, reliable, and transparent quality evaluation methods. While numerous standards and regula- tory initiatives have emerged and many more are being worked on, the current landscape remains fragmented with varying scopes, definitions, and enforcement mechanisms. This paper provides a structured, yet not exhaustive, overview of current international standards, regulatory instruments, and soft-law guidelines relevant to AI-based software quality evaluation. The purpose of this paper is to provide a starting point for practitioners and researchers for understanding the sta- tus, as well as the short-coming evolution, of the standards addressing AI-based technologies and for orienting their efforts to contribute to fill the existing lacks and weaknesses in the standard corpus.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16362, pp. 323-333. Salerno, Italy, 1-3/12/2025
DOI: 10.1007/978-3-032-12092-2_27
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com
2025
Conference article
Open Access
Prognostic techniques in automated driving system (ADS) vehicle safety
Merola F., Hanif A., Lami G., Ahmed Q., Monohon M.
The recent advancements in fields such as sensors, AI, and IoT are majorly impacting the automotive industry. Automated Driving Systems (ADS) are developing rapidly, meaning that SAE J3016 Level 3 and above vehicles are quickly becoming a reality. As a result, maintenance of such systems becomes essential to ensure their safe and efficient operation. Prognostic techniques in particular are crucial to monitor the state of health and predicting the end of life for components. Prognostics engineering is being applied in many industries and for conventional automotive applications, but ADS is new technology, and the prognostics for these systems are still being developed and adapted. In this paper, we first present a review of the most used prognostic techniques across different safety-critical domains such as aerospace, power, and manufacturing. Then, we summarize the main challenges that must be faced to successfully develop novel approaches for prognostics of ADS components and provide a set of recommendations to support future research in the field. Finally, we present a future project consisting of a scenario-based prognostic framework for ADS-equipped vehiclesSource: SAE TECHNICAL PAPER SERIES. Detroit, USA, 08-10/04/2025
Merola F., Hanif A., Lami G., Ahmed Q., Monohon M.
The recent advancements in fields such as sensors, AI, and IoT are majorly impacting the automotive industry. Automated Driving Systems (ADS) are developing rapidly, meaning that SAE J3016 Level 3 and above vehicles are quickly becoming a reality. As a result, maintenance of such systems becomes essential to ensure their safe and efficient operation. Prognostic techniques in particular are crucial to monitor the state of health and predicting the end of life for components. Prognostics engineering is being applied in many industries and for conventional automotive applications, but ADS is new technology, and the prognostics for these systems are still being developed and adapted. In this paper, we first present a review of the most used prognostic techniques across different safety-critical domains such as aerospace, power, and manufacturing. Then, we summarize the main challenges that must be faced to successfully develop novel approaches for prognostics of ADS components and provide a set of recommendations to support future research in the field. Finally, we present a future project consisting of a scenario-based prognostic framework for ADS-equipped vehiclesSource: SAE TECHNICAL PAPER SERIES. Detroit, USA, 08-10/04/2025
See at:
CNR IRIS 
| wcx.sae.org | CNR IRIS | CNR IRIS
2025
Conference article
Open Access
Strengthen process debt identification through process assessment standards
Lami G., Merola F.
Process Debt (PD), a concept derived from the Technical Debt, consists of a sub-optimal activity that might have short-term benefits but generates a negative impact in the medium-long term. PD identification is a key phase of PD management as it aims to determine the type of PD, where it is located, and how to estimate its impact. However, PD identification is the most challenging phase, as practitioners find it the most effort-intensive, mainly due to the immaterial nature of the process. In this paper, to mitigate the difficulties of PD identification, we propose a methodology that relies on frameworks compliant with the ISO/IEC 33000 family standard, the reference standard for process assessment. We also provide an exemplar application using the data from a process assessment performed using the Automotive SPICE, a framework compliant with the ISO/IEC 33000 requirements. An excerpt of the case study results is presented, showing the potential for a systematic and effective approach to PD identification.Source: COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE, vol. 2657, pp. 273-288. Riga, Latvia, 17-19/08/2025
DOI: 10.1007/978-3-032-04288-0_17
Metrics:
Lami G., Merola F.
