New preprint: Seamless and Traceable Requirements

Maria Naumcheva, Sophie Ebersold, Jean-Michel Bruel and Bertrand Meyer, UOOR: Seamless and Traceable Requirements, submitted for publication, February 2025, preprint available on arXiv.

This article grew out of Maria Naumcheva’s PhD thesis defended on December 18 at the University of Toulouse (I will write separately about the thesis as a whole). It is part of a general effort at systematic requirements engineering, reflected in earlier articles by the some or all of the same group of authors (see my publication list) and in my requirements book. Here is a short version of the abstract for the article:

In industrial practice, requirements are an indispensable element of any serious software project. In the academic study of software engineering, requirements are one of the heavily researched subjects. And yet requirements engineering, as practiced in industry, makes shockingly sparse use of the concepts propounded in the requirements literature.

The present paper starts from an assumption about the causes for this situation and proposes a remedy to redress it. The posited explanation is that change is the major factor affecting the practical application of even the best-intentioned requirements techniques. No sooner has the ink dried on the specifications than the system environment and stakeholders’ views of the system begin to evolve.

The proposed solution is a requirements engineering method, called UOOR, which unifies many known requirements concepts and a few new ones in a framework entirely devised to accommodate and support seamless change throughout the project lifecycle. The method encompasses the commonly used requirements techniques such as scenarios, and integrates them into the seamless software development process. The work presented here introduces the notion of seamless requirements traceability, which relies on the propagation of traceability links, themselves based on formal properties of relations between project artifacts.

As a proof of concept, the paper presents a traceability tool to be integrated into a general-purpose IDE that provides the ability to link requirements to other software project artifacts, display notifications of changes in requirements, and trace those changes to the related project elements.

The UOOR approach is not just a theoretical proposal but has been designed for practical use and has been applied to a significant real-world case study: Roborace, a competition of autonomous racing cars.

Reminder: my full annotated publication list is here.

New preprint: Loop unrolling — formal definition and application to testing

Li Huang, Bertrand Meyer and Reto Weber, New preprint: Loop unrolling:  formal definition and application to testing, February 2025, submitted to publication. Available here on arXiv and also here.

Abstract

Testing coverage criteria usually make a gross simplification: they assume that loops will have their bodies executed 0 or 1 time. How much (specificall,y how many bugs) are we missing as a result?

This article defines loop unrolling formally (removing common misconceptions of the topic), shows how loop unrolling was applied to a testing framework (using program-proving techniques as well), in line with our test-and-proofs work of the past several years), and presents detailed empirical evidence about the effect on finding bugs.

(Some of the initial ideas were recorded earlier in an unpublished technical note.)

Reminder: my full annotated publication list is here.

New preprint: a standard framework for research on bugs and automatic program repair

Preprint of new article: Victoria Kananchuk, Ilgiz Mustafin and Bertrand Meyer, Bugfix: a standard language, database schema and repository for research on bugs and automatic program repair, submitted for publication, February 2025. Available on arXiv here. Also available here.

What this is in a nutshell (there is a longer abstract below): a proposal for, and first steps towards, helping work on Automatic Program Repair (APR) by providing a common framework, including: a language for describing bugs and fixes in a standard way; the same functionality available as an API (using JSON); and a repository (a database) accessible in that framework and containing  numerous bugs and fixes produced by researchers and practitioners.

The article draws on a short paper at the APR workshop of ICSE last year; I plan to use it as a basis for my keynote at the next workshop at ICSE in Ottawa on May 29. Rather than a paper describing firm results, this paper is meant to start a process; quoting from one of the final paragraphs:

The present work should be viewed as a community-service contribution: it is meant to help everyone interested in bugs and their automatic repair, particularly researchers in the field, to achieve new advances by relieving them of common and repetitive tasks, facilitating the assessment of new techniques, and making it possible to compare the effectiveness of competing or complementary approaches by providing a common reference.

It remains to see if anyone is interested!

Credits: much of the work (especially the construction of the repository) was carried out by Victoria Kananchuk as part of a master thesis; Ilgiz Mustafin particularly contributed to the JSON interface.

Here is the full abstract:

 

Automatic Program Repair (APR) is a brilliant idea: when detecting a bug, also provide suggestions for correct- ing the program.

Over the past decades, researchers have come up with promising techniques for making APR a mainstay of software development. Progress towards that goal is, however, hindered by the absence of a common frame of reference to support and compare the multiplicity of ideas, methods, tools, programming languages and programming environments for carrying out automatic program repair.

