Lessons Learned in a Journey Toward Correct-by-Construction Model-Based Development

Author(s):  
Laura Baracchi ◽  
Silvia Mazzini ◽  
Stefano Puri ◽  
Tullio Vardanega
Author(s):  
TAGHI M. KHOSHGOFTAAR ◽  
EDWARD B. ALLEN ◽  
ARCHANA NAIK ◽  
WENDELL D. JONES ◽  
JOHN P. HUDEPOHL

High software reliability is an important attribute of high-assurance systems. Software quality models yield timely predictions of quality indicators on a module-by-module basis, enabling one to focus on finding faults early in development. This paper introduces the Classification And Regression Trees (CART) a algorithm to practitioners in high-assurance systems engineering. This paper presents practical lessons learned on building classification trees for software quality modeling, including an innovative way to control the balance between misclassification rates. A case study of a very large telecommunications system used CART to build software quality models. The models predicted whether or not modules would have faults discovered by customers, based on various sets of software product and process metrics as independent variables. We found that a model based on two software product metrics had comparable accuracy to a model based on forty product and process metrics.


2018 ◽  
Author(s):  
Εμμανουέλα Στάχτιαρη

Η παρούσα διατριβή εισάγει τεχνικές για την αυστηρή και από κατασκευής ορθή σχεδίαση συστημάτων. Ειδικότερα, εστιάσαμε στο πώς μπορούμε να παράγουμε και να επικυρώνουμε ένα λειτουργικό μοντέλο της εφαρμογής που προκύπτει από ένα σύνολο απαιτήσεων ή από τον κώδικα της εφαρμογής. Αρχικά, ασχοληθήκαμε με την πρώιμη επικύρωση των απαιτήσεων και της σχεδίασης του συστήματος, ώστε να εξαλειφθεί η ανάγκη επαλήθευσης εκ των υστέρων και να περιοριστούν οι έλεγχοι επικύρωσης κατά τα τελευταία στάδια ανάπτυξης. Δεύτερον, εστιάσαμε στην αυτόματη δημιουργία λειτουργικών μοντέλων εφαρμογών από προγράμματα με εμφωλευμένη σύνταξη, διατηρώντας τη σημασιολογία των προγραμμάτων. Τέλος, προτείναμε μία ροή σχεδίασης που αποσκοπεί στη διατήρηση της συνέπειας μεταξύ του λειτουργικού μοντέλου και του κώδικα εφαρμογής μέσω της χρήσης μιας νέας γλώσσας ειδικού σκοπού, κατάλληλης για τη σχεδίαση συστημάτων περιορισμένων πόρων του διαδικτύου των αντικειμένων.


Author(s):  
Moria Levy ◽  
Rinat Salem

Lesson learning is a well-known and crucial organizational tool that serves many organizations wishing to improve their performance. This chapter describes a knowledge management (KM)-based model, improving the level of learning and of the lessons learned with the goal of reducing repeated mistakes as well as recreating their successes. The key features of the model were the base of a research conducted using a case study approach implemented at the Welfare Division of the Jerusalem Municipality's Community Services Administration. The implemented model, based on KM ideas, added two significant stages to the process of debriefing—refining the lessons learned and transforming them into lessons that are managed in an independent database—as well as an additional stage, which was comprised of active processes of integrating the lessons into the organizational work.


2016 ◽  
Vol 13 (12) ◽  
pp. 9927-9931
Author(s):  
Xilian Huang ◽  
Jun Dan ◽  
Ruwei Tang

2011 ◽  
Vol 186 ◽  
pp. 251-255 ◽  
Author(s):  
Jun Feng Tian ◽  
Ye Zhu

Due to not considering the guaranty of trustiness, traditional software development methods and techniques lack effective measures for ensuring trustiness. Combining agent technique with trusted computing provided by TPM, a trusted software construction model based on Trust Shell (TSCMTS) is demonstrated in this paper, where Trust Shell is responsible for ensuring the trustiness of software logically. In particular, for the purpose of improving the accuracy of trustiness constraints, a strategy of determining multiple attributes’ weights by information entropy for check point is proposed. Both simulation experiment results and practical application indicate that the TSCMTS is of effective trustiness and reasonable performance overhead.


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