Process Debt (PD), a concept derived from the Technical Debt, consists of a sub-optimal activity that might have short-term benefits but generates a negative impact in the medium-long term. PD identification is a key phase of PD management as it aims to determine the type of PD, where it is located, and how to estimate its impact. However, PD identification is the most challenging phase, as practitioners find it the most effort-intensive, mainly due to the immaterial nature of the process. In this paper, to mitigate the difficulties of PD identification, we propose a methodology that relies on frameworks compliant with the ISO/IEC 33000 family standard, the reference standard for process assessment. We also provide an exemplar application using the data from a process assessment performed using the Automotive SPICE, a framework compliant with the ISO/IEC 33000 requirements. An excerpt of the case study results is presented, showing the potential for a systematic and effective approach to PD identification.Source: COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE, vol. 2657, pp. 273-288. Riga, Latvia, 17-19/08/2025
DOI: 10.1007/978-3-032-04288-0_17
Metrics:
See at:
CNR IRIS | link.springer.com | CNR IRIS | CNR IRIS
2025
Journal article
Open Access
Automatic linguistic analysis of annotated text to improve standards development
Lami G., Merola F., Fusani M.
The draft Standards in progress, when accompanied by reviewers' comments, represent a clear example of annotated textual data and are therefore attractive for "supervised machine learning" analyses. This article describes an ongoing experiment in which a collection of annotated drafts is analyzed using automatic linguistic analysis techniques to identify effective solutions for improving the Standards creation process. The goal is to predict the parts of the standard that are prone to comments. The results achieved so far are presented and discussed along with new possible directions to take.Source: Journal of Visual Language and Computing, vol. 2025 (issue 2), pp. 35-42
Lami G., Merola F., Fusani M.
The draft Standards in progress, when accompanied by reviewers' comments, represent a clear example of annotated textual data and are therefore attractive for "supervised machine learning" analyses. This article describes an ongoing experiment in which a collection of annotated drafts is analyzed using automatic linguistic analysis techniques to identify effective solutions for improving the Standards creation process. The goal is to predict the parts of the standard that are prone to comments. The results achieved so far are presented and discussed along with new possible directions to take.Source: Journal of Visual Language and Computing, vol. 2025 (issue 2), pp. 35-42
See at:
CNR IRIS | ksiresearch.org | CNR IRIS
2025
Conference article
Open Access
Exploring the use of automatic linguistic analysis to improve standards development
Fusani M., Lami G., Merola F.
The draft Standards in progress, when accompanied by reviewers' comments, represent a clear example of annotated textual data and are therefore attractive for "supervised machine learning" analyses. This article describes an ongoing experiment, in which a collection of annotated drafts is analyzed through automatic linguistic analysis techniques using various methods to identify effective solutions for improving the Standards creation process through the capability to predict the parts of the standard that are prone to be commented. The results achieved so far are presented and discussed along with new possible directions to take.
Fusani M., Lami G., Merola F.
The draft Standards in progress, when accompanied by reviewers' comments, represent a clear example of annotated textual data and are therefore attractive for "supervised machine learning" analyses. This article describes an ongoing experiment, in which a collection of annotated drafts is analyzed through automatic linguistic analysis techniques using various methods to identify effective solutions for improving the Standards creation process through the capability to predict the parts of the standard that are prone to be commented. The results achieved so far are presented and discussed along with new possible directions to take.
See at:
CNR IRIS | ksiresearchorg.ipage.com | CNR IRIS
2025
Journal article
Open Access
Verifying robustness of neural networks in vision-based end-to-end autonomous driving
Bernardeschi C., Lami G., Merola F., Rossi F.
This paper addresses the verification of neural network robustness against perturbations of input data in vision-based end-to-end autonomous driving systems. The main contributions of this work are: i) We provide a comprehensive analysis of current neural-network-based perception and decision-making components in autonomous vehicles, highlighting their susceptibility to attacks or perturbation. ii) We develop and implement a novel framework for systematically evaluating and verifying the robustness of neural networks against such perturbations, focusing on imperceptible image modifications. iii) We present empirical results demonstrating our verification framework’s effectiveness in identifying weaknesses and providing probabilistic guarantees on network behavior. Our work underscores the critical need for robust verification methods to ensure the reliability and safety of autonomous driving systems, paving the way for safer integration of neural networks in autonomous vehicles.Source: IEEE ACCESS, vol. 13, pp. 71688-71704
DOI: 10.1109/access.2025.3563120
Metrics:
Bernardeschi C., Lami G., Merola F., Rossi F.
