Tag Archives: peer code review

Research Experiment: A Recap

Before I start diving into results, I’m just going to recap my experiment so we’re all up to speed.

I’ll try to keep it short, sweet, and punchy – but remember, this is a couple of months of work right here.

Ready?  Here we go.

What I was looking for

A quick refresher on what code review is

Code review is like the software industry equivalent of a taste test.  A developer makes a change to a piece of software, puts that change up for review, and a few reviewers take a look at that change to make sure it’s up to snuff.  If some issues are found during the course of the review, the developer can go back and make revisions.  Once the reviewers give it the thumbs up, the change is put into the software.

That’s an oversimplified description of code review,  but it’ll do for now.

So what?

What’s important is to know that it works. Jason Cohen showed that code review reduces the number of defects that enter the final software product. That’s great!

But there are some other cool advantages to doing code review as well.

  1. It helps to train up new hires.  They can lurk during reviews to see how more experienced developers look at the code.  They get to see what’s happening in other parts of the software.  They get their code reviewed, which means direct, applicable feedback.  All good things.
  2. It helps to clean and homogenize the code.  Since the code will be seen by their peers, developers are generally compelled to not put up “embarrassing” code (or, if they do, to at least try to explain why they did).  Code review is a great way to compel developers to keep their code readable and consistent.
  3. It helps to spread knowledge and good practices around the team.  New hires aren’t the only ones to benefit from code reviews.  There’s always something you can learn from another developer, and code review is where that will happen.  And I believe this is true not just for those who receive the reviews, but also for those who perform the reviews.

That last one is important.  Code review sounds like an excellent teaching tool.

So why isn’t code review part of the standard undergraduate computer science education?  Greg and I hypothesized that the reason that code review isn’t taught is because we don’t know how to teach it.

I’ll quote myself:

What if peer code review isn’t taught in undergraduate courses because we just don’t know how to teach it?  We don’t know how to fit it in to a curriculum that’s already packed to the brim.  We don’t know how to get students to take it seriously.  We don’t know if there’s pedagogical value, let alone how to show such value to the students.

The idea

Inspired by work by Joordens and Pare, Greg and I developed an approach to teaching code review that integrates itself nicely into the current curriculum.

Here’s the basic idea:

Suppose we have a computer programming class.  Also suppose that after each assignment, each student is randomly presented with anonymized assignment submissions from some of their peers.  Students will then be asked to anonymously peer grade these assignment submissions.

Now, before you go howling your head off about the inadequacy / incompetence of student markers, or the PeerScholar debacle, read this next paragraph, because there’s a twist.

The assignment submissions will still be marked by TA’s as usual.  The grades that a student receives from her peers will not directly affect her mark.  Instead, the student is graded based on how well they graded their peers. The peer reviews that a student completes will be compared with the grades that the TA’s delivered.  The closer a student is to the TA, the better the mark they get on their “peer grading” component (which is distinct from the mark they receive for their programming assignment).

Now, granted, the idea still needs some fleshing out, but already, we’ve got some questions that need answering:

  1. Joordens and Pare showed that for short written assignments, you need about 5 peer reviews to predict the mark that the TA will give.  Is this also true for computer programming assignments?
  2. Grading students based on how much their peer grading matches TA grading assumes that the TA is an infallible point of reference.  How often to TA’s disagree amongst themselves?
  3. Would peer grading like this actually make students better programmers?  Is there a significant difference in the quality of their programming after they perform the grading?
  4. What would students think of peer grading computer programming assignments?  How would they feel about it?

So those were my questions.

How I went about looking for the answers

Here’s the design of the experiment in a nutshell:

Writing phase

I have a treatment group, and a control group.  Both groups are composed of undergraduate students.  After writing a short pre-experiment questionnaire, participants in both groups will have half an hour to work on a short programming assignment.  The treatment group will then have another half an hour to peer grade some submissions for the assignment they just wrote.  The submissions that they mark will be mocked up by me, and will be the same for each participant in the treatment group.  The control group will not perform any grading – instead, they will do an unrelated vocabulary exercise for the same amount of time.  Then, participants in either group will have another half an hour to work on the second short programming assignment. Participants in my treatment group will write a short post-experiment questionnaire to get their impressions on their peer grading experience.  Then the participants are released.

Here’s a picture to help you visualize what you just read.

Tasks for each group in my experiment.