Bugfix, described in this article, is an effort at providing such a framework: a standardized set of notations, tools and interfaces, as well as a database of bugs and fixes, for use by the APR research community to try out its ideas and compare the results on an objective basis. The most directly visible component of the Bugfix effort is the Bugfix language, a human-readable formalism making it possible to describe elements of the following kinds: a bug (described abstractly, for example the permutation of two arguments in a call); a bug example (an actual occurrence of a bug, in a specific code written in a specific programming language, and usually recorded in some repository); a fix (a particular correction of a bug, obtained for example by reversing the misplaced arguments); an application (an entity that demonstrates how a actual code example matches with a fix); a construct (the abstract description of a programming mechanism, for example a “while” loop, independently of its realization in a programming language; and a language (a description of how a particular programming language includes certain constructs and provides specific concrete syntax for each of them — for example Java includes loop, assignment etc. and has a defined format for each of them).

The language is only one way to access this information. A JSON-based program interface (API) provides it in a form accessible to tools, which may record and access such information into databases.

Bugfix includes such a database (repository), containing a considerable amount of bugs, examples and fixes. We hope that this foundational work will help the APR research community to advance the field by providing a common yardstick and repository.

 

Reminder: my full annotated publication list is here.

New preprint: Software engineering as a domain to formalize

Bertrand Meyer, Software engineering as a domain to formalize, available here.

This article is meant as a blog but was written as a standard text and I haven’t had the time to HTML-ize yet. So I am just providing an abstract below, and linking to the PDF which gives the details.

The purpose is simple: start a community project. The description is prospective only and does not claim to describe a finished product. While simple, the idea is ambitious: define the field of software engineering through a formal theory. Unfortunately, much formal methods work) is axiom- and definition-rich and theorem-poor. Here, the goal is to produce the exact reverse: a good theory that starts with a minimal set of definitions and axioms, and tries to derive as many laws as possible.

Here is the abstract of the article:

Software engineering concepts and processes are worthy of formal study; and yet we seldom formalize them. This  article explores what a theory of software engineering could and should look like.


Software engineering research has developed formal techniques of specification and verification as an application of mathematics to specify and verify systems addressing needs of various application domains. These domains usually do not include the domain of software engineering itself. It is, however, a rich domain with many processes and properties that cry for formalization and potential verification.


This article outlines the structure of a possible theory of software engineering in the form of an object-oriented model, isolating abstractions corresponding to fundamental software concepts of project, milestone, code module, test and other staples of our field, and their mutual relationships. While the presentation is only a sketch of the full theory, it provides a set of guidelines for how a comprehensive and practical Theory of Software Engineering should (through an open-source community effort) be developed.

Please write to the author if you are interested in participating. The link to the PDF of the article again: here.

The French School of Programming

July 14 (still here for 15 minutes) is not a bad opportunity to announced the publication of a new book: The French School of Programming.

The book is a collection of chapters, thirteen of them, by rock stars of programming and software engineering research (plus me), preceded by a Foreword by Jim Woodcock and a Preface by me. The chapters are all by a single author, reflecting the importance that the authors attached to the project. Split into four sections after chapter 1, the chapters are, in order:

1. The French School of Programming: A Personal View, by Gérard Berry (serving as a general presentation of the subsequent chapters).

Part I: Software Engineering

2. “Testing Can Be Formal Too”: 30 Years Later, by  Marie-Claude Gaudel

3. A Short Visit to Distributed Computing Where Simplicity Is Considered a First-Class Property, by Michel Raynal

4. Modeling: From CASE Tools to SLE and Machine Learning, by Jean-Marc Jézéquel

5. At the Confluence of Software Engineering and Human-Computer Interaction: A Personal Account,  by Joëlle Coutaz

Part II:  Programming Language Mechanisms and Type Systems

6. From Procedures, Objects, Actors, Components, Services, to Agents, by  Jean-Pierre Briot

7. Semantics and Syntax, Between Computer Science and Mathematics, by Pierre-Louis Curien

8. Some Remarks About Dependent Type Theory, by Thierry Coquand

Part III: Theory

9. A Personal Historical Perspective on Abstract Interpretation, by Patrick Cousot

10. Tracking Redexes in the Lambda Calculus, by  Jean-Jacques Lévy

11. Confluence of Terminating Rewriting Computations, by  Jean-Pierre Jouannaud

Part IV: Language Design and Programming Methodology

12. Programming with Union, Intersection, and Negation Types, by Giuseppe Castagna

13, Right and Wrong: Ten Choices in Language Design, by Bertrand Meyer

What is the “French School of Programming”? As discussed in the Preface (although Jim Woodcock’s Foreword does not entirely agree) it is not anything defined in a formal sense, as the variety of approaches covered in the book amply demonstrates. What could be more different (for example) than Coq, OCaml (extensively referenced by several chapters) and Eiffel? Beyond the differences, however, there is a certain je ne sais quoi of commonality; to some extent, in fact, je sais quoi: reliance on mathematical principles, a constant quest for simplicity, a taste for elegance. It will be for the readers to judge.