This paper addresses the verification of neural network robustness against perturbations of input data in vision-based end-to-end autonomous driving systems. The main contributions of this work are: i) We provide a comprehensive analysis of current neural-network-based perception and decision-making components in autonomous vehicles, highlighting their susceptibility to attacks or perturbation. ii) We develop and implement a novel framework for systematically evaluating and verifying the robustness of neural networks against such perturbations, focusing on imperceptible image modifications. iii) We present empirical results demonstrating our verification framework’s effectiveness in identifying weaknesses and providing probabilistic guarantees on network behavior. Our work underscores the critical need for robust verification methods to ensure the reliability and safety of autonomous driving systems, paving the way for safer integration of neural networks in autonomous vehicles.Source: IEEE ACCESS, vol. 13, pp. 71688-71704
DOI: 10.1109/access.2025.3563120
Metrics:
See at:
IEEE Access | IEEE Access | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2024
Journal article
Open Access
A risk assessment framework based on fuzzy logic for automotive systems
Merola F., Bernardeschi C., Lami G.
Recent advancements in the automotive field have significantly increased the level of complexity and connectivity of modern vehicles. In this context, the topic of cybersecurity becomes extremely relevant, as a successful attack can have an impact in terms of safety on the car navigation, potentially leading to harmful behavior. Risk assessment is typically performed using discrete input and output scales, which can often lead to an identical output in terms of risk evaluation despite the inputs presenting non-negligible differences. This work presents a novel fuzzy-logic-based methodology to assess cybersecurity risks which takes attack feasibility and safety impact as input factors. This technique allows us explicitly model the uncertainty and ambiguousness of input data, which is typical of the risk assessment process, providing an output on a more detailed scale. The fuzzy inference engine is based on a set of control rules expressed in natural language, which is crucial to maintaining the interpretability and traceability of the risk calculation. The proposed framework was applied to a case study extracted from ISO/SAE 21434. The obtained results are in line with the traditional methodology, with the added benefit of also providing the scatter around the calculated value, indicating the risk trend. The proposed method is general and can be applied in the industry independently from the specific case study.Source: SAFETY, vol. 10 (issue 2), pp. 1-21
DOI: 10.3390/safety10020041
Metrics:
Merola F., Bernardeschi C., Lami G.
Recent advancements in the automotive field have significantly increased the level of complexity and connectivity of modern vehicles. In this context, the topic of cybersecurity becomes extremely relevant, as a successful attack can have an impact in terms of safety on the car navigation, potentially leading to harmful behavior. Risk assessment is typically performed using discrete input and output scales, which can often lead to an identical output in terms of risk evaluation despite the inputs presenting non-negligible differences. This work presents a novel fuzzy-logic-based methodology to assess cybersecurity risks which takes attack feasibility and safety impact as input factors. This technique allows us explicitly model the uncertainty and ambiguousness of input data, which is typical of the risk assessment process, providing an output on a more detailed scale. The fuzzy inference engine is based on a set of control rules expressed in natural language, which is crucial to maintaining the interpretability and traceability of the risk calculation. The proposed framework was applied to a case study extracted from ISO/SAE 21434. The obtained results are in line with the traditional methodology, with the added benefit of also providing the scatter around the calculated value, indicating the risk trend. The proposed method is general and can be applied in the industry independently from the specific case study.Source: SAFETY, vol. 10 (issue 2), pp. 1-21
DOI: 10.3390/safety10020041
Metrics:
See at:
Safety | Safety | Archivio della Ricerca - Università di Pisa | IRIS Cnr | IRIS Cnr | Archivio della Ricerca - Università di Pisa | CNR IRIS
2024
Other
Open Access
PISA model process improvement scheme for automotive - Version: 3.0
Lami G., Falcini F.
The PISA model Version 3.0 provides the automotive community with an automotive-specific standard to support organization and project benchmarking in the context of technological developments, with a focus on software-intensive ones. The current version is an extension to address innovative aspects in developments of software-intensive automotive components. The PISA model natively targets the characteristics of automotive developments by incorporating automotive development key aspects. The PISA model provides a risk-oriented evaluation model in the context of a project and organization evaluation. This approach is beneficial for all stakeholders of the automotive supply chain. The purpose of the PISA model is to evaluate performance of an automotive development project and/or benchmark an organization using an automotive specific perspective.DOI: 10.32079/isti-tr-2024/006
DOI: https://doi.org/10.32079/isti-tr-2024/006
Metrics:
Lami G., Falcini F.