So now I’ve got two piles of submissions – one for each assignment, 60 submissions in total.  I add my mock-ups to each pile.  That means 35 submissions in each pile, and 70 submissions in total.

Marking phase

I assign ID numbers to each submission, shuffle them up, and hand them off to some graduate level TA’s that I hired.  The TA’s will grade each assignment using the same marking rubric that the treatment group used to peer grade.  They will not know if they are grading a treatment group submission, a control group submission, or a mock-up.

Choosing phase

After the grading is completed, I remove the mock-ups, and pair up submissions in both piles based on who wrote it.  So now I’ve got 30 pairs of submissions:  one for each student.  I then ask my graders to look at each pair, knowing that they’re both written by the same student, and to choose which one they think is better coded, and to rate and describe the difference (if any) between the two.  This is an attempt to catch possible improvements in the treatment group’s code that might not be captured in the marking rubric.

So that’s what I did

So everything you’ve just read is what I’ve just finished doing.

Once the submissions are marked, I’ll analyze the marks for the following:

  1. Comparing the two groups, is there any significant improvement in the marks from the first assignment to the second in the treatment group?
    1. If there was an improvement, on which criteria?  And how much of an improvement?
  2. How did the students do at grading my mock-ups?  How similar were their peer grades to what the TAs gave?
  3. How much did my two graders agree with one another?
  4. During the choosing phase, did my graders tend to choose the second assignment over the first assignment more often for the treatment group?

And I’ll also analyze the post-experiment questionnaire to get student feedback on their grading experience.

Ok, so that’s where I’m at.  Stay tuned for results.

Exploring Peer Review in the Computer Science Classroom: Part 1

Exploring Peer Review in the Computer Science Classroom

by Scott Turner and Manuel A. Pérez Quiñones

I’m new at reading papers, so I’ve gotten used to 5 or 10 page-ers.  This looks like the big one, though – 69 pages.

I assume they have something significant to say.  The title sure sounds interesting, especially considering what I’m looking for.

Anyhow, it’s a big paper, and there’s a lot to go through.  Let’s get started.

Right off the bat, I can see that they’re interested in the same problem that I am:

Peer review, while it has many known benefits (Zeller 2000; Papalaskari 2003; Wolfe 2004; Hamer, Ma et al. 2005; Trytten 2005), and is used extensively in other fields (Falchikov and Goldfinch 2000; Topping, Smith et al. 2000; Liu and Hansen 2002; Dossin 2003; Carlson and Berry 2005) and in industry (Anderson and Shneiderman 1977; Anewalt 2005; Hundhausen, Agrawal et al. 2009), is not as widely used in the computer science curriculum.  This may be due, in part, to a lack of information about what, who and when to review in order to achieve specific goals in computer science.

This next part got my attention:

That is not to say that the literature is silent on these issues.  The studies make these choices but there are few reasons given for the decisions and even fewer comparisons performed to show relative value of those options.

Holy smokes.  A pretty bold critique of those previous papers (at least one of which, I’ve already reviewed).  It sounds like Scott and Manuel were as disappointed in some of the peer code review literature as I was.  If I was part of an audience that was being read this paper aloud, I would “wooo!” at this point.

What is needed is a clearer understanding of the requirements that the discipline imposes on the peer review process so that it may be effectively used.

Cool – I’m looking forward to seeing what they dug up.

Reading onwards through the introduction, I’m seeing the same basic arguments for peer code review that I’ve seen elsewhere.  I’ll summarize:

  • PCR (peer code review)  involves active use of higher levels of Bloom’s Taxonomy:  synthesis, analysis and evaluation, both for reviewers and review-ees
  • PCR prepares students for industry, since code review is (or should be) a common part of professional software development

Soon after, a good point is brought up – PCR is potentially a beneficial learning activity, but it all depends on the goals of a particular assignment.  A particular review structure may be better for improving code quality, and another might be better for increasing student motivation.  These considerations need to be taken into account when choosing a PCR structure.

By PCR structure, I think the writers mean:

  • What is being reviewed – source code vs design diagrams, for example
  • Who is being reviewed – students could review one another, or they could all review a piece of code provided by the instructor
  • When the review occurs – what level of students should take part in PCR?  Is there a minimum grade level that must be achieved before PCR is effective?  And when, during a project, should PCR happen?  Early in the design process, or after-the-fact – like a “code autopsy”?