Being single authors of their chapters, the authors felt free to share some of their deepest insights an thoughts. See for example Thierry Coquand’s discussion of the concepts that led to the widely successful Coq proof system, Marie-Claude Gaudel’s new look at her seminal testing work of 30 years ago, and Patrick Cousot’s detailed recounting of the intellectual path that led him and Radhia to invent abstract interpretation.


The French School of Programming
Edited by Bertrand Meyer
Springer, 2024. xxiv + 439 pages

Book page on Springer site
Amazon US page
Amazon France page
Amazon Germany page

The book is expensive (I tried hard to do something about it, and failed). But many readers should be able to download it, or individual chapters, for free through their institutions.

It was a privilege for me to take this project to completion and work with such extraordinary authors who produced such a collection of gems.

New article: scenarios versus OO requirements

Maria Naumcheva, Sophie Ebersold, Alexandr Naumchev, Jean-Michel Bruel, Florian Galinier and Bertrand Meyer: Object-Oriented Requirements: a Unified Framework for Specifications, Scenarios and Tests, in JOT (Journal of Object Technology), vol. 22, no. 1, pages 1:1-19, 2023. Available here with link to PDF  (the journal is open-access).

From the abstract:

A paradox of requirements specifications as dominantly practiced in the industry is that they often claim to be object-oriented (OO) but largely rely on procedural (non-OO) techniques. Use cases and user stories describe functional flows, not object types.

To gain the benefits provided by object technology (such as extendibility, reusability, and reliability), requirements should instead take advantage of the same data abstraction concepts – classes, inheritance, information hiding – as OO design and OO programs.

Many people find use cases and user stories appealing because of the simplicity and practicality of the concepts. Can we reconcile requirements with object-oriented principles and get the best of both worlds?

This article proposes a unified framework. It shows that the concept of class is general enough to describe not only “object” in a narrow sense but also scenarios such as use cases and user stories and other important artifacts such as test cases and oracles. Having a single framework opens the way to requirements that enjoy the benefits of both approaches: like use cases and user stories, they reflect the practical views of stakeholders; like object-oriented requirements, they lend themselves to evolution and reuse.

The article builds in part on material from chapter 7 of my requirements book (Handbook of Requirements and Business Analysis, Springer).

Logical beats sequential

Often,  “we do this and then we do that” is just a lazy way of stating “to do that, we must have achieved this.” The second form is more general than the first, since there may be many things you can “do” to achieve a certain condition.

The extra generality is welcome for software requirements, which should describe essential properties without over-specifying, in particular without prescribing a specific ordering of operations  when it is only one possible sequence among several, thereby restricting the flexibility of designers and implementers.

This matter of logical versus sequential constraints is at the heart of the distinction between scenario-based techniques — use cases, user stories… — and object-oriented requirements. This article analyzes the distinction. It is largely extracted from my recent textbook, the Handbook of Requirements and Business Analysis [1], which contains a more extensive discussion.

1. Scenarios versus OO

Scenario techniques, most significantly use cases and user stories, have become dominant in requirements. They obviously fill a need and are intuitive to many people. As a general requirement technique, however, they lack abstraction. Assessed against object-oriented requirements techniques, they suffer from the same limitations as procedural (pre-OO)  techniques against their OO competitors in the area of design and programming. The same arguments that make object technology subsume non-OO approaches in those areas transpose to requirements.

Scenario techniques describe system properties in terms of a particular sequence of interactions with the system. A staple example of a use case is ordering a product through an e-commerce site, going through a number of steps. In contrast, an OO specification presents a certain number of abstractions and operations on them, chracterized by their logical properties. This description may sound vague, so we move right away to examples.

2. Oh no, not stacks again

Yes, stacks. This example is rather computer-sciency so it is not meant to convince anyone but just to explain the ideas. (An example more similar to what we deal with in the requirements of industry projects is coming next.)

A stack is a LIFO (Last-In, First-Out) structure. You insert and remove elements at the same end.