The PISA model Version 3.0 provides the automotive community with an automotive-specific standard to support organization and project benchmarking in the context of technological developments, with a focus on software-intensive ones. The current version is an extension to address innovative aspects in developments of software-intensive automotive components. The PISA model natively targets the characteristics of automotive developments by incorporating automotive development key aspects. The PISA model provides a risk-oriented evaluation model in the context of a project and organization evaluation. This approach is beneficial for all stakeholders of the automotive supply chain. The purpose of the PISA model is to evaluate performance of an automotive development project and/or benchmark an organization using an automotive specific perspective.DOI: 10.32079/isti-tr-2024/006
DOI: https://doi.org/10.32079/isti-tr-2024/006
Metrics:
2024
Conference article
Restricted
Integrating cybersecurity concerns in automotive safety validation: a systematic approach
Lami G., Merola F.
Automated vehicles (AV) are characterized by intelligent functions (many developed using AI-based solutions), autonomy, and high connectivity with the external environment. The high connectivity of AV opens relevant cybersecurity issues due to many potential attack surfaces. Cybersecurity attacks' effects on AV may also determine severe risks in terms of functional safety due to vehicles' high automation and autonomy. Safety validation of AV cannot be disjoint from the analysis and treatment of cybersecurity concerns. In this paper, we define a methodology called Combined Safety and Cybersecurity Validation (CSCV) aimed at strengthening, in a systematic manner, safety validation of AI-based functions of AV by addressing cybersecurity concerns. The CSCV methodology focuses on the emerging scenario-based approach for testing AI-based vehicle functions and is based on creating variants of the scenarios used for functional safety testing. The variants are derived from the original scenarios modified by the effects of highly risky cyberattacks that can occur during the scenario execution.DOI: 10.1109/icsrs63046.2024.10927483
Metrics:
Lami G., Merola F.
Automated vehicles (AV) are characterized by intelligent functions (many developed using AI-based solutions), autonomy, and high connectivity with the external environment. The high connectivity of AV opens relevant cybersecurity issues due to many potential attack surfaces. Cybersecurity attacks' effects on AV may also determine severe risks in terms of functional safety due to vehicles' high automation and autonomy. Safety validation of AV cannot be disjoint from the analysis and treatment of cybersecurity concerns. In this paper, we define a methodology called Combined Safety and Cybersecurity Validation (CSCV) aimed at strengthening, in a systematic manner, safety validation of AI-based functions of AV by addressing cybersecurity concerns. The CSCV methodology focuses on the emerging scenario-based approach for testing AI-based vehicle functions and is based on creating variants of the scenarios used for functional safety testing. The variants are derived from the original scenarios modified by the effects of highly risky cyberattacks that can occur during the scenario execution.DOI: 10.1109/icsrs63046.2024.10927483
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2023
Conference article
Restricted
Functional safety and cybersecurity improvement areas in automotive: an empirical study
Giuseppe Lami, Francesco Merola
Over the last decade, there has been an exponential increase in software-driven functions embedded in vehicles. In such a scenario, demands and needs regarding Functional Safety assurance have grown in criticality and complexity. As new- generation vehicles are characterized by high connectivity and autonomy, Functional Safety concerns can no longer be disjointed from Cybersecurity implications. To face such a situation, the automotive community has made enormous efforts to define methodologies, set up technologies, and enforce its culture.This paper presents the outcomes of an empirical study performed with the aim of identifying the current Functional Safety and Cybersecurity improvement areas in automotive software-intensive systems development. The study, conducted through an online questionnaire on a selected sample of automotive players, provided some interesting indications on which areas need to be improved the most.The results of the study show that the main improvement needs are related to methodologies deployed, tools in use, skills, and organizational structure for Cybersecurity and Integrated Functional Safety and Cybersecurity practices. In particular, the improvement need is higher for management aspects than engineering ones. We observed also that the need for improvement is markedly higher for small/medium companies than large ones.DOI: 10.1109/icsrs59833.2023.10381401
Metrics:
Giuseppe Lami, Francesco Merola