These are good questions.  No wonder this paper is so long – I think their experiment is going to try to answer them all.

And just when things are starting to get good…they go into a literature review.  Yech.  I know it’s important to lay the groundwork, but I think I just felt my eyes turn to oatmeal.

The literature starts by briefly listing off those sources again – past papers who have tried to deal with this topic.  They categorize them based on what the papers try to deliver, and then they give them a light slam for not having a scientific basis on which to form the structures of their PCR structures.  I heartily agree.

The first part of the literature review discusses the benefits of peer review in other fields.  Papers as far back as the 1950’s are cited.  I think it goes without saying that having other people critique your work can be a great way of receiving constructive feedback (ask any playwrite, for example).  I guess these fellas feel they have to be pretty rigorous though, and really ground their argument in some solid past work.  Power to them.

An interesting notion is brought up – peer reviews over an extended length of time within the same groups helps cultivate “interaction between…peers and for the building of knowledge”.  One-time reviews, however, “[lends] itself more to a cognitive approach…more attention can be paid to the changes in the students’ thought processes”.  Hm.

This fellow named Topping seems to be quite popular with these guys.  Apparently, he came up with something called “Topping’s Peer Review Topology”, and I get the feeling that he is one of their primary sources in figuring out different ways of constructing PCR structures.

Oh, and an important morsel just got snuck in:

We are interested in how the student is affected by the acts of reviewing and being reviewed rather than by the social interaction occurring during the process.

So that sense of community that that other paper was talking about – not being looked at here.

The paper then goes on to chisel down some of the jargon from Topping’s Topology, and make it fit the field of Computer Science.  By doing this, the writers simpy reiterate the variables they’re going to be playing with:  what, who, and when.

The paper then dives into a two page summary of some peer review papers, and the various results that they found.  They note a few instances where peer review seemed to improve student performance, and other cases where peer review resulted in semi-disaster.  There are just as many theories as there are conflicting accounts.  From reading this stuff, it seems that peer review is a vast and complicated topic, and nobody seems to really have a firm grasp on it just yet.

Likewise, rubric creation seems to be a bit of a contentious topic:

While there seems to be a general consensus that rubrics are important and that they improve the peer review activity, there is not as much agreement on how they should be implemented.

However, it is clear that rubrics are useful in peer review for novice reviewers:

Rubrics can supply the guidance students need to learn how to evaluate an assignment.  It provides the needed scaffolding until the students are comfortable witht he process and the domain to make correct judgements.

Makes sense to me.

The paper then asks an important question: what makes a “successful” review in the education context?  Greater understanding?  Learning new concepts?  Improved grades?  Better designs?  Fewer code defects?

The answer:  it really depends on the instructor, and what the course wants from the PCR process.  For example, what is more important – having the reviewer learn to review?  Or having the review-ee receive good feedback?  Or both?  PCR is complex, and has lots of things to consider…

The next section highlights how technology is used to support peer review.  One particularly interesting example, is of a Moodle module that allows for peer reviews on assignments.  Apparently, the authors are fans.  I’ve never used Moodle before, and haven’t yet found the module that they’re talking about, but it sounds worth investigation.

The very next section details their experiment – their method, their data, and their results.  However, this post is getting a bit long, so I’m going to stop here, and continue on in a second post.

Stay tuned for the exciting conclusion!

Process Improvement of Peer Code Review and Behavior Analysis of its Participants

Process Improvement of Peer Code Review and Behavior Analysis of its Participants

by WANG Yan-qing, LI Yi-jun, Michael Collins, LIU Pei-jie
SIGCSE ’08, March 12-15, 2008

If you’ve been following, I’ve been trying to figure out why code reviews aren’t a part of the basic undergraduate computer science curriculum.  The other papers and articles I’ve read so far have had less to do with the classroom, and more to do with code reviews in industry.

This paper got a little bit closer to the classroom, and, more importantly, closer to my particular question.

To begin, the paper introduces some terminology I’m not familiar with – the software crisis.  I’m familiar with the concept though:  writing good software for large systems is not a simple problem, and as computers become a bigger and more important part of our lives, this inability to easily write good code could quickly end up biting us in the collective rear.

Code review is one of several methods that the software industry has adopted to try to “tame” the software crisis.

I like this part:

Even though code reviews are time consuming, they are much more efficient than testing [19]. A typical engineer, for example,  will find approximately 2 to 4 defects in an hour of unit testing but will find 6 to 10 defects in each hour of review code [19].