 

Think of a stack of plates, where you can deposit one plate at a time, at the top, and retrieve one plate at a time, also at the top. We may call the two operations put and remove. Both are commands (often known under the alternative names push and pop). We will also use an integer query count giving the number of elements.

Assume we wanted to specify the behavior of a stack through use cases. Possible use cases (all starting with an empty stack) are:

/1/

put
put ; put
put ; put ; put       
— etc.: any number of successive put (our stacks are not bounded)

put ; remove
put ; put ; remove
put ; put ; remove ; remove
put ; put ; remove ; remove ; put ; remove

We should also find a way to specify that the system does not support such use cases as

/2/

remove ; put

or even just

/3/

remove

We could keep writing such use cases forever — some expressing normal sequences of operations, others describing erroneous cases — without capturing the fundamental rule that at any stage, the number of put so far has to be no less than the number of remove.

A simple way to capture this basic requirement is through logical constraints, also known as contracts, relying on assertions: preconditions which state the conditions under which an operation is permitted, and postconditions which describe properties of its outcome. In the example we can state that:

  • put has no precondition, and the postcondition

          count = old count + 1

using the old notation to refer to the value of an expression before the operation (here, the postcondition states that put increases count by one).

  • remove has the precondition

count > 0

and the postcondition

count = old count – 1

since it is not possible to remove an element from an empty stack. More generally the LIFO discipline implies that we cannot remove more than we have put.(Such illegal usage sequences are sometimes called “misuse cases.”)

(There are other properties, but the ones just given suffice for this discussion.)

The specification states what can be done with stacks (and what cannot) at a sufficiently high level of abstraction to capture all possible use cases. It enables us to keep track of the value of count in the successive steps of a use case; it tells us for example that all the use cases under /1/ above observe the constraints: with count starting at 0, taking into account the postconditions of put and remove, the precondition of every operation will be satisfied prior to all of its calls. For /2/ and /3/ that is not the case, so we know that these use cases are incorrect.

Although this example covers a data structure, not  requirements in the general sense, it illustrates how logical constraints are more general than scenarios:

  • Use cases, user stories and other  forms of scenario only describe specific instances of behavior.
  • An OO model with contracts yields a more abstract specification, to which individual scenarios can be shown to conform, or not.

3. Avoiding premature ordering decisions

As the stack example illustrates, object-oriented specifications stay away from premature time-order decisions by focusing on object types (classes) and their operations (queries and commands), without making an early commitment to the order of executing these operations.

In the book, I use in several places a use-case example from one of the best books about use cases (along with Ivar Jacobson’s original one of course): Alistair Cockburn’s Writing Effective Use Cases (Pearson Education, 2001). A simplified form of the example is:

1. A reporting party who is aware of the event registers a loss to the insurance company.

2. A clerk receives and assigns claim to a claims agent.

3. The assigned claims adjuster:

3.1 Conducts an investigation.
3.2 Evaluates damages.
3.3 Sets reserves.
3.4 Negotiates the claim.
3.5 Resolves the claim and closes it.

(A reserve in the insurance business is an amount that an insurer, when receiving a claim, sets aside as to cover the financial liability that may result from the claim.)

As a specification, this scenario is trying to express useful things; for example, you must set reserves before starting to negotiate the claim. But it expresses them in the form of a strict sequence of operations, a temporal constraint which does not cover the wide range of legitimate scenarios. As in the stack example, describing a few such scenarios is helpful as part of requirements elicitation, but to specify the resulting requirements it is more effective to state the logical constraints.

Here is a sketch (in Eiffel) of how a class INSURANCE_CLAIM could specify them in the form of contracts. Note the use of require to introduce a precondition and ensure for postconditions.

class INSURANCE_CLAIM feature

        — Boolean queries (all with default value False):
    is_investigated, is_evaluated, is_reserved,is_agreed,is_imposed, is_resolved:

BOOLEAN

    investigate
                — Conduct investigation on validity of claim. Set is_investigated.
        deferred
        ensure
            is_investigated
        end

    evaluate
                — Assess monetary amount of damages.
        require
            is_investigated
        deferred
        ensure
            is_evaluated
            — Note: is_investigated still holds (see the invariant at the end of the class text).
        end

    set_reserve
                — Assess monetary amount of damages. Set is_reserved.
        require
            is_investigated
            — Note: we do not require is_evaluated.
        deferred
        ensure
            is_reserved
        end
 

    negotiate
                — Assess monetary amount of damages. Set is_agreed only if negotiation
                — leads to an agreement with the claim originator.
        require
                   is_reserved
is_evaluated   
                   

        deferred
        ensure
            is_reserved
            — See the invariant for is_evaluated and is_investigated.
        end

    impose (amount: INTEGER)
                — Determine amount of claim if negotiation fails. Set is_imposed.
        require
            not is_agreed
            is_reserved
        deferred
        ensure
            is_imposed
        end

    resolve
                — Finalize handling of claim. Set is_resolved.
        require
            is_agreed or is_imposed
        deferred
        ensure
            is_resolved
        end

invariant                    — “⇒” is logical implication.