Over the last decade, there has been an exponential increase in software-driven functions embedded in vehicles. In such a scenario, demands and needs regarding Functional Safety assurance have grown in criticality and complexity. As new- generation vehicles are characterized by high connectivity and autonomy, Functional Safety concerns can no longer be disjointed from Cybersecurity implications. To face such a situation, the automotive community has made enormous efforts to define methodologies, set up technologies, and enforce its culture.This paper presents the outcomes of an empirical study performed with the aim of identifying the current Functional Safety and Cybersecurity improvement areas in automotive software-intensive systems development. The study, conducted through an online questionnaire on a selected sample of automotive players, provided some interesting indications on which areas need to be improved the most.The results of the study show that the main improvement needs are related to methodologies deployed, tools in use, skills, and organizational structure for Cybersecurity and Integrated Functional Safety and Cybersecurity practices. In particular, the improvement need is higher for management aspects than engineering ones. We observed also that the need for improvement is markedly higher for small/medium companies than large ones.DOI: 10.1109/icsrs59833.2023.10381401
Metrics:
2022
Other
Open Access
Processo di gestione dei flussi amministrativi delle certificazioni degli apparati per la memorizzazione elettronica e la trasmissione telematica dei dati dei corrispettivi giornalieri
Spagnolo Go, Cempini A, Falchi C, Lami G, Pierotti A, Puntoni M
Questo Rapporto Tecnico intende fornire una chiara e completa descrizione del nuovo processo di gestione dei flussi amministrativi nel contesto delle Certificazioni degli apparati per la memorizzazione elettronica e la trasmissione telematica dei dati dei corrispettivi giornalieri di cui all'art. 2, comma 1, del decreto legislativo 5 agosto 2015, n. 127 ai sensi del D.M. 23 marzo 1983 e secondo il provvedimento dell'Agenzia delle Entrate del 0182017 del 28 ottobre 2016 e successive modificazioni ed integrazioni.DOI: https://doi.org/10.32079/isti-tr-2022/020
DOI: 10.32079/isti-tr-2022/020
Metrics:
Spagnolo Go, Cempini A, Falchi C, Lami G, Pierotti A, Puntoni M
Questo Rapporto Tecnico intende fornire una chiara e completa descrizione del nuovo processo di gestione dei flussi amministrativi nel contesto delle Certificazioni degli apparati per la memorizzazione elettronica e la trasmissione telematica dei dati dei corrispettivi giornalieri di cui all'art. 2, comma 1, del decreto legislativo 5 agosto 2015, n. 127 ai sensi del D.M. 23 marzo 1983 e secondo il provvedimento dell'Agenzia delle Entrate del 0182017 del 28 ottobre 2016 e successive modificazioni ed integrazioni.DOI: https://doi.org/10.32079/isti-tr-2022/020
DOI: 10.32079/isti-tr-2022/020
Metrics:
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CNR IRIS | ISTI Repository | CNR IRIS
2022
Conference article
Restricted
Technical debt management in automotive software industry
Lami G, Spagnolo Go
The suppliers of software-intensive electronic automotive components are facing technical challenges due to the innovation rush and the growing time pressure from customers. As the quality of on-board automotive electronic systems is strongly dependent on the quality of their development practices, car manufacturers and suppliers proactively focus on improving technical and organizational processes. Automotive SPICE (ASPICE) is today the reference standard for assessing and improving automotive electronics processes and projects in this setting. As car manufacturers use ASPICE to qualify their suppliers of software-intensive systems, such a standard becomes a market demand. This paper identifies and discusses the benefits and impact of the integration and harmonization of Technical Debt Management (TDM) in an ASPICE- compliant software development project. Besides this paper provides a conceptual framework and a reference process description for the integration of ASPICE and TDM practices in a sample Software Engineering process.DOI: 10.1109/seaa56994.2022.00053
Metrics:
Lami G, Spagnolo Go
The suppliers of software-intensive electronic automotive components are facing technical challenges due to the innovation rush and the growing time pressure from customers. As the quality of on-board automotive electronic systems is strongly dependent on the quality of their development practices, car manufacturers and suppliers proactively focus on improving technical and organizational processes. Automotive SPICE (ASPICE) is today the reference standard for assessing and improving automotive electronics processes and projects in this setting. As car manufacturers use ASPICE to qualify their suppliers of software-intensive systems, such a standard becomes a market demand. This paper identifies and discusses the benefits and impact of the integration and harmonization of Technical Debt Management (TDM) in an ASPICE- compliant software development project. Besides this paper provides a conceptual framework and a reference process description for the integration of ASPICE and TDM practices in a sample Software Engineering process.DOI: 10.1109/seaa56994.2022.00053
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2022
Conference article
Open Access
A lightweight software product quality evaluation method
Lami G., Spagnolo G. O.
