PowTrAn: An R Package for power trace analysis

Energy efficiency is an increasingly important non-functional property of software, especially when it runs on mobile or IoT devices. An engineering approach demands a reliable measurement of energy consumption of software while performing computational tasks. In this paper, we describe PowTrAn, an R package supporting the analysis of the power traces of a device executing software tasks. The tool analyzes traces with embedded markers, a non-invasive technique that enables gauging software efficiency based on the energy consumed by the whole device. The package effectively handles large power traces, detects work units, and computes correct energy measures, even in noisy conditions, such as those caused by multiple processes working simultaneously. PowTrAn was validated on applications in realistic conditions and multiple hardware configurations. PowTrAn also provides data visualization that helps the user to assess the measurement consistency, and it also helps to highlight possible energy outliers

How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review

Context: Machine Learning (ML) has been at the heart of many innovations over the past years. However, including it in so-called 'safety-critical' systems such as automotive or aeronautic has proven to be very challenging, since the shift in paradigm that ML brings completely changes traditional certification approaches. Objective: This paper aims to elucidate challenges related to the certification of ML-based safety-critical systems, as well as the solutions that are proposed in the literature to tackle them, answering the question 'How to Certify Machine Learning Based Safety-critical Systems?'. Method: We conduct a Systematic Literature Review (SLR) of research papers published between 2015 to 2020, covering topics related to the certification of ML systems. In total, we identified 217 papers covering topics considered to be the main pillars of ML certification: Robustness, Uncertainty, Explainability, Verification, Safe Reinforcement Learning, and Direct Certification. We analyzed the main trends and problems of each sub-field and provided summaries of the papers extracted. Results: The SLR results highlighted the enthusiasm of the community for this subject, as well as the lack of diversity in terms of datasets and type of models. It also emphasized the need to further develop connections between academia and industries to deepen the domain study. Finally, it also illustrated the necessity to build connections between the above mention main pillars that are for now mainly studied separately. Conclusion: We highlighted current efforts deployed to enable the certification of ML based software systems, and discuss some future research directions.Comment: 60 pages (92 pages with references and complements), submitted to a journal (Automated Software Engineering). Changes: Emphasizing difference traditional software engineering / ML approach. Adding Related Works, Threats to Validity and Complementary Materials. Adding a table listing papers reference for each section/subsection

Object Oriented Design Pattern Inference

When designing a new application, experienced software engineers usually try to employ solutions that proved successful in previous projects. Such reuse of code organizations is seldom made explicit. Nevertheless it represents important information about the system, that can be extremely valuable in the maintenance phase, by documenting the design choices underlying the implementation. In addition, having it available, it can be reused whenever a similar problem is encountered. In this paper an approach is proposed to the inference of recurrent design patterns directly from the code or the design. No assumption is made on the availability of any pattern library, and the concept analysis algorithm, adapted for this purpose, is able to infer the presence of class groups which instantiate a common, repeated pattern. In fact, concept analysis provides sets of objects sharing attributes, which, in the case of object oriented design patterns, become class members or inter-class relations. The approach was applied to a C++ application, for which the structural relations among classes led to the extraction of a set of structural design patterns, which could be enriched with non structural information about class members and method invocations. The resulting patterns could be interpreted as meaningful organizations aimed at solving general problems which have several instances in the analyzed application

Search-based techniques applied to optimization of project planning for a massive maintenance project

This paper evaluates the use of three different search– based techniques, namely genetic algorithms, hill climbing and simulated annealing, and two problem representations, for planning resource allocation in large massive maintenance projects. In particular, the search–based approach aims to find an optimal or near optimal order in which to allocate work packages to programming teams, in order to minimize the project duration. The approach is validated by an empirical study of a large, commercial Y2K massive maintenance project, which compares these techniques with each other and with a random search (to provide base line comparison data). Results show that an ordering-based genome encoding (with tailored cross over operator) and the genetic algorithm appear to provide the most robust solution, though the hill climbing approach also performs well. The best search technique results reduce the project duration by as much a

Make It Simple - An Empirical Analysis of GNU Make Feature Use in Open Source Projects

Abstract—Make is one of the oldest build technologies and is still widely used today, whether by manually writing Makefiles, or by generating them using tools like Autotools and CMake. Despite its conceptual simplicity, modern Make implementations such as GNU Make have become very complex languages, featuring functions, macros, lazy variable assignments and (in GNU Make 4.0) the Guile embedded scripting language. Since we are interested in understanding how widespread such complex language features are, this paper studies the use of Make features in almost 20,000 Makefiles, comprised of over 8.4 million lines, from more than 350 different open source projects. We look at the popularity of features and the difference between hand-written Makefiles and those generated using various tools. We find that generated Makefiles use only a core set of features and that more advanced features (such as function calls) are used very little, and almost exclusively in hand-written Makefiles. I

HER2-Low Status Does Not Affect Survival Outcomes of Patients with Metastatic Breast Cancer (MBC) Undergoing First-Line Treatment with Endocrine Therapy plus Palbociclib: Results of a Multicenter, Retrospective Cohort Study

Simple Summary Breast cancers (BCs) with a HER2 immunohistochemical score of 1+ or 2+ with negative in situ hybridization are referred as HER2-low BCs. The knowledge about the biological and clinical characteristics of HER2-low BCs is still limited and controversial. Despite that new anti-HER2 antibody-drug conjugates (ADCs) have demonstrated significant activity in HER2-low BCs, no anti-HER2 agents are currently approved for this subgroup in Europe. Therefore, treatment for HER2-low BCs is determined by HR expression status. In this study, we aimed to investigate the prognostic significance of HER2-low status in HR+/HER2 negative (HER2-) metastatic BC (MBC) patients treated with endocrine therapy (ET) plus palbociclib as first line. HR+ MBC patients with HER2-low tumors who received first-line treatment with ET plus palbociclib show similar survival outcomes compared to those HER2-0 disease. Background: Approximately 45-50% of breast cancers (BCs) have a HER2 immunohistochemical score of 1+ or 2+ with negative in situ hybridization, defining the "HER2-low BC" subtype. No anti-HER2 agents are currently approved for this subgroup in Europe, where treatment is still determined by HR expression status. In this study, we investigated the prognostic significance of HER2-low status in HR+/HER2- metastatic BC (MBC) patients treated with endocrine therapy (ET) plus palbociclib as first line. Methods: We conducted a retrospective study including 252 consecutive HR+/HER2- MBC patients who received first-line ET plus palbociclib at six Italian Oncology Units between March 2016 and June 2021. The chi-square test was used to assess differences in the distribution of clinical and pathological variables between the HER-0 and HER2-low subgroups. Survival outcomes, progression-free survival (PFS) and overall survival (OS), were calculated by the Kaplan-Meier method, and the log-rank test was performed to estimate the differences between the curves. Results: A total of 165 patients were included in the analysis: 94 (57%) and 71 (43%) patients had HER2-0 and HER2-low disease, respectively. The median age at treatment start was 64 years. No correlation between patients and tumor characteristics and HER2 status was found. Median PFS (mPFS) for the entire study cohort was 20 months (95% CI,18-25 months), while median OS (mOS) was not reached at the time of analysis. No statistically significant differences, in terms of PFS (p = 0.20) and OS (p = 0.1), were observed between HER2-low and HER2-0 subgroups. Conclusions: In our analysis, HR+ MBC patients with low HER2 expression who received first-line treatment with ET plus Palbociclib reported no statistically different survival outcomes compared to HER2-0 patients. Further prospective studies are needed to confirm the clinical role of HER2 expression level