is_evaluated is_investigated
is_reserved 
is_evaluated
is_resolved
is_agreed or is_imposed
is_agreed
is_evaluated
is_imposed
is_evaluated
is_imposed
not is_agreed

                          — Hence, by laws of logic, is_agreed not is_imposed

end

Notice the interplay between the preconditions, postconditions and class invariant, and the various boolean-valued queries they involve (is_investigated, is_evaluated, is_reserved…). You can specify a strict order of operations o1, o2 …, as in a use case, by having a sequence of assertions pi such that operation oi has the contract clauses require pi and ensure pi+1; but assertions also enable you to specify a much broader range of allowable orderings as all acceptable.
The class specification as given is only a first cut and leaves many aspects untouched. It will be important in practice, for example, to include a query payment describing the amount to be paid for the claim; then impose has the postcondition payment = amount, and negotiate sets a certain amount for payment.
Even in this simplified form, the specification includes a few concepts that the original use case left unspecified, in particular the notion of imposing a payment (through the command impose) if negotiation fails. Using a logical style typically uncovers such important questions and provides a framework for answering them, helping to achieve one of the principal goals of requirements engineering.

4. Logical constraints are more general than sequential orderings

The specific sequence of actions described in the original use case (“main success scenario”) is compatible with the logical constraints: you can check that in the sequence

investigate
evaluate
set_reserve
negotiate
resolve

the postcondition of each step implies the precondition of the next one (the first has no precondition). In other words, the temporal specification satisfies the logical one. But you can also see that prescribing this order is a case of overspecification: other orderings also satisfy the logical specification. It may be possible for example — subject to confirmation by Subject-Matter Experts — to change the order of evaluate and set_reserve, or to perform these two operations in parallel.

The specification does cover the fundamental sequencing constraints; for example, the pre- and postcondition combinations imply that investigation must come before evaluation and resolution must be preceded by either negotiation or imposition. But they avoid the non-essential constraints which, in the use case, were only an artifact of the sequential style of specification, not a true feature of the problem.

The logical style is also more conducive to conducting a fruitful dialogue with domain experts and stakeholders:

  • With a focus on use cases, the typical question from a requirements engineer (business analyst) is “do you do A before doing B?” Often the answer will be contorted, as in “usually yes, but only if C, oh and sometimes we might start with B if D holds, or we might work on A and B in parallel…“, leading to vagueness and to more complicated requirements specifications.
  • With logic-based specifications, the two fundamental question types are: “what conditions do you need before doing B?” and “does doing A ensure condition C?”. They force stakeholders to assess their own practices and specify precisely the relations between operations of interest.

5. What use for scenarios?

Use-cases and more generally scenarios, while more restrictive than logical specifications, remain important as complements to specifications. They serve as both input and output to more abstract requirements specifications (such as OO specifications with contracts):

  • As input to requirements: initially at least, stakeholders and Subject-Matter Experts often find it intuitive to describe typical system interactions, and their own activities, in the form of scenarios. Collecting such scenarios is an invaluable requirements elicitation technique. The requirements engineer must remember that any such scenario is just one example walk through the system, and must abstract from these examples to derive general logical rules.
  • As output from requirements: from an OO specification with its contracts, the requirements engineers can produce valid use cases. “Valid” means that the operation at every step satisfies the applicable precondition, as a consequence of the previous steps’ postconditions and of the class invariant. The requirements engineers can then submit these use cases to the SMEs and through them to stakeholders to confirm that they make sense, update the logical conditions if they do not (to rule out bad use cases), and check the results they are expected to produce.

6. Where do scenarios fit?

While many teams will prefer to write scenarios (for the purposes just described) in natural language, it is possible to go one step further and, in an object-oriented approach to requirements, gather scenarios in classes. But that point exceeds the scope of the present sketch. We will limit ourselves here to the core observation: logical constraints subsume sequential specifications; you can deduce the ltter from the former, but not the other way around; and focusing on abstract logical specifications leads to a better understanding of the requirements.