In this paper, we describe an evaluation method, called QuESPro (Quality Evaluation of Software Product), aimed at performing third party evaluation of the suitability for the intended use of software products, by targeting a trade-off between the mere informal expert judgment and the application of complex and expensive evaluation methods. The QuESPro is based on the framework provided by the ISO/IEC 25000 series standard and provides a step-wise process to determine a quantitative evaluation of the relevant quality characteristics of software products. With the aim of assessing the feasibility of the QuESPro method in terms of feasibility, identifying its strengths, and identifying improvement opportunities we applied it to an industrial case study. The results of such a case study are reported in this paper as well.DOI: 10.5220/0011316400003266
Metrics:
Lami G., Spagnolo G. O.
In this paper, we describe an evaluation method, called QuESPro (Quality Evaluation of Software Product), aimed at performing third party evaluation of the suitability for the intended use of software products, by targeting a trade-off between the mere informal expert judgment and the application of complex and expensive evaluation methods. The QuESPro is based on the framework provided by the ISO/IEC 25000 series standard and provides a step-wise process to determine a quantitative evaluation of the relevant quality characteristics of software products. With the aim of assessing the feasibility of the QuESPro method in terms of feasibility, identifying its strengths, and identifying improvement opportunities we applied it to an industrial case study. The results of such a case study are reported in this paper as well.DOI: 10.5220/0011316400003266
Metrics:
2021
Conference article
Open Access
System and software testing in automotive: an empirical study on process improvement areas
Falcini F., Lami G.
-- In the automotive domain, the development of software-intensive components is mainly demanded to particular suppliers that are required by car manufacturers a.k.a. OEMs (Original Equipment Manufacturer) to measure and, eventually, improve their development process by applying process models such as Automotive SPICE. Automotive SPICE is a widelyapplied reference framework providing a set of requested practices in the development life-cycle, including system and software testing. This paper aims at contributing in identifying what are the most frequent weaknesses in system and software testing in automotive. The authors present the results of an empirical study aimedat characterizing and analyzing recurrent system and software testing weaknesses in automotive. The authors, as Automotive SPICE assessors, have evaluated requirement management practices on the basis of the evidences gathered from real industrial development projects during a significant number of assessments performed at several organizations world-wide.This paper is intended to derive a picture of the state-of-thepractice of system and software testing in automotive focusing on the development of software-intensive automotive components. The purpose is to provide researchers and practitioners with a reference for improvement initiatives aimed at solving those weaknesses.DOI: 10.1109/icst49551.2021.00035
DOI: 10.5281/zenodo.4669973
DOI: 10.5281/zenodo.4669946
DOI: 10.5281/zenodo.4669974
DOI: 10.5281/zenodo.4669947
Metrics:
Falcini F., Lami G.
