PhD Position F/M PhD Position - Actionable Analytics for Software Production Contexts (F/M)

PhD Position F/M PhD Position - Actionable Analytics for Software Production Contexts (F/M) Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : PhD Position About the research centre or Inria department Created in 2008, the Inria center at the University of Lille employs 360 people, including 305 scientists in 16 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center at the University of Lille maintains a close relationship with large companies and SMEs. By fostering synergies between researchers and industry, Inria contributes to the transfer of skills and expertise in the field of digital technologies, and provides access to the best of European and international research for the benefit of innovation and businesses, particularly in the region. For over 10 years, the Inria center at the University of Lille has been at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT). Context Industrial Context: Berger-Levrault designs and maintains software solutions for public administrations in highly regulated sectors, such as education, healthcare, social services, and regional management. These products are built for the long term: they must continue to evolve while incorporating technological, organizational, and architectural choices accumulated over several decades. In this context, understanding software involves more than just reading its code. Major challenges also lie in its production context: change history, tickets, reviews, pipelines, knowledge sharing, and the distribution of responsibilities. The thesis aims to model and analyze this environment to produce insights useful for system maintenance and evolution. Organization of the research work: The doctoral student will be jointly supervised by Berger-Levrault and the EVREF team at Inria Lille, in order to align industrial needs, expertise in software maintenance and evolution, and tool development on Moose. The proposed timeline is organized into three phases: • scientific framing and modeling, • integration and correlation of sources, • followed by evaluation of prototypes and dissemination of results. References: [BBN+17] Lionel Briand, Domenico Bianculli, Shiva Nejati, Fabrizio Pastore, and Mehrdad Sabetzadeh. The case for context-driven software engineering research. IEEE Software, September 2017. [DDN02] Serge Demeyer, Stéphane Ducasse, and Oscar Nierstrasz. Object-Oriented Reengineering Patterns. Morgan Kaufmann, 2002. [MZ13] Tim Menzies and Thomas Zimmermann. Software analytics : So what ? IEEE Software, July 2013. [Per21] Quentin Perez. Gestion des contributions architecturales dans les projets logiciels : Métriques, analyses empiriques et apprentissage machine. Phd thesis, 2021. Assignment Background and objectives of the Thesis: Legacy information systems face challenges related to longevity, transformation, and risk [DDN02]. Code aging, knowledge loss, and technical debt are exacerbated by the fragmentation of software development across multiple tools, even though it is often this fragmentation that accounts for maintenance difficulties. Recurring problems fall into three categories: a loss of overall visibility due to the fragmentation of information across code, tickets, reviews, and pipelines; a loss or concentration of knowledge linked to staff turnover; and high-risk changes due to the inability to link software structure, development activity, and work organization. Thesis objectives: The thesis aims to define a unified framework for analyzing the software production context, implement it as a Moose extension capable of linking code, tickets, reviews, and pipelines, and then produce actionable analyses and visualizations to help identify expertise, unstable areas, knowledge concentrations, and maintenance risks. These objectives will be evaluated using representative case studies from Berger-Levrault. Main activities Industrial and scientific challenges for Berger-Levrault: Scientific Challenges: This thesis is grounded in the framework of actionable analytics [MZ13, BBN+17]: producing contextualized, interpretable analyses that are useful for decision-making. Three key challenges structure the topic: defining an extensible metamodel of the production context, correlating heterogeneous sources to reconstruct relevant units of analysis, and transforming this data into actionable indicators and visualizations for maintenance. Technical challenges: The main technical challenges involve defining a metamodel common to multiple platforms, establishing robust relationships between code, tickets, reviews, and pipelines, and scaling up processing in an industrial setting. Proposed solutions: The thesis will propose an extension of Moose dedicated to analyzing the software production context. It will focus on integrating data from repositories, forges, tickets, and pipelines; linking them within a common metamodel; and then producing analyses useful to teams: identifying expertise, pinpointing knowledge concentrations, characterizing maintenance cycles, and presenting results through visualizations tailored to industrial needs. Related work: Research on understanding legacy systems highlights the importance of linking software structure and maintenance activities [DDN02]. More recently, Perez [Per21] has shown that ownership can be characterized by the nature of the modified artifacts. The proposed research extends this approach by aiming for a unified modeling of the production context, at the intersection of reverse engineering, metamodeling, process mining, and visualization. Skills Languages: • French and English Spoken and written Additional skills preferred: • Oral presentation • Writing (articles, reports) Benefits package • Subsidized meals • Partial reimbursement of public transport costs • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) • Possibility of teleworking and flexible organization of working hours • Professional equipment available (videoconferencing, loan of computer equipment, etc.) • Social, cultural and sports events and activities • Access to vocational training • Social security coverage Remuneration €2,300 gross per month Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Distributed programming and Software engineering • Town/city : Villeneuve d'Ascq • Inria Center : Centre Inria de l'Université de Lille • Starting date : 2026-11-01 • Duration of contract : 3 years • Deadline to apply : 2026-09-30 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Please provide your CV and cover letter Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : EVREF • PhD Supervisor : Ducasse Stephane / Stephane.Ducasse@inria.fr The keys to success Development: • Object-oriented programming • Metaprogramming • Metamodeling • Design patterns Process: • TDD • Refactoring Tools: • Git • Statistics • Visualization • Data analytics About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.