What more argument do you need?  It’s just a matter of getting rid of that “time consuming” part, right?  Right…

And this is even juicier:

PCR [peer code review] is a technique which is generally considered to be effective on promoting students’ higher cognitive skills [9], since students use their own knowledge and skill to interpret, analyze and evaluate others’ work to clarify and correct it [2].

Wonderful!  I’m in my problem space!

Reading along, it seems that this paper is introducing a new, refined structure for PCR, and will detail results of a study on using that new structure in a programming course.  Cool.

The introduction ends by saying that the new structure seemed to enhance the quality of student’s work, as well as their ability to critique one another.  Great news!

It’s not all sunshine and puppies, though – they also mention that they ran into a few problems, and that they’ll be discussing those too.

So the first thing they’ve done, is tried to make the terminology clearer:


  • Author:  the student who writes the code that is being reviewed
  • Reviewer:  the person who is reviewing the code
  • Reviser:  the author, after receiving a Comments Form from a Reviewer
  • Instructor:  the teacher or qualified TA who is responsible for the class


  • Manuscript Code:  the unrevised code that is first submitted by an Author
  • Comments Form:  the comments given from the Reviewer to the Author
  • Revision Code:  the code that is revised by the Reviser after the Reviewer gives the Reviser the Comments Form (whew…follow that?)
  • Reference Solution:  the “answer” to the assignment, held by the Instructor

Now that we’ve got all the players and documents laid out, let’s take a look at the process:


  • Phase 1:  The Author completes the Manuscript Code
  • Phase 2:  The Author emails the Manuscript Code to the Instructor.  Simultaneously, a blank Comments Form and a copy of the Manuscript Code is sent to a Reviewer
  • Phase 3:  The Reviewer reviews the code as soon as possible, filling in the Comments Form.
  • Phase 4:  The Reviewer sends the completed Comments Form back to the Author, and also sends a carbon copy to the Instructor
  • Phase 5:  After receiving the Comments Form, the Reviser (who was originally the Author…oh boy…almost went cross-eyed, there) makes the appropriate alterations to the original Manuscript Code, referencing the Comment Form where appropriate.  The completed Revision Code is emailed to the Instructor.
  • Phase 6:  The Instructor should now have a copy of the original Manuscript Code, the completed Comments Form, and the final Revision Code.  The Instructor should be able to check that the author and reviewer did their work properly.

Wow.  What a convoluted way of saying something simple.  They even included a diagram, with lots of arrows.  Somehow, I think this could be said simpler.  Oh well.

It also sounds like a lot of emailing.  You’re balancing your course on the reliability of the email protocol?  Errr….

Well, let’s see what problems they ran into…

  1. The assumption that all participants would carefully and responsibly carry out each phase of the process was faulty.  This may have been due to “careless authors, irresponsible reviewers and busy instructors in the review process”.
  2. Some students lack the coding ability to either:
    1. Produce code that is readable and reviewable in a constructive way
    2. Review code in a constructive, or informed way
  3. The process is difficult to control due to the reliance on email (no kidding!)
    1. Some students would not submit Manuscript Code or Comment Forms on time
    2. Some students would submit multiple copies of their Manuscript Code, due to an inherent mistrust of the reliability of email
  4. There was opportunity for students to “game” the process to their advantage. In this particular study, there was very little control of who was doing what.  Though a particular Author was supposed to write the Manuscript Code, this wasn’t enforced, and there was an occasion where another student wrote the code instead.  Same with review writing, and revision writing.  Yeah, cheating is always a problem.

The paper then goes into some discussion about the observed behaviour of Authors and Reviewers.  They noted that most students did not enjoy reviewing very poorly written code, and don’t give their best efforts on reviews for such code.  Mere encouragement from the instructor was not enough to compel them to give their best reviews either.  The paper suggests finding some way of making Reviewers review code more carefully; perhaps through awarding bonus marks.

Behaviour of Instructors was also analyzed.  The paper mentioned that Instructors with large class sizes might try to cut down on their workload by only viewing the Comment Forms that the Reviewers had provided.  But this strategy does not give the Instructor the entire story, and is open to manipulation from students.

The paper ends with a discussion about group formations, and how best to diffuse student cheating conspiracies.

At the last moment, they suggest some “web-based [application] with a built-in blind review mechanism” be developed.