-- In the automotive domain, the development of software-intensive components is mainly demanded to particular suppliers that are required by car manufacturers a.k.a. OEMs (Original Equipment Manufacturer) to measure and, eventually, improve their development process by applying process models such as Automotive SPICE. Automotive SPICE is a widelyapplied reference framework providing a set of requested practices in the development life-cycle, including system and software testing. This paper aims at contributing in identifying what are the most frequent weaknesses in system and software testing in automotive. The authors present the results of an empirical study aimedat characterizing and analyzing recurrent system and software testing weaknesses in automotive. The authors, as Automotive SPICE assessors, have evaluated requirement management practices on the basis of the evidences gathered from real industrial development projects during a significant number of assessments performed at several organizations world-wide.This paper is intended to derive a picture of the state-of-thepractice of system and software testing in automotive focusing on the development of software-intensive automotive components. The purpose is to provide researchers and practitioners with a reference for improvement initiatives aimed at solving those weaknesses.DOI: 10.1109/icst49551.2021.00035
DOI: 10.5281/zenodo.4669973
DOI: 10.5281/zenodo.4669946
DOI: 10.5281/zenodo.4669974
DOI: 10.5281/zenodo.4669947
Metrics:
See at:
ZENODO | ZENODO | ZENODO | ZENODO | CNR IRIS | ieeexplore.ieee.org | dblp.uni-trier.de | doi.org | IRIS Cnr | IRIS Cnr | CNR IRIS | CNR IRIS
2020
Other
Open Access
Specifica DOCUMENTI COMMERCIALI Secondo il provvedimento dell'Agenzia delle Entrate del 248558/2020 del 30 Giugno 2020
Spagnolo Go, Serchiani G, Lami G
This Technical Report is intended to provide a clear and complete description of the new operations of the Telematic Registrator following the adoption by the Italian Tax Revenue Agency of Resolution 248558/2020 of 30 June 2020.DOI: https://doi.org/10.32079/isti-tr-2020/011
DOI: 10.32079/isti-tr-2020/011
Metrics:
Spagnolo Go, Serchiani G, Lami G
This Technical Report is intended to provide a clear and complete description of the new operations of the Telematic Registrator following the adoption by the Italian Tax Revenue Agency of Resolution 248558/2020 of 30 June 2020.DOI: https://doi.org/10.32079/isti-tr-2020/011
DOI: 10.32079/isti-tr-2020/011
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2020
Conference article
Open Access
Requirements management in automotive: an empirical study on process improvement areas
Falcini F, Lami G
In the automotive domain the development of software-intensive components is mainly demanded to specialized suppliers that are required by car manufacturers a.k.a. OEMs (Original Equipment Manufacturer) to measure and, eventually, improve their development process by applying process models such as Automotive SPICE. Automotive SPICE is therefore a widely-Applied reference framework providing a set of requested practices in the development life-cycle, including requirements management. Requirements management is a key issue in automotive because the high volatility of requirements during projects and the need of interactions among different stakeholders. This paper aims at contributing in identifying what are the most frequent weaknesses in requirements management in automotive. The authors present the results of an empirical study aimed at characterizing and analyzing recurrent requirement management weaknesses in automotive. The authors, as Automotive SPICE assessors, have evaluated requirement management practices on the basis of the evidences gathered from real industrial development projects during a significant number of assessments performed at several organizations world-wide. This paper is intended to derive a picture of the state-of-The-practice of requirements management in automotive focusing on the development of software-intensive automotive components. The purpose is to provide researchers and practitioners with a reference for improvement initiatives aimed at solving those weaknesses.DOI: 10.1109/re48521.2020.00037
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Falcini F, Lami G
In the automotive domain the development of software-intensive components is mainly demanded to specialized suppliers that are required by car manufacturers a.k.a. OEMs (Original Equipment Manufacturer) to measure and, eventually, improve their development process by applying process models such as Automotive SPICE. Automotive SPICE is therefore a widely-Applied reference framework providing a set of requested practices in the development life-cycle, including requirements management. Requirements management is a key issue in automotive because the high volatility of requirements during projects and the need of interactions among different stakeholders. This paper aims at contributing in identifying what are the most frequent weaknesses in requirements management in automotive. The authors present the results of an empirical study aimed at characterizing and analyzing recurrent requirement management weaknesses in automotive. The authors, as Automotive SPICE assessors, have evaluated requirement management practices on the basis of the evidences gathered from real industrial development projects during a significant number of assessments performed at several organizations world-wide. This paper is intended to derive a picture of the state-of-The-practice of requirements management in automotive focusing on the development of software-intensive automotive components. The purpose is to provide researchers and practitioners with a reference for improvement initiatives aimed at solving those weaknesses.DOI: 10.1109/re48521.2020.00037
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CNR IRIS | ieeexplore.ieee.org | ISTI Repository | doi.org | CNR IRIS | CNR IRIS
2019
Contribution to book
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Comparing results of natural language disambiguation tools with reports of manual reviews of safety-related standards
Biscoglio I, Ciancabilla A, Fusani M, Lami G, Trentanni G