Reference

Bertrand Meyer: Handbook of Requirements and Business Analysis, Springer, 2022. See the book page with sample chapters and further material here.

Recycled(This article was first published on the Communications of the ACM blog.)

New paper: optimization of test cases generated from failed proofs

Li Huang (PhD student at SIT) will be presenting at an ISSRE workshop the paper Improving Counterexample Quality from Failed Program Verification, written with Manuel Oriol and me. One can find the text on arXiv here. (I will update this reference with the official publication link when I have it.)

The result being presented is part of a more general effort at combining proofs and tests (with other papers in the pipeline). The idea of treating proofs and tests as complementary rather than competing methods of software verification is an old pursuit of mine (which among other consequences resulted in the creation with Yuri Gurevich of the Tests and Proofs conference, which I see is continuing to run). A particular observation is that failure means a different thing for proofs and tests.

A failed test provides interesting information (in fact it is a successful proof — of incorrectness). A successful proof is, of course, also interesting (in principle it should be end of the story), whereas a successful test tells us very little. But in the practice of program proving the common occurrence is failure to prove a program element correct. You are typically left with no clue as to the source of the failure. In the AutoProof verification system for Eiffel, we are able to rely on the underlying technology (Boogie and Z3) to extract a counterexample which gives concrete evidence: as with a failed test, a programmer can in general quickly understand what is wrong.

In other words, the useless negative result of the bottom-left entry of the above picture can produce a useful result:

Pasted

The general approach is the subject of another article but this one focuses on producing tests that are actually significant for the programmer. If you get very large values, you will not immediately be able to relate to them. Hence the need for a process of minimization, described in the article. The results on our examples are encouraging, making it possible to evidence the bug on very small integer values.

Reference

Li Huang, Bertrand Meyer and Manuel Oriol: Improving Counterexample Quality from Failed Program Verification, 6th International Workshop on Software Faults, October 2022. Preprint available on arXiv here. The program workshop is available here; the presentation is on Monday, 31 October, 15:55 CET (7:55 AM Los Angeles, 10:55 New York).

 

Introduction to the Theory of Programming Languages: full book now freely available

itpl_coverShort version: the full text of my Introduction to the Theory of Programming Languages book (second printing, 1991) is now available. This page has more details including the table of chapters, and a link to the PDF (3.3MB, 448 + xvi pages).

The book is a survey of methods for language description, particularly semantics (operational, translational, denotational, axiomatic, complementary) and also serves as an introduction to formal methods. Obviously it would be written differently today but it may still have its use.

A few days ago I released the Axiomatic Semantics chapter of the book, and the chapter introducing mathematical notations. It looked at the time that I could not easily  release the rest in a clean form, because it is impossible or very hard to use the original text-processing tools (troff and such). I could do it for these two chapters because I had converted them years ago for my software verification classes at ETH.

By perusing old files, however,  I realized that around the same time (early 2000s) I actually been able to produce PDF versions of the other chapters as well, even integrating corrections to errata  reported after publication. (How I managed to do it then I have no idea, but the result looks identical, save the corrections, to the printed version.)

The figures were missing from that reconstructed version (I think they had been produced with Brian Kernighan’s PIC graphical description language , which is even more forgotten today than troff), but I scanned them from a printed copy and reinserted them into the PDFs.

Some elements were missing from my earlier resurrection: front matter, preface, bibliography, index. I was able to reconstruct them from the original troff source using plain MS Word. The downside is that they are not hyperlinked; the index has the page numbers (which may be off by 1 or 2 in some cases because of reformatting) but not hyperlinks to the corresponding occurrences as we would expect for a new book. Also, I was not able to reconstruct the table of contents; there is only a chapter-level table of contents which, however, is hyperlinked (in other words, chapter titles link to the actual chapters). In the meantime I obtained the permission of the original publisher (Prentice Hall, now Pearson Education Inc.).

Here again is the page with the book’s description and the link to the PDF:

bertrandmeyer.com/ITPL

 

 

OOSC-2 available online (officially)

My book Object-Oriented Software Construction, 2nd edition (see the Wikipedia page) has become hard to get. There are various copies floating around the Web but they often use bad typography (wrong colors) and are unauthorized.

In response to numerous requests and in anticipation of the third edition I have been able to make it available electronically (with the explicit permission of the original publisher).

You can find the link on another page on this site. (In sharing or linking please use that page, not the URL of the actual PDF which might change.)

I hope having the text freely available proves useful.