Methods and tools for detecting and measuring ambiguity in texts have been proposed for years, yet their efficacy is still under study for improvement, encouraged by results in various application fields (requirements, legal documents, interviews, ...). The paper presents a fresh-started process aimed at validating such methods and tools by applying some of them to a semi-structured data corpus. This corpus represents results of manual reviews, done by international experts, along with their source texts. The purpose is to check how much results of automated analysis are consistent with the reviewers reports. The application domain is that of safety-related system/software Standards in Railway. Thus, if we increase confidence in tools, then we also increase confidence in Standard correctness, which in turn impacts in conforming products.DOI: 10.1007/978-3-030-30985-5_15
Metrics:
Biscoglio I, Ciancabilla A, Fusani M, Lami G, Trentanni G
Methods and tools for detecting and measuring ambiguity in texts have been proposed for years, yet their efficacy is still under study for improvement, encouraged by results in various application fields (requirements, legal documents, interviews, ...). The paper presents a fresh-started process aimed at validating such methods and tools by applying some of them to a semi-structured data corpus. This corpus represents results of manual reviews, done by international experts, along with their source texts. The purpose is to check how much results of automated analysis are consistent with the reviewers reports. The application domain is that of safety-related system/software Standards in Railway. Thus, if we increase confidence in tools, then we also increase confidence in Standard correctness, which in turn impacts in conforming products.DOI: 10.1007/978-3-030-30985-5_15
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doi.org | CNR IRIS | CNR IRIS | link.springer.com
2019
Contribution to book
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QuARS: a pioneer tool for NL requirement analysis
Lami G, Fusani M, Trentanni G
This paper summarizes the achievements of Stefania Gnesi's research activity in the area of the natural language requirements analysis and quality evaluation. The development of the QuARS tool has been the pivotal step of this research stream led by Stefania Gnesi at ISTI-CNR. A functional description of the QuARS tool is provided as well as a short report of its evolutions over a decade. The wide use of QuARS in several research and industrial contexts demonstrates the validity and the originality of Stefania's contribution in such an area of software engineering.DOI: 10.1007/978-3-030-30985-5_13
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Lami G, Fusani M, Trentanni G
This paper summarizes the achievements of Stefania Gnesi's research activity in the area of the natural language requirements analysis and quality evaluation. The development of the QuARS tool has been the pivotal step of this research stream led by Stefania Gnesi at ISTI-CNR. A functional description of the QuARS tool is provided as well as a short report of its evolutions over a decade. The wide use of QuARS in several research and industrial contexts demonstrates the validity and the originality of Stefania's contribution in such an area of software engineering.DOI: 10.1007/978-3-030-30985-5_13
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doi.org | CNR IRIS | CNR IRIS | link.springer.com
2019
Conference article
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Embracing software process improvement in automotive through PISA Model
Falcini F, Lami G
Vehicles innovation is principally driven by electronics components and software that play today a predominant role for the vehicle's functions. Because the quality of on-board automotive electronic systems is strongly dependent on the quality of their development practices, car-makers and suppliers proactively focused on improvement of technical and organizational processes. In this setting, several reference standards for the assessment and improvement of automotive electronics processes and projects have been conceived and used in the last decade. Although the effects of the application of them in automotive industry have been generally positive, getting compliance in the short period may represent, in some contexts, a target hardly achievable, or even a chimera. In this context, a novel scheme addressing both project evaluation and process improvement and targeting a hand-on approach for the practitioners has been recently developed starting from the analysis of practitioners needs and success factors in the software process improvement. This scheme is named Process Improvement Scheme for Automotive (PISA Model). The structure and contents of the PISA Model is described in this paper.DOI: 10.1007/978-3-030-35333-9_5
Metrics:
Falcini F, Lami G
Vehicles innovation is principally driven by electronics components and software that play today a predominant role for the vehicle's functions. Because the quality of on-board automotive electronic systems is strongly dependent on the quality of their development practices, car-makers and suppliers proactively focused on improvement of technical and organizational processes. In this setting, several reference standards for the assessment and improvement of automotive electronics processes and projects have been conceived and used in the last decade. Although the effects of the application of them in automotive industry have been generally positive, getting compliance in the short period may represent, in some contexts, a target hardly achievable, or even a chimera. In this context, a novel scheme addressing both project evaluation and process improvement and targeting a hand-on approach for the practitioners has been recently developed starting from the analysis of practitioners needs and success factors in the software process improvement. This scheme is named Process Improvement Scheme for Automotive (PISA Model). The structure and contents of the PISA Model is described in this paper.DOI: 10.1007/978-3-030-35333-9